Search Results (130)

Bitter melon, an important medicinal and edible economic crop, is often threatened by diseases such as downy mildew, powdery mildew, viral diseases, anthracnose, and blight during its growth. Efficient and accurate disease detection is of significant importance for achieving sustainable disease management in bitter melon cultivation. To address the issues of weak generalization ability and high computational demands in existing deep learning models in complex field environments, this study proposes an improved lightweight YOLOv8-LSW model. The model incorporates the inverted bottleneck structure of LeYOLO-small to design the backbone network, utilizing depthwise separable convolutions and cross-stage feature reuse modules to achieve lightweight design, reducing the number of parameters while enhancing multi-scale feature extraction capabilities. It also integrates the ShuffleAttention mechanism, strengthening the feature response in lesion areas through channel shuffling and spatial attention dual pathways. Finally, WIoUv3 replaces the original loss function, optimizing lesion boundary regression based on a dynamic focusing mechanism. The results show that YOLOv8-LSW achieves a precision of 95.3%, recall of 94.3%, mAP50 of 98.1%, mAP50-95h of 95.6%, and F1-score of 94.80%, which represent improvements of 2.2%, 2.7%, 1.2%, 2.2%, and 2.46%, respectively, compared to the original YOLOv8n. The effectiveness of the improvements was verified through heatmap analysis and ablation experiments. The number of parameters and GFLOPS were reduced by 20.58% and 20.29%, respectively, with an FPS of 341.58. Comparison tests with various mainstream deep learning models also demonstrated that YOLO-LSW performs well in the bitter melon disease detection task. This research provides a technical solution with both lightweight design and strong generalization ability for real-time detection of bitter melon diseases in complex environments, which holds significant application value in promoting precision disease control in smart agriculture. Full article

This study evaluates the efficacy of a novel moisturizing cream using a sodium lauryl sulfate (SLS)-induced skin damage model, supported by advanced imaging with two-photon microscopy (TPM). TPM’s capabilities allow for in-depth, non-invasive visualization of skin repair processes, surpassing traditional imaging methods. The innovative formulation of the cream includes ceramide NP, ceramide NS, ceramide AP, lactobacillus/soybean ferment extract, and bacillus ferment, targeting the enhancement of skin hydration, barrier function, and structural integrity. In SLS-stimulated 3D skin models and clinical settings, the cream significantly improved the expression of key barrier proteins such as filaggrin (FLG), loricrin (LOR), and transglutaminase 1 (TGM1), while reducing inflammatory markers like IL-1α, TNF-α, and PGE2. Notably, the cream facilitated a significant increase in epidermal thickness and improved the dermal–epidermal junction index (DEJI), as observed through TPM, indicating profound skin repair and enhanced barrier functionality. Clinical trials further demonstrated the cream’s reparative effects, significantly reducing symptoms in participants with sensitive skin and post-intense pulsed light (IPL) treatment scenarios. This study highlights the utility of TPM as a groundbreaking tool in cosmetic dermatology, offering real-time analysis of the effects of skincare products on skin structure and function. Full article

Optimizing airflow organization is essential for ensuring the energy-efficient and secure operation of data centers. To address common airflow distribution issues in air-cooled systems, such as uneven air supply and cooling capacity imbalance, this study investigates a bidirectional airflow data center room located in a hot-summer and warm-winter region. A computational fluid dynamics (CFD) model was developed based on field-measured data to analyze the airflow distribution characteristics and evaluate the existing thermal conditions. Three optimization strategies were systematically examined: (1) Installation of rack blanking panels, (2) cold aisle containment with varying degrees of closure, and (3) combined implementations of these measures. Performance evaluation was conducted using three thermal metrics: the Return Temperature Index (RTI), Supply Heat Index (SHI), and Rack Cooling Index (RCIHI). The results demonstrate that among individual optimization strategies, rack blanking panels achieved the most significant improvement, reducing SHI by 42.61% while effectively eliminating local hotspots. For combined optimization strategies, the rack blanking panels and fully contained cold aisle containment showed optimal performance, improving cooling utilization efficiency by 88.26%. The optimal retrofit solution for this data center is the rack blanking panels with fully contained cold aisle containment. When considering budget constraints, the secondary option would be rack blanking panels with cold aisle top-only containment. These findings provide practical guidance for energy efficiency improvements in similar data center environments. Full article

Flexible wearable electronics face critical challenges in achieving reliable physiological monitoring, particularly due to the trade-off between sensitivity and durability in flexible electrodes, compounded by mechanical modulus mismatch with biological tissues. To address these limitations, we develop an anti-freezing ionic hydrogel through a chitosan/acrylamide/LiCl system engineered via the solution post-treatment strategy. The optimized hydrogel exhibits exceptional ionic conductivity (24.1 mS/cm at 25 °C) and excellent cryogenic tolerance. Leveraging these attributes, we construct a gel-based triboelectric nanogenerator (G-TENG) that demonstrates ultrahigh sensitivity (1.56 V/kPa) under low pressure. The device enables the precise capture of subtle vibrations at a frequency of 1088 Hz with a signal-to-noise ratio of 16.27 dB and demonstrates operational stability (>16,000 cycles), successfully differentiating complex physiological activities including swallowing, coughing, and phonation. Through machine learning-assisted analysis, the system achieves 96.56% recognition accuracy for five words and demonstrates good signal recognition ability in different ambient sound scenarios. This work provides a paradigm for designing environmentally adaptive wearable sensors through interfacial modulus engineering and ion transport optimization. Full article

Background: While parental type 2 diabetes (T2D) is a known risk factor for offspring T2D, the differential impact of maternal versus paternal transmission remains debated. Methods: This prospective family-based cohort study enrolled 4508 diabetes-free adults from Northern China with a median 7.32-year follow-up. Using Cox proportional hazards models, we examined parent-of-origin effects on T2D incidence, adjusting for lifestyle, adiposity, and metabolic covariates. Results: Parental T2D conferred elevated offspring risk (adjusted HR = 1.82, 95% CI:1.44–2.30), and was predominantly driven by maternal transmission. Maternal T2D was robustly associated with offspring risk (HR = 1.89, 95% CI: 1.47–2.43), whereas paternal T2D showed no significant effect (HR = 1.27, 95% CI: 0.88–1.84). Offspring with only maternal T2D history exhibited the highest risk (HR = 2.55, 95% CI: 1.87–3.50; p = 4.70 × 10⁻⁹), persisting after full adjustment, while no significant association was observed for paternal diabetes. Lifestyle modified this association: healthy diet (diet score > 2 vs. ≤2: HR = 1.34 vs. 2.76; p_interaction = 9.10 × 10⁻⁴) and regular exercise (regular vs. unregular: HR = 1.13 vs. 2.10; p_interaction = 4.20 × 10⁻²) attenuated maternal transmission. Conclusions: Maternal T2D confers greater intergenerational risk than paternal T2D, with modifiable lifestyle factors mitigating this association. These findings highlight the importance of integrating maternal diabetes history into clinical risk stratification tools and prioritizing lifestyle interventions in the offspring of affected mothers to mitigate inherited risk. Full article

The aerial–terrestrial integrated Internet of Things (ATI-IoT) utilizes both aerial platforms (e.g., drones and high-altitude platform stations) and terrestrial networks to establish comprehensive and seamless connectivity across diverse geographical regions. The integration offers significant advantages, including expanded coverage in remote and underserved areas, enhanced reliability of data transmission, and support for various applications such as emergency communications, vehicular ad hoc networks, and intelligent agriculture. However, due to the inherent openness of wireless channels, ATI-IoT faces potential network threats and attacks, and its security issues cannot be ignored. In this regard, incorporating physical layer security techniques into ATI-IoT is essential to ensure data integrity and confidentiality. Motivated by the aforementioned factors, this review presents the latest advancements in ATI-IoT that facilitate physical layer security. Specifically, we elucidate the endogenous safety and security of wireless communications, upon which we illustrate the current status of aerial–terrestrial integrated architectures along with the functions of their components. Subsequently, various emerging techniques (e.g., intelligent reflective surfaces-assisted networks, device-to-device communications, covert communications, and cooperative transmissions) for ATI-IoT enabling physical layer security are demonstrated and categorized based on their technical principles. Furthermore, given that aerial platforms offer flexible deployment and high re-positioning capabilities, comprehensive discussions on practical applications of ATI-IoT are provided. Finally, several significant unresolved issues pertaining to technical challenges as well as security and sustainability concerns in ATI-IoT enabling physical layer security are outlined. Full article

Background: Maize is easily contaminated by Aspergillus flavus, and the aflatoxin produced by A. flavus has been classified as a Group 1 carcinogen, for which there are currently no effective control measures. Biological control is regarded as an environmentally friendly and safe approach. Strains ZH179, ZH409, and ZH99 are three bacteria isolated from our laboratory that exhibit antagonistic effects against A. flavus. We conducted experiments to investigate their biocontrol efficacy. Results: The experimental results demonstrated that these three strains effectively inhibited A. flavus on plates and stored maize seeds. Identification revealed that ZH179 is Bacillus velezensis, while ZH409 and ZH99 are B. amyloliquefaciens. We also identified lipopeptide synthetase-related genes, including srfAA, srfAD, fenA, fenB, ituA, ituB, ituD, bmyA, bmyB, and bmyC, in these three strains. Furthermore, LC-MS analysis confirmed that these strains could produce lipopeptide compounds such as surfactin, fengycin, iturin, and bacillomycin. Using the Oxford cup method, we found that the lipopeptide compounds produced by these strains can inhibit the growth of A. flavus. Conclusion: These findings suggest that strains ZH179, ZH409, and ZH99 have good control effects on A. flavus during the storage of maize, primarily due to the lipopeptide compounds. This study provides a theoretical basis for using these three strains in the biological control of A. flavus. Full article

Potato common scab, caused by Streptomyces species, is a widespread soil-borne disease that poses a significant threat to potato cultivation globally. In this study, a Bacillus velezensis D7-8 strain was isolated from a potato. This endophytic bacterium exhibited broad-spectrum antifungal activity, and pot trials demonstrated that the D7-8 strain effectively controlled potato common scab with an efficacy of 42.07%. The complete genome sequence of the D7-8 strain was sequenced and subsequently identified as B. velezensis through multiple bioinformatic methods, primarily through structural variation analysis of whole-genome sequences. The machine learning method predicted that the expression profiles of colinear genes among closely related Bacillus species were highly consistent. Metabolite analysis of crude extracts using ultra-high-performance liquid chromatography coupled with quadrupole-Orbitrap high-resolution mass spectrometry (UPLC-Q-Exactive HRMS) revealed that D7-8 produces bioactive compounds, including surfactin and fengycin, both known for their antimicrobial properties. This study elucidates the antagonistic effect of B. velezensis D7-8 against Streptomyces acidiscabies and provides a valuable reference for future research on accurate microbial identification. Full article

Bacteria and endogenous enzymes generate volatile organic compounds (VOCs), which are posited to be the primary source of undesirable flavors in spoilt pork. Headspace solid-phase microextraction–gas chromatography–mass spectrometry (HS-SPME-GC-MS) was employed to assess the fluctuations in VOC concentrations in pork stored under tray packaging at 6–8 °C for 10 days, while total volatile basic nitrogen (TVB-N) and total viable counts (TVCs) were used to determine the quality of the pork. During storage, TVCs steadily increased, reflecting the growth of spoilage-related microorganisms, while TVB-N levels surpassed the spoilage threshold early, indicating an acceleration of the degradation process. Nine VOCs associated with pork spoilage were found by partial least squares discriminant analysis (PLS-DA), fold change (FC), and t-tests. The substances comprised ethyl acetate, acetoin, 3-methyl-1-butanol, 3-methylbutanal, 1-octen-3-ol, hexanal, vinyl acetate, 2-methylaziridine, and heptanal. A univariate linear regression analysis revealed a strong positive correlation (p < 0.001) between the gaseous total volatile basic nitrogen (G-TVBN) and the storage duration. Given that G-TVBN accurately reflects changes in pork freshness and the progression of spoilage, these results highlight the potential for dynamically monitoring the freshness and spoilage processes of pork. Full article

The quarantine pest, Cylas formicarius, is a key pest of sweet potatoes during both production and storage, posing a major threat to food security in various countries. To investigate behavioral mechanisms, the ultrastructure of the heads of larval and adult stages was analyzed using scanning electron microscopy, with an emphasis on the sensilla of the mouthparts and antennae. The results reveal degeneration of the antennae and ocelli in larvae. The larval mouthparts are equipped with three types and six subtypes of sensilla. Both male and female adults have four types and six subtypes of sensilla on their mouthparts. Compared to larvae, the adult mouthparts display a greater diversity of sensilla types and higher numbers of sensilla basicaonica (SB), sensilla chaetica (SC), and sensilla digitiformia (SD). Adult antennae consist of a scape, a pedicel, and eight flagellomeres (F1–F8), with F8 showing sexual dimorphism. Seven types of sensilla, excluding SB and sensilla ligulate (SL), each with two subtypes, were identified on the antennae of adults of both sexes. SC, sensilla furcatea, Böhm bristles, and SL were newly observed in the antennae of C. formicarius adults. Additionally, one type and seven subtypes of sensilla on the adult antennae exhibit distinct sexual dimorphism in terms of structure or number. The relationship between the head structure and adaptability of C. formicarius was examined, and the functions of each sensilla were discussed, providing a theoretical basis for future studies on the behavior of this pest. Full article

Flexible perovskite solar cells (F-PSCs) have the advantages of high power-per-weight, solution processability, and bending durability and have emerged as a competitive photovoltaic technology for various applications. As the core electron transport layer (ETL) in n-i-p-type device configurations, the solution-processed SnO₂ generally suffers from serious defect stacking on films, compromising the charge transport properties and the performance of resulting devices. Herein, we proposed a media-filling strategy to optimize the contact quality at the buried interface by introducing Al₂O₃ nanoparticles on the SnO₂ surface. Rather than forming a compact insulating layer, the Al₂O₃ can fill the grain boundaries of SnO₂ and smooth the substrate surface. Optimized interfacial contact under careful concentration control can rationally minimize the contact area of the perovskite with the surface imperfections of SnO₂ to mitigate trap-assisted charge recombination. Furthermore, the reduced surface roughness of SnO₂ facilitates the uniform deposition and oriented growth of upper perovskite film. As a result, the target F-PSCs achieved an impressive efficiency of 23.83% and retained 80% of the initial performance after 5000 bending cycles at a radius of four mm. Full article

Perovskite solar cells (PSCs) can utilize the residual photons from indoor light and continuously supplement the energy supply for low-power electron devices, thereby showing the great potential for sustainable energy ecosystems. However, the solution-processed perovskites suffer from serious defect stacking within crystal lattices, compromising the low-light efficiency and operational stability. In this study, we designed a multifunctional organometallic salt named sodium sulfanilate (4-ABS), containing both electron-donating amine and sulfonic acid groups to effectively passivate the positively-charged defects, like under-coordinated Pb ions and iodine vacancies. The strong chemical coordination of 4-ABS with the octahedra framework can further regulate the crystallization kinetics of perovskite, facilitating the enlarged crystal sizes with mitigated grain boundaries within films. The synergistic optimization effects on trap suppression and crystallization modulation upon 4-ABS addition can reduce energy loss and mitigate ionic migration under low-light conditions. As a result, the optimized device demonstrated an improved power conversion efficiency from 22.48% to 24.34% and achieved an impressive efficiency of 41.11% under 1000 lux weak light conditions. This research provides an effective defect modulation strategy for synergistically boosting the device efficiency under standard and weak light irradiations. Full article

In light of global climate change, China has set strategic goals for carbon peaking by 2030 and carbon neutrality by 2060, emphasizing the necessity of constructing a new power system with a high proportion of renewable energy sources. As coal-fired power plants are the main carbon emissions source in the power system, their low-carbon transition and morphology structure optimization is crucial. This paper explores the critical role of dynamic carbon emission factors within source–network–storage power system planning and proposes an innovative inverse dynamic carbon emission factor that effectively captures the nonlinear relationship between load rates and emissions. Comparative analyses using the HRP-38 test case demonstrate that the inverse model enhances computational efficiency, reduces solution times, and more accurately reflects the emissions characteristics of coal-fired units across varying operational conditions. Furthermore, the inverse model offers improved economic performance and broader flexibility in unit selection, highlighting its potential to balance carbon emissions control and economic optimization in future power system planning. Full article

Background and aim: The prevalence and adverse outcomes of metabolic dysfunction associated with steatotic liver disease (MAFLD) are increasing. The changes in the gut microbiota and metabolites associated with metabolic dysfunction-associated steatohepatitis (MASH) are regarded as an essential part of the progression of MAFLD. This study aimed to identify the gut microbiota and metabolites involved in the development of MAFLD in patients. Method: This study enrolled 90 patients (healthy controls, HC: n = 30; MASH: n = 30; MASH-related cirrhosis, MC: n = 30), and their fecal samples were collected for 16S rRNA sequencing and non-targeted LC–MS/MS metabolomics analysis. Data preprocessing and statistical analyses were performed using QIIME2 software, Pynast, QIIME2 package, Progenesis QI, and R program. Results: The abundance of Prevotellaceae at the family level and Prevotella at the genus level was lower in the MASH and NC samples than in the HC samples. Both Prevotellaceae and Prevotella showed the strongest correlation with MASH progression via random forest analysis. Untargeted metabolomics was used to quantitatively screen for discrepant metabolites in the stool samples from the three groups. Linolenic acid (LA)-related metabolite levels were significantly lower in MASH and NC samples. Associations between Prevotella- or LA-related metabolites and liver function were discovered. A high abundance of Prevotella was associated with LA-related metabolites and MASH. Conclusion: This study identified that gut microbiota and metabolites are associated with MASH-related metabolic dysfunction. LA and Prevotella are depleted during MASH progression, and additional supplementation with Prevotella may be a potential strategy for the future treatment of MAFLD. Full article

Banana crop ranks among the most crucial fruit and food crops in tropical and subtropical areas. Despite advancements in production technology, diseases such as cordana leaf spot, caused by Neocordana musae, remain a significant challenge, reducing productivity and quality. Traditional chemical controls are becoming less effective due to the development of resistance in target pathogens, which pose significant environmental and health concerns. Consequently, there is growing attention toward the development of biocontrol strategies. Here, we identified a new bacterial strain, Bacillus stercoris 92p, from the rhizosphere soil of banana. We evaluated its ability to suppress the growth of N. musae and other fungal pathogens that cause leaf spot disease in bananas. The inhibitory effect of B. stercoris 92p were checked using dual culture assays, microscopic observations, and pot experiments. Furthermore, the biocontrol mechanisms were investigated using whole-genome sequencing and biochemical analyses. The results showed that B. stercoris 92p exhibited significant antifungal activity against N. musae and other fungal pathogens, with inhibition rates exceeding 70%. Microscopic examination revealed significant morphological alterations in the hyphae and conidia of the tested pathogens. In pot experiments, B. stercoris 92p effectively reduced the severity of cordana leaf spot, achieving a biocontrol efficacy of 61.55%. Genomic analysis and biochemical tests indicated that B. stercoris 92p produces various antifungal compounds, including lipopeptides (fengycins and surfactins), hydrolytic enzymes (proteases and amylases), and phosphate-solubilizing metabolites. In conclusion, the study highlights that B. stercoris could potentially be used as a potential biological control agent against cordana leaf spot. Full article