Search Results (335)

Grafting is a widely used technique to improve stress tolerance in horticultural plants. However, little is known about how grafting affects citrus growth under low-nitrogen (N) stress. To investigate the responses of different grafting combinations to low N availability, we examined root morphology, photosynthesis, chlorophyll fluorescence and semi-quantitative mineral profiles in grafted and ungrafted citrus plants subjected to two N levels (10 and 0.15 mM NO₃⁻ -N) under potted conditions. Analyses were performed on roots and leaves of six plant combinations: ungrafted Trifoliate orange (Poncitrus trifoliata L. Raf., Pt) and red tangerine (Citrus reticulata Blanco, Cr); self-grafted combinations (Pt/Pt and Cr/Cr); and reciprocal heterografts (Pt/Cr and Cr/Pt). Under low-N stress, plant height decreased by 12.3–36.8%, stem diameter by 2.9–31.8%, leaf area by 18.2–26.3%, and SPAD by 11.6–24.5% across the six combinations, with the Cr/Cr combination showing the largest reductions in all parameters. The highest net photosynthetic rate (P_n), intercellular CO₂ concentration (C_i), stomatal conductance (Gs), electron transport rate (ETR), maximum quantum efficiency of PSII (Fv/Fm) and effective quantum efficiency of PSII (Fv’/Fm’) were observed in the Pt and Pt/Pt plants. Low-N stress reduced chloroplastid pigment contents and limited photosynthetic rates. Under 10 mM N treatment, the Fv/Fm values of Pt, Cr, Pt/Pt, and Cr/Pt were approximately 0.82, whereas those of Pt/Cr and Cr/Cr were below 0.82, suggesting lower maximal PSII efficiency in combinations with Cr rootstock. Regarding mineral elements, under low-N stress, the relative levels of P, K, Ca, Mg, and Fe in leaf and root sap increased, while those of N, Cu, Zn, B, and Mn decreased. Overall, combinations with Pt rootstock (Pt/Pt and Cr/Pt) showed better growth and photosynthetic performance, and more stable mineral profiles under low-N stress than combinations with Cr rootstock (Cr/Cr and Pt/Cr). These findings provide a physiological basis for understanding rootstock-specific responses to low-N stress under controlled conditions. Full article

This study aimed to determine the optimal biochar application rate for sustaining cotton productivity in moderately saline soils under dry sowing with wet emergence (DSWE) conditions in Shaya County, Xinjiang. A two-year field experiment, arranged in a randomized complete block design with two replicates, evaluated six biochar application rates (S1–S6) against a non-amended control (CK). The biochar, derived from fruit-wood via limited-oxygen pyrolysis at 500 °C (pH 9.82, porosity 64.5%), was applied as a single pre-sowing amendment. Soil water–salt dynamics, crop emergence, and growth parameters were continuously monitored. The results indicated that biochar application consistently reduced soil salinity; specifically, seedling-stage salinity decreased by 30.1–42.2% in the first year compared with the CK. Cotton emergence and yield improved significantly across both seasons. However, the optimal application rate for maximizing yield varied between years. While a high rate (S5: 25 t·hm⁻²) produced the highest first-year yield (6243.8 kg·hm⁻²), a moderate rate (S3: 15 t·hm⁻²) demonstrated greater yield stability and achieved the maximum yield (5975.2 kg·hm⁻²) in the second year. This interannual shift is likely attributable to biochar aging and structural pore saturation in the high-dose plots. Combined with high regional evaporation, these factors exacerbated secondary salinization and reduced the residual benefits of the amendment over time. In contrast, the moderate dose maintained a more effective balance between continuous water–salt regulation and nutrient availability. Under the experimental conditions, a single pre-sowing application of 15 t·hm⁻² biochar, combined with a 375 m³·hm⁻² drip irrigation volume, is recommended as an effective strategy to ameliorate salinity and support long-term yield stability. Full article

The continuous downward mining of close-distance coal seam groups faces severe challenges, yet existing research rarely addresses the structural failure mechanisms in groups with three or more layers. To address this, a two-dimensional physical similarity simulation combined with non-contact digital image correlation (DIC) technology and fractal geometry theory was conducted based on the geological conditions of Donghuantuo Coal Mine. This multi-method approach ensured the high-precision capture and validity of the spatiotemporal deformation data. The evolution of overlying strata and fracture networks during the extraction of four close-distance coal seams was quantified. The results indicate that underlying seam mining triggers severe secondary activation of upper goafs, which transforms the classic vertical three-zone structure into a composite trapezoidal failure zone. Driven by structural instability, the maximum subsidence of the overlying strata exhibits a step-like nonlinear growth, increasing dramatically from an initial 0.44 m to 8.70 m. Simultaneously, the topological evolution of the fracture network exhibits an overall nonlinear increase. Specifically, the fractal dimension rose from an initial value of 1.234 to a more stable value of 1.437, featuring two significant surges with growth rates of 8.34% and 3.79% that directly corresponded to spatial goaf connectivity. The mutual verification between the macroscopic displacement jumps and the fracture network evolution confirms the reliability of the obtained results. Ultimately, the mechanical model of the interlayer rock transitions from a rigid load-bearing beam to a loose buffer layer. Based on these mechanisms, a differentiated interlayer support strategy is proposed. High pre-tension and impact-resistant supports must be applied to the upper seams, whereas pressure-relief and flexible yielding supports are required for the lower seams. This study provides theoretical guidance for disaster prevention in close-distance coal seam groups mining. Full article

Ammonia-oxidizing bacteria (AOB) are the rate-limiting microbial group in biological nitrogen removal. However, difficulties in isolation and cultivation, along with unclear metabolic regulation mechanisms, have long constrained their engineering applications. Existing research has mostly focused on the responses of model strains to environmental factors, while studies on the growth regulation mechanisms driven by key medium components remain scarce. Moreover, there is a lack of efficient strains suitable for complex wastewater with high ammonia and high salinity. To isolate an efficient strain and optimize its culture conditions for high-ammonia wastewater treatment, we collected water samples from a polluted river in Zhongshan City. After enrichment, a strain was isolated via gradient dilution and silica gel plating, identified by scanning electron microscopy and 16S rDNA sequencing as Nitrosomonas europaea W4 (99.93% similarity to the type strain). Single-factor medium optimization examined CaCO₃ and Fe²⁺/Fe³⁺, while temperature and initial ammonia nitrogen effects were tested, and landfill leachate was used for verification. CaCO₃ shortened the lag phase without affecting maximum specific growth rate; replacing Fe³⁺ with Fe²⁺ further reduced lag and enhanced the ammonia oxidation rate. Optimal growth occurred at 25–30 °C and an initial ammonia nitrogen concentration of ~2000 mg/L. In landfill leachate, the strain increased the ammonia degradation rate 6.3-fold, from 4.64 ± 0.11 mg L⁻¹ d⁻¹ in the uninoculated control group to 29.32 ± 0.07 mg L⁻¹ d⁻¹, and importantly, nitrite can be rapidly degraded by indigenous denitrifiers, posing no secondary pollution risk. Overall, N. europaea W4 exhibits high ammonia oxidation efficiency, and the optimized medium and conditions improve its proliferation and metabolic stability, providing a basis for cultivation and application in treating high-strength ammonia nitrogen wastewater. Full article

To elucidate the evolution of dynamic recrystallization (DRX) mechanisms in cold-worked Cr4Mo4Ni4V martensitic steel, tensile tests were conducted on a 50% cold-deformed material at 600–850 °C at a fixed strain rate of 0.001 s⁻¹, combined with systematic microstructural characterization. Under this specific strain rate, the results reveal a temperature-dependent transition from continuous dynamic recrystallization (CDRX) to discontinuous dynamic recrystallization (DDRX). At 600 °C, CDRX dominates, producing recrystallized grains with orientations close to the parent matrix and relatively strong texture. At 750 °C, CDRX and DDRX coexist, while DDRX is significantly enhanced, characterized by grain boundary nucleation and random orientations, leading to a marked reduction in texture intensity; simultaneously, the fraction of recrystallized grains and high-angle grain boundaries reaches a maximum. At 850 °C, DDRX becomes dominant. This transition in DRX mechanism governs the high-temperature plasticity, with optimal superplasticity achieved at 800 °C, corresponding to an elongation of 748%. Cavities are primarily initiated at carbide/matrix interfaces, and their growth and coalescence dominate the fracture process. These findings clarify the temperature-dependent DRX evolution and its role in regulating superplasticity, providing guidance for microstructure design and superplastic forming of martensitic steels. Full article

Temperature abuse during storage represents a critical factor influencing microbial behavior in meat products, particularly in non-conventional matrices such as guinea pig meat. This study aimed to characterize and compare the primary growth kinetics of Aerobic mesophilic bacteria and Staphylococcus aureus (S. aureus) in guinea pig meat burgers under controlled temperature abuse conditions (30, 35, and 40 °C). Microbial growth was monitored over 96 h and described using the modified Gompertz model to estimate key kinetic parameters, including maximum specific growth rate (µ_max) and lag phase duration (λ). Aerobic mesophilic bacteria exhibited increasing µ_max values with temperature, indicating enhanced metabolic activity under elevated thermal conditions. In contrast, S. aureus showed reduced µ_max and prolonged λ at 40 °C, suggesting stress-induced modulation of growth dynamics. These findings demonstrate that temperature increases do not uniformly accelerate microbial proliferation across different populations within the same food matrix. The contrasting kinetic responses indicate that Aerobic mesophilic bacteria and S. aureus respond differently to temperature abuse conditions, highlighting that total aerobic counts alone may not reliably predict pathogen behavior in guinea pig meat burgers. Full article

Background/Objectives: Abdominal aortic aneurysm (AAA) surveillance is based largely on monitoring the maximum diameter, a single scalar metric that obscures regional remodeling and offers limited information on the location and time dependency of the growth rate. The present work addresses this limitation with a geometry-based patient-specific framework that learns local, linear evolution from longitudinal clinical imaging, yielding 3D forecasts of AAA geometry at arbitrary future times. Methods: Lumen and outer wall surfaces are represented on a centerline-anchored cylindrical grid, with subsequent implementation of individualized linear mixed-effects models. The model is explicitly interpretable as the fixed effects predict global trends and the random effects represent regional heterogeneity. In a multicenter cohort of 79 patients, we evaluated forecasts using spatial similarity (with the 95th percentile of the Hausdorff distance—HD95) and clinically relevant global geometric scalars such as maximum diameter and volume. Results: When forecasting a future AAA geometry, the model achieved sub-millimetric HD95 spatial errors and less than 6% error for the aforementioned global scalars. The model was deployed in an interactive application named the Aneurysm Forecasting Studio, which allows a user to visualize the AAA in an explorable forecast space. Conclusions: During typical clinical surveillance intervals, AAA geometric remodeling is reasonably approximated as locally linear in time, enabling transparent, fast forecasts that support surveillance optimization, threshold timing, and digital twin-based interventional planning. Full article

The present study provides a high-frequency empirical assessment of the financial performance, volatility, and market integration of thematic sustainability-oriented equity funds, focusing on clean energy and environmental innovation indices. Specifically, the study compares the financial performance of representative thematic green equity funds, such as ICLN and QCLN, and an emerging-market benchmark (ECON) with conventional developed-market indices (SPY, QQQ, GSPC, and XLE) using daily stock prices from 2010 to 2025. The analysis employs a transparent and replicable framework based on daily logarithmic and cumulative returns and incorporates the compound annual growth rate (CAGR), Sharpe and Sortino ratios, beta estimation, correlation analysis, and maximum drawdown. The research frequency is appropriate for a thorough analysis of short-term market structures and performance. The results indicate that sustainability-oriented equity indices exhibit higher volatility, deeper drawdowns, and greater sensitivity to broad market movements than conventional benchmarks. Sustainability-focused equity indices that emphasize clean energy exhibit higher market sensitivity (betas above 1) and strong correlations with traditional equity indices. Correlation and beta estimates suggest a high degree of integration with traditional equity markets, implying limited diversification benefits within an equity-only framework. Periods of relative outperformance appear to be associated with favorable policy conditions and energy market dynamics, but are not consistently sustained over the sample period. In addition, the overall results suggest that sustainability investments generate substantial environmental and social externalities. Risk-adjusted performance measures suggest weaker historical performance over the sample period relative to conventional benchmarks. These findings should be interpreted as a comparative historical assessment rather than a structural risk model. From a policy perspective, the findings suggest that stable and credible regulatory frameworks, including long-term climate policy support and investment-enabling institutions, may be important for improving the financial resilience and long-term viability of green equity instruments. From a sustainability transition perspective, the observed volatility and market dependence of sustainability-oriented equity indices may constrain their effectiveness as standalone market-based financing mechanisms without complementary institutional and policy support. Full article

The aim of this study was to identify SNPs in the cattle genome associated with estimated breeding values of feet (EBV_feet) in Holstein-Friesian (HF) cows in Hungary. Foot health is of major importance in dairy cattle industry whereas claw disorders are leading to lameness and thus result in low fertility rates and productivity. Genotyping was performed using the EuroG_MDv4 microarray platform. The final database comprised 2963 animals and 59,151 SNPs. EBV_feet values have been divided into high and low groups. All calculations regarding the genetic differentiation (genome-wide and locus-specific) between high- and low-value groups for EBV_feet, linear regression, and haplotype association tests have been performed with the SNP and Variation Suite software. Thirty-nine SNPs associated with EBV_feet were determined on BTAs 3, 7, 8, 15, 21, and X. The maximum values of the identified SNPs were 0.22 for F_{st_marker}, 23.1 for the −log10(p) of the linear regression, and 26.3 for the −log10(p) of the haplotype association tests on BTA 3. The closest genes to SNPs associated with estimated breeding values for feet (EBV_feet) are mainly associated with tissue structure, immune response, metabolism, growth, development, transport and signaling. Our results could add additional information to the genetic programs focusing on the improvement of foot health in HF cattle. Full article

With rising incidence in recent years, Listeriosis, a severe foodborne disease in humans primarily transmitted through ready-to-eat (RTE) foods contaminated with Listeria monocytogenes, became the most severe zoonotic disease in the European Union (EU) in 2024 with the highest hospitalization and mortality rates, prompting stricter regulatory requirements under Regulation (EC) No 2073/2005 and its recent amendments. This systematic literature review aimed to evaluate the availability, validity and quality of published challenge test data on the growth potential and maximum growth rate of Listeria monocytogenes in RTE foods to identify data gaps and, if possible, to support the derivation of a classification of RTE foods into the two existing regulatory categories, a and b (not able and able to support the growth of Listeria monocytogenes). Conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and the Cochrane Handbook, a comprehensive database search was done to identify eligible challenge test studies on Listeria monocytogenes growth in RTE foods, followed by structured screening and quality assessment based on the EURL Lm Technical Guidance Documents. A limited and heterogeneous body of published challenge test data on the growth potential and maximum growth rate of Listeria monocytogenes in RTE foods was identified, with substantial data gaps across multiple food groups, precluding meta-analysis and limiting regulatory applicability under the current regulations. Overall, the available literature is insufficient to reliably support regulatory classification or to enable direct extrapolation by food business operators (FBO), underscoring the need for product-specific investigations and food group-specific guidance for food safety. Full article

The Changbai Mountain–Liaodong region is a crucial component of the global black soil belt in Northeast China and a significant national grain production base. However, like many high-latitude agricultural regions worldwide, it faces persistent challenges during the spring sowing period, including low soil temperatures and excessive moisture. Therefore, developing region-specific, effective methods of reducing soil moisture and increasing temperature while improving soil fertility is essential for improving agricultural productivity. To this aim, a field experiment was conducted with two factors: a main plot subjected to ridge tillage (RT) and flat tillage (FT) and subplots with biochar (BC) and straw (ST) amendments. A subplot with no amendment (CK) was used as a control. During maize growth, the daily soil temperature and moisture were monitored, and the soil water evaporation rates and physical structure, as well as the maize yield performance, were evaluated. The results showed that biochar and straw application significantly decreased the soil monthly water content by 1.69–2.22% (p < 0.05) in the surface soil layer (0–15 cm) from May to June, with a more pronounced effect under RT. In contrast, biochar application increased soil moisture and water storage from July to September, indicating that the influence of biochar on soil moisture depends on time and field aging processes. Biochar amendment raised the soil maximum temperature by 0.32–0.79 °C in the top 0–15 cm layer, while straw incorporation decreased the minimum soil temperature by 0.11–0.52 °C. The increase in soil temperature was primarily due to the biochar’s darker color, which facilitated solar radiation absorption, while the decrease in soil temperature was caused by the “Wind Leakage Effect” induced by the large particle size of the straw. Biochar and straw incorporation effectively enhanced maize dry matter accumulation by an average of 15.8% and 8.2%, respectively, and grain yield by 13.0% and 7.8%, respectively. Correlation analysis indicates that these increments are primarily due to enhanced soil moisture and available N content during the middle to late stages of maize growth. Therefore, the integration of straw and biochar with high-ridge cultivation is an effective strategy for excessive moisture reduction and warming in spring soil and it also contributes positively to maize yield. Full article

Spectrum scarcity has become a critical issue due to the rapid deployment of fifth-generation (5G) networks and the explosive growth of future wireless data traffic. Spectrally Efficient Frequency Division Multiplexing (SEFDM) is a promising technique to enhance spectral efficiency by compressing subcarrier spacing and allowing spectral overlap; however, it suffers from severe inter-carrier interference (ICI) caused by the loss of orthogonality. In particular, under Rayleigh fading channels, the combined effects of ICI and multipath fading lead to significant degradation in bit error rate (BER) performance. Conventional SEFDM systems employing a cyclic prefix (CP) encounter an unavoidable error floor due to residual interference stemming from non-orthogonality. On the other hand, while zero-padding (ZP)-based SEFDM offers superior multipath tolerance, further enhancement in communication quality is still desired. This paper proposes a novel receiver architecture utilizing sector antennas to spatially separate multipath components based on the angle of arrival (AoA). Furthermore, we investigate and compare sector selection algorithms specifically tailored for SEFDM systems. Simulation results demonstrate that the proposed method, employing a sector selection scheme based on the maximum channel response power, effectively suppresses inter-symbol interference (ISI) and improves BER performance for both CP-SEFDM and ZP-SEFDM. Furthermore, our quantitative evaluations confirm that the proposed architecture successfully achieves the theoretical maximum spectral efficiency even in higher-order modulation schemes (16QAM), while maintaining a low computational complexity compared to conventional spatial diversity techniques. Full article

The industrial application of starter cultures requires stable physiological and genetic performance. In this study, Streptococcus salivarius subsp. thermophilus and Lactobacillus delbrueckii subsp. bulgaricus were continuously subcultured. Physiological stability was assessed through colony morphology, fermentation activity, and growth profiling. Genetic stability was evaluated through comparative genomics of carbohydrate metabolism networks and single-nucleotide polymorphism (SNP) analysis. The results showed that after 2000 generations, the cellular morphology of the strains remained intact. Additionally, the strains exhibited enhanced growth performance and fermentation capability. The Gompertz model revealed that adapted S. thermophilus A37 and L. bulgaricus B29 exhibited shortened lag phases, increased maximum specific growth rates, and high stationary-phase cell densities. Phenotypic microarray and comparative genomics revealed that S. thermophilus mainly used mono- and disaccharides, with impaired ribose metabolism due to the absence of the rbsk gene in the pentose phosphate pathway. In contrast, L. bulgaricus metabolized diverse oligosaccharides, sugar alcohols, and plant-derived substrates. Additionally, it effectively catabolized ribose through the phosphoketolase pathway and possessed a trehalose degradation cluster. All strains exhibited genomic stability, with SNPs revealing fewer than 21 variations per isolate. This study provides an important theoretical foundation for evaluating the stability of fermentation starter cultures. Full article

Limosilactobacillus fermentum KUB-D18 is a probiotic strain with significant potential in food fermentation and health promotion, yet the systems-level mechanisms underlying its physiological robustness remain elusive. To elucidate the metabolic remodeling strategies operating across growth phases, we developed an integrated framework combining genome-scale metabolic modeling (GSMM) with transcriptomics. A high-quality metabolic model for L. fermentum KUB-D18, designated iYH640 and comprising 640 genes, 1530 metabolites, and 1922 reactions, was constructed and validated against experimental growth data. Specifically, in vitro assays measuring biomass and glucose concentrations showed a maximum specific growth rate of 0.2696 h⁻¹ and a glucose uptake rate of 11.75 mmol gDCW⁻¹ h⁻¹, providing physiological constraints for the model. Using transcriptome-regulated flux balance analysis (TR-FBA), gene expression profiles from the logarithmic phase (L-phase) and stationary phase (S-phase) were integrated to quantify growth phase-specific metabolic flux distributions. These simulations revealed a distinct transcription-driven metabolic shift, in which the organism moves from a proliferation-oriented metabolic state with active central carbon metabolism and macromolecule synthesis to a maintenance-oriented state. This S-phase is characterized by reduced flux through anabolic pathways together with the selective preservation of redox balance and nucleotide homeostasis. Collectively, these results provide a quantitative explanation of how L. fermentum KUB-D18 balances growth and maintenance, offering a mechanistic basis for improving its stability and functional performance in industrial probiotic applications. Full article

The application of Genome-Scale Metabolic Network Models (GSMM) in fermentation optimization is hampered by challenges in differentiating viable from dead cells and parameter distortion induced by conventional detection methods. Using E. coli BL21(DE3) as the model organism, this study developed a flux analysis strategy that couples cell kinetics with GSMM. Key parameters were estimated using the gradient descent algorithm, thereby enabling precise prediction of viable cell concentration and glucose consumption dynamics. Integrating this with the Quadratic Programming-based parsimonious Flux Balance Analysis (QP-pFBA) algorithm, intracellular metabolic reaction fluxes were quantified. Results demonstrated that the model can effectively differentiate viable from dead cells; Batch D, adopting the gradient-increasing feeding strategy, achieved the maximum specific growth rate (μ_max) of 0.6457, the highest among the four batches. Moreover, key metabolic reaction fluxes were highly correlated with the feeding strategy. This framework forgoes specialized, high-cost equipment and offers robust cross-strain/process adaptability, thereby greatly advancing GSMM utility. It provides a powerful tool for precise fermentation control and accelerates the shift toward data-driven biomanufacturing. Full article