Search Results (120)

Global warming and anthropogenic climate change are projected to expand the geographic distribution and population abundance of ectothermic species and exacerbate the biological invasion of exotic species. DNA methylation, as a reversible epigenetic modification, could provide a putative link between the phenotypic plasticity of invasive species and environmental temperature variations. We assessed and interpreted the epigenetic mechanisms of invasive and indigenous species’ differential tolerance to thermal stress through the invasive species Bemisia tabaci Mediterranean (MED) and the indigenous species Bemisia tabaci AsiaII3. We examine their thermal tolerance following exposure to heat and cold stress. We found that MED exhibits higher thermal resistance than AsiaII3 under heat stress. The fluorescence-labeled methylation-sensitive amplified polymorphism (F-MSAP) results proved that the increased thermal tolerance in MED is closely related to DNA methylation changes, other than genetic variation. Furthermore, the quantitative real-time polymerase chain reaction (qRT-PCR) and Western blotting analysis of DNA methyltransferases (Dnmts) suggested that increased expression of Dnmt3 regulates the higher thermal tolerance of female MED adults. A mechanism is revealed whereby DNA methylation enhances thermal tolerance in invasive species. Our results show that the Dnmt-mediated regulation mechanism is particularly significant for understanding invasive species’ successful invasion and rapid adaptation under global warming, providing new potential targets for controlling invasive species worldwide. Full article

The utilization of saline–alkali land for rice cultivation is critical for global food security. However, most existing studies on rice salt tolerance focus on the seedling stage, with limited insights into tolerance mechanisms during reproductive growth, particularly at the panicle initiation stage (PI). Leveraging precision salinity-control facilities, this study imposed four salt stress gradients (0, 3, 5, and 7‰) to dissect the differential response mechanisms of six rice varieties (YXYZ: Yuxiangyouzhan, JLY3261: Jingliangyou3261, SLY91: Shuangliangyou91, SLY138: Shuangliangyou138, HLYYHSM: Hualiangyouyuehesimiao, and SLY11:Shuangliangyou111) during PI. The results revealed that increasing salinity significantly reduced tiller number (13.14–68.04%), leaf area index (18.58–57.99%), canopy light interception rate (11.91–44.08%), and net photosynthetic rate (2.63–52.42%) (p < 0.001), accompanied by reactive oxygen species (ROS)-induced membrane lipid peroxidation. Integrative analysis of field phenotypic and physiological indices revealed distinct adaptation strategies: JLY3261 rapidly activated antioxidant enzymes under 3‰ salinity, alleviating lipid peroxidation (no significant difference in H₂O₂ or malondialdehyde content compared to 0‰ salinity) and maintaining tillering and aboveground biomass. SLY91 tolerated 7‰ salinity via CAT/POD-mediated lipid peroxide degradation, with H₂O₂ and malondialdehyde contents increasing initially but decreasing with escalating stress. These findings highlight genotype-specific antioxidant strategies underlying salt-tolerance mechanisms and the critical need for integrating phenomics–physiological assessments at reproductive stages into salt-tolerance breeding pipelines. Full article

In this study, two color morphs (red and green) of Asian swimming crab (Charybdis japonica) commonly distributed in the China Sea area were analyzed for their L*a*b* values, carapace and inner membrane histology, morphological characteristics, mitochondrial DNA sequences, muscle texture, and amino acid composition. The results showed that compared with the green morph group, the red morph group exhibits higher aggregation of melanocytes and fewer pigment cells in the inner membrane. In addition, L* and b* of the carapace, and L* values of the inner membrane were lower in red morph group. Both populations of C. japonica also exhibit significant differences in their morphological parameters, including carapace length, body weight, and pincer width. However, the coefficient of variation for these morphological parameters did not correspond to the subspecies level. The mitochondrial DNA analysis also revealed sequence identity of COI (98.96%) and ITS-1 (99.71%) genes in both groups, supporting them to belong to the same species. Both groups also presented significant differences in their muscle texture characteristics, including adhesiveness, springiness, and gumminess, but no significant differences were observed in the muscle amino acid composition. Overall, red and green morphs of C. japonica show differences in their body color, morphological characteristics, and muscle quality, but still belong to the same species. Full article

Fuzz defects are prevalent surface imperfections in carbon fiber-reinforced polymer (CFRP) prepregs. Current manual inspection methods or conventional neural network-based approaches face significant limitations in achieving standardized and accurate severity assessment of such defects. In this article, a methodology comprising three key technical innovations is proposed: First, an adaptive thresholding algorithm is implemented, utilizing local average grayscale values to accurately identify fuzz defect pixels. Second, a grayscale histogram analysis is performed on the identified defect regions to quantify severity levels, effectively mitigating the influence of substrate material variations and illumination conditions on assessment accuracy. Third, a quantitative formula is defined based on the detection boxes drawn by the neural network object detection model and the effective area of defects to evaluate the severity of fuzz defects. Experimental validation shows 90% consistency with practical manual assessment in defect severity ranking tasks, proving its industrial applicability. Full article

In recent years, congestion on port motorways has become increasingly frequent, significantly constraining transportation efficiency and contributing to higher pollution emissions. This paper proposes a novel max-pressure-driven integrated control (IFC-MP) for port motorways, inspired by the max pressure (MP) concept, which continuously adjusts the weights of ramp metering (RM) and the variable speed limit (VSL) based on pressure feedback from the on-ramp and upstream, assigning greater control weight to the side with higher pressure. A queue management mechanism is incorporated to prevent on-ramp overflow. The effectiveness of IFC-MP is verified in SUMO, filling the gap where the previous integrated control methods for port motorways lacked micro-simulation validation. The results show that IFC-MP enhances bottleneck throughput by approximately 7% compared to the no-control case, optimizes the total time spent (TTS) by 26–27%, and improves total pollutant emissions (TPEs) by about 11%. Compared to strategies that use only RM and VSL control, or activate VSL control only after RM reaches its lower bound, the time–space distribution of speed under IFC-MP is more uniform, with smaller fluctuations in bottleneck occupancy. Additionally, IFC-MP maintains relatively stable performance under varying compliance levels. Overall, the IFC-MP is an effective method for alleviating congestion on port motorways, excelling in optimizing both traffic efficiency and pollutant emissions. Full article

Background: Arthroscopic rotator cuff repair faces high retear risks in multi-tendon injuries due to insufficient biological healing; leukocyte-rich PRP may enhance tendon–bone integration through inflammatory modulation and growth factor release. Methods: Four databases including PubMed, Embase, Cochrane Library, and Web of Science were searched until March 2025. Literature screening, quality evaluation, and data extraction were performed according to inclusion and exclusion criteria. GRADE was used to grade the strength of the evidence and the results. Results: The main finding of this study was that leukocyte-rich platelet-rich plasma combined with arthroscopic surgery for rotator cuff injuries can improve the Constant Score (MD = 1.13, 95% CI: 0.19, 2.07, p = 0.02, I² = 47%), American Shoulder and Elbow Surgeons score (MD = 6.02, 95% CI: 4.67, 7.36, p < 0.01, I² = 0%), and University of California, Los Angeles score (MD = 1.20, 95% CI: 0.34, 2.06, p < 0.01, I² = 0%) of patients with rotator cuff tear after treatment, and reduce the postoperative Visual Analog Scale score (MD = −0.62, 95% CI: −1.16, −0.08, p = 0.02, I² = 83%) of patients. However, there were no statistical differences regarding the Simple Shoulder Test (MD = 0.08, 95% CI: −0.23, 0.39, p = 0.61, I² = 5%). Conclusions: Based on current evidence, the use of LR-PRP in arthroscopic rotator cuff repair could lessen postoperative pain and improve postoperative functional scores in individuals with rotator cuff injuries. Full article

Ship collisions pose a significant threat to maritime safety, especially in congested precautionary areas with high vessel traffic density. Traditional collision risk assessment methods, such as distance to closest point of approach (DCPA) and time to closest point of approach (TCPA), often overlook environmental uncertainties and variations in human response. To address these limitations, this study proposes a novel approach for collision risk assessment using automatic identification system (AIS) data. AIS data from vessels in precautionary areas are resampled to synchronize their temporal frameworks, enabling the systematic identification of ship encounters. Each encounter is analyzed by evaluating critical parameters, including the minimum ship encounter distance (MSED), relative azimuth angles, and trajectories, within a customized ship domain model that incorporates vessel characteristics such as ship length and course. Key metrics, such as intrusion depth and time, are calculated based on vessels’ entry and exit points during each encounter. A set of collision risk indices, which integrates both intrusion depth and time, is introduced, with particular emphasis on intrusion depth due to its heightened sensitivity to proximity danger and constrained maneuvering space. An extensive analysis of vessel interactions in the precautionary area establishes a holistic collision risk index. A case study using AIS data from Ningbo–Zhoushan Port, involving a dataset of 1000 ship encounters, demonstrates the effectiveness of the proposed method. Specifically, the holistic collision risk in the No.2 precautionary area is 0.456, while the No.3 precautionary area shows a risk value of 0.443. These results confirm the effectiveness and feasibility of the proposed method for evaluating and classifying collision risks, offering a more precise and reliable framework for collision risk assessment in complex navigational environments. Full article

Abnormal ship navigation behaviors in cross-sea bridge waters pose significant threats to maritime safety, creating a critical need for accurate anomaly detection methods. Ship AIS trajectory data contain complex temporal features but often lack explicit labels. Most existing anomaly detection methods heavily rely on labeled or semi-supervised data, thus limiting their applicability in scenarios involving completely unlabeled ship trajectory data. Furthermore, these methods struggle to capture long-term temporal dependencies inherent in trajectory data. To address these limitations, this study proposes an unsupervised trajectory anomaly detection model combining a transformer architecture with a variational autoencoder (transformer–VAE). By training on large volumes of unlabeled normal trajectory data, the transformer–VAE employs a multi-head self-attention mechanism to model both local and global temporal relationships within the latent feature space. This approach significantly enhances the model’s ability to learn and reconstruct normal trajectory patterns, with reconstruction errors serving as the criterion for anomaly detection. Experimental results show that the transformer–VAE outperforms conventional VAE and LSTM–VAE in reconstruction accuracy and achieves better detection balance and robustness compared to LSTM–-VAE and transformer–GAN in anomaly detection. The model effectively identifies abnormal behaviors such as sudden changes in speed, heading, and trajectory deviation under fully unsupervised conditions. Preliminary experiments using the POT method validate the feasibility of dynamic thresholding, enhancing the model’s adaptability in complex maritime environments. Overall, the proposed approach enables early identification and proactive warning of potential risks, contributing to improved maritime traffic safety. Full article

Background: Osteoporosis (OP) is a systemic bone disease often undiagnosed until fractures occur. Metabolites may influence OP, offering potential biomarkers or therapeutic targets. This study investigates the causal relationship between circulating metabolites and OP-related phenotypes using Mendelian Randomization (MR). Methods: GWAS data on 233 metabolic traits from 136,016 participants were analyzed through two-sample MR. Linkage disequilibrium score regression (LDCS) was used to estimate genetic correlations between metabolic traits and OP-related phenotypes, leveraging European ancestry linkage disequilibrium scores to account for polygenicity and stratification. MR employed the inverse-variance weighted (IVW) method, with sensitivity analyses via MR-Egger, MR-PRESSO, and weighted median methods to address pleiotropy and confounders. Results: LDCS identified significant genetic correlations between metabolites and bone mineral density (BMD) phenotypes, with total body BMD (toBMD) showing the strongest associations. Thirty-five metabolite traits, including apolipoprotein A-I, exhibited significant linkages. Among 79 metabolites influencing BMD, serum acetate levels were significantly associated with femoral neck BMD (OR: 1.28, 95% CI: 1.02–1.62), lumbar spine BMD (OR: 1.73, 95% CI: 1.32–2.27), and total body BMD (OR: 1.21, 95% CI: 1.04–1.42). Creatinine levels were consistently linked to reduced BMD, including lumbar spine BMD (OR: 0.88, 95% CI: 0.79–0.99). Triglycerides in IDL and VLDL particles also contributed to BMD variation. Conclusions: Significant genetic correlations and causal relationships were observed between specific metabolites and OP, highlighting key traits as potential biomarkers of bone health. These findings enhance the understanding of OP pathogenesis and suggest future preventive strategies. Full article

Synthetic Aperture Radar (SAR) constellations have become a key technology for disaster monitoring, terrain mapping, and ocean surveillance due to their all-weather and high-resolution imaging capabilities. However, the design of large-scale SAR constellations faces multi-objective optimization challenges, including short revisit cycles, wide coverage, high-performance imaging, and cost-effectiveness. Traditional optimization methods, such as genetic algorithms, suffer from issues like parameter dependency, slow convergence, and the complexity of multi-objective trade-offs. To address these challenges, this paper proposes a hybrid optimization framework that integrates chaotic sequence initialization and fuzzy rule-based decision mechanisms to solve high-dimensional constellation design problems. The framework generates the initial population using chaotic mapping, adaptively adjusts crossover strategies through fuzzy logic, and achieves multi-objective optimization via a weighted objective function. The simulation results demonstrate that the proposed method outperforms traditional algorithms in optimization performance, convergence speed, and robustness. Specifically, the average fitness value of the proposed method across 20 independent runs improved by 40.47% and 35.48% compared to roulette wheel selection and tournament selection, respectively. Furthermore, parameter sensitivity analysis and robustness experiments confirm the stability and superiority of the proposed method under varying parameter configurations. This study provides an efficient and reliable solution for the orbital design of large-scale SAR constellations, offering significant engineering application value. Full article

We propose and demonstrate a tunable femtosecond electro-optic optical frequency comb by shaping a continuous-wave seed laser in an all-fiber configuration. The seed laser, operating at 1.5 μm, is first cascade-phase-modulated and subsequently de-chirped to generate low-contrast pulses of approximately 8 ps at a repetition rate of 5.95 GHz. These pulses are then refined into clean, high-quality picosecond pulses using a Mamyshev regenerator. The generated source is further amplified using an erbium–ytterbium-doped fiber amplifier operating in a highly nonlinear regime, yielding output pulses compressed to around 470 fs. Tunable continuously across a 5.7~6 GHz range with a 1 MHz resolution, the picosecond pulses undergo nonlinear propagation in the final amplification stage, leading to output pulses that can be further compressed to a few hundred femtoseconds. By using a tunable bandpass filter, the center wavelength and spectral bandwidth can be flexibly tuned. This system eliminates the need for mode-locked cavities, simplifying conventional ultrafast electro-optic combs by relying solely on phase modulation, while delivering femtosecond pulses at multiple-gigahertz repetition rates. Full article

Soil reclamation is essential for restoring the ecological environment in coal mining subsidence areas, with reclaimed soil quality serving as a key indicator of success. Traditional evaluation methods often rely on subjective judgment, leading to potential biases. This study proposes an approach combining cluster analysis (CA), correlation degree analysis (CDA), principal component analysis (PCA), and membership function (MF) to evaluate soil reclamation quality in the Ezhuang subsidence area, Shandong Province, China. A minimum dataset (MDS) was established, including seven indicators: exchangeable magnesium, total nitrogen, available copper, available manganese, zinc, free iron, and available silicon. Soil quality indices (SQIs) were calculated using membership functions, revealing moderate soil quality across the reclamation area, with significant spatial variations. The northeastern section exhibited relatively good soil quality, while the northwestern and southeastern sections were poorer. Key factors influencing soil quality included variations in organic matter, exchangeable magnesium, and available copper. The accuracy of the CA-CDA-PCA-MF method was validated, with a coefficient of determination (R²) of 0.877 and a coefficient of deviation (CV) of 0.053, demonstrating its reliability. This method provides a robust tool for evaluating and improving soil restoration in mining areas, with potential applications in similar reclamation projects. Full article

With the growth of the global population and the acceleration of industrialization, the problem of water pollution has become increasingly serious, posing a major threat to the ecosystem and human health. Traditional water treatment technologies make it difficult to cope with complex pollution, so the scientific community is actively exploring new and efficient treatment methods. Biochar (BC), as a low-cost, green carbon-based material, exhibits good adsorption and catalytic properties in water treatment due to its porous structure and abundant active functional groups. However, BC’s pure adsorption or catalytic capacity is limited, and researchers have dramatically enhanced its performance through modification means, such as loading metals or heteroatoms. In this paper, we systematically review the recent applications of BC and its modified materials for water treatment in adsorption, Fenton-like, electrocatalytic, photocatalytic, and sonocatalytic systems, and discuss their adsorption/catalytic mechanisms. However, most of the research in this field is at the laboratory simulation stage and still needs much improvement before it can be applied in large-scale wastewater treatment. This review improves the understanding of the pollutant adsorption/catalytic properties and mechanisms of BC-based materials, analyzes the limitations of the current studies, and investigates future directions. Full article

The makapuno coconut endosperm is distinguished by its soft and irregular texture, in contrast to the solid endosperm of regular coconuts. To establish a scientific foundation for studying makapuno coconuts, callus was induced from makapuno endosperm using a combination of plant growth regulators. The induction was successful, and the resulting callus was subsequently subcultured for further study. Transcriptome sequencing of the makapuno callus identified 429 differentially expressed genes (DEGs), with 273 upregulated and 156 downregulated, compared to callus derived from regular coconut endosperm. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis indicated that these DEGs were involved in key metabolic pathways, including fructose and mannose metabolism, carbon fixation in photosynthetic organisms, galactose metabolism, and amino sugar and nucleotide sugar metabolism. Furthermore, lipid content analysis of the makapuno callus revealed a significantly higher total lipid level compared to regular callus, with notable differences in the levels of specific fatty acids, such as myristic acid, palmitic acid, and linoleic acid. This study establishes a novel platform for molecular biological research on makapuno coconuts and provides valuable insights into the molecular mechanisms underlying the formation of makapuno callus tissue. The findings also lay the groundwork for future research aimed at elucidating the unique properties of makapuno endosperm and exploring its potential applications. Full article

The modular multilevel converter (MMC) plays an important role in large-scale renewable energy integration and transmission, and it can also operate in standalone mode, powering AC passive loads. This paper focuses on the impact of load variation on the stability of the MMC. First, the impact of load variation on the MMC transfer function is analyzed in detail using the harmonic state-space (HSS) modeling method. Then, by means of the impedance-based stability analysis method, it is found that the MMC tends to become unstable with the increase in inductive loads. If the controller is not well-designed, the system may fail when loads change. Therefore, the worst-case design is used to guarantee the overall system’s stability under all load conditions. The impact of traditional proportional resonant (PR) controller parameters on the system’s stability is analyzed, revealing that the stability margin and control performance of the controller are limited. Thus, an improved controller structure with an additional series of compensators is proposed. Extensive simulation results in MATLAB/Simulink R2024a verify the analysis of this work and the effectiveness of the proposed controller. Full article