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This paper presented a review on the capabilities of machine learning algorithms toward Earth observation data modelling and information extraction. The main purpose was to identify new trends in the application of or research on machine learning and Earth observation—as well as to help researchers positioning new development in these domains, considering the latest peer-reviewed articles. A review of Earth observation concepts was presented, as well as current approaches and available data, followed by different machine learning applications and algorithms. Special attention was given to the contribution, potential and capabilities of Earth observation-machine learning approaches. The findings suggested that the combination of Earth observation and machine learning was successfully applied in several different fields across the world. Additionally, it was observed that all machine learning categories could be used to analyse Earth observation data or to improve acquisition processes and that RF, SVM, K-Means, NN (CNN and GAN) and A2C were among the most-used techniques. In conclusion, the combination of these technologies could prove to be crucial in a wide range of fields (e.g., agriculture, climate and biology) and should be further explored for each specific domain.

The application of a catalytic membrane in the oxidative desulfurization of a multicomponent model diesel formed by most refractory sulfur compounds present in fuel is reported here for the first time. The catalytic membrane was prepared by the impregnation of the active lamellar [Gd(H4nmp)(H2O)2]Cl·2H2O (UAV-59) coordination polymer (CP) into a polymethyl methacrylate (PMMA, acrylic glass) supporting membrane. The use of the catalytic membrane in the liquid–liquid system instead of a powder catalyst arises as an enormous advantage associated with the facility of catalyst handling while avoiding catalyst mass loss. The optimization of various parameters allowed to achieve a near complete desulfurization after 3 h under sustainable conditions, i.e., using an aqueous H2O2 as oxidant and an ionic liquid as extraction solvent ([BMIM]PF6, 1:0.5 ratio diesel:[BMIM]PF6). The performance of the catalytic membrane and of the powdered UAV-59 catalyst was comparable, with the advantage that the former could be recycled successfully for a higher number of desulfurization cycles without the need of washing and drying procedures between reaction cycles, turning the catalytic membrane process more cost-efficient and suitable for future industrial application.

The bacterial communities in rhizosphere soil interact with the roots of plants. This interaction is beneficial for both the bacteria and the plants, which makes it very important to identify the structure of these bacterial communities for plant growth and development. However, the composition characteristics of bacterial communities in rhizosphere soil of 2-year and 5-year Haloxylon ammodendron have not been clearly defined. The purpose of this study was to identify the diverse composition of 2-year and 5-year Haloxylon ammodendron in Turpan, Xinjiang. Thus, rhizosphere soil bacteria were analyzed by isolating, purifying, and identifying the species through high-throughput sequencing technology. The bacterial strains in the rhizosphere soil of Haloxylon ammodendron were isolated with the dilution coating method, resulting in 37 isolated strains. The selective media were used to screen the growth-promoting characteristics of the rhizosphere soil isolates of Haloxylon ammodendron. The results of high-throughput amplification sequencing showed that the rhizosphere bacteria in the 2-year rhizosphere soil belonged to 45 phyla, 109 classes, 288 orders, 451 families, 826 genera, and 404 species, and those in the 5-year rhizosphere soil belonged to 56 phyla, 148 classes, 369 orders, 601 families, 1062 genera, and 671 species. Among them, Firmicutes, Proteobacteria, Actinobacteriota, Bacteroidota, Crenarchaeota, and so on are the dominant bacteria. There were 12206 and 14,053 OTUs in the 2-year-old and 5-year-old rhizosphere soil bacteria, respectively, and 3329 OTUs in the 2-year- and 5-year-old rhizosphere soil, accounting for 16.98% of the total number of OTUs. The results showed that three strains, sg16, sg21, and ss4, had the highest inorganic phosphorus solubility index (1.58). The isolated strain did not have the ability to dissolve organophosphorus and potassium, while the screened strain sg16 had the ability to fix nitrogen. Two strains with a good iron-bearing capacity, Sg9F and Sg1, were screened, among which Sg9F had the highest D/d value and Sg9F had the strongest iron-bearing capacity. The results showed that 37 strains of rhizosphere soil bacteria belonged to six genera. They are Bacillus, Corynebacterium, Phyllobacterium, Lysinibacillus, Sinorhizobium meliloti, and Streptomyces levis. Among them are sg21 (Bacillus sp.), sg1 (Bacillus sp.), sg9F (Streptomyces levis), sg16 (Phyllobacterium phragmitis), and ss4 (Sinorhizobium meliloti). This study provides a particular research basis for the influence of Haloxylon ammodendron rhizosphere bacteria on soil nutrient release and depicts a solution for improving the yield and quality of cistanche deserticola indirectly through isolating, screening, and identifying rhizosphere soil bacteria, including screening strains with growth-promoting functions and analyzing the population structure of rhizosphere bacteria in 2- and 5-year soil in combination with high-throughput sequencing technology.

With an ageing global population, healthcare systems confront challenges unique to the elderly. Current care models primarily manage health–illness shifts but frequently miss developmental transitions, particularly for older adults. Meleis’s transition theory offers an underutilized framework to rejuvenate our gerontogeriatric nursing approach. This article aims to articulate and advocate the value of Meleis’s transition theory as a framework for gerontogeriatric nursing, focusing on developmental transitions, thereby seeking a transformative change in the quality of elderly care. The article delves into Meleis’s transition theory’s vital components—transition types, conditions, and nursing therapeutics. It explores how these can be a multifaceted guide for gauging and overseeing ageing’s developmental shifts; adopting this theoretical perspective deepens our comprehension and bears tangible implications. Nurses versed in this theory could appreciate the benefits of a nuanced approach to the elderly, distinguishing it from the conventional biomedical stance. As the demands of an ageing populace grow, the integration of Meleis’s transition theory into nursing practices is not merely beneficial but imperative, setting a new standard for comprehensive and specialized elderly care.

LiDAR and cameras, often regarded as the “eyes” of intelligent driving vehicles, are vulnerable to adverse weather conditions like haze, rain, and snow, compromising driving safety. In order to solve this problem and enhance the environmental sensing capability under severe weather conditions, this paper proposes a multimodal back-end fusion object detection method, Sec-CLOCs, which is specifically optimized for vehicle detection under heavy snow. This method achieves object detection by integrating an improved YOLOv8s 2D detector with a SECOND 3D detector. First, the quality of image data is enhanced through the Two-stage Knowledge Learning and Multi-contrastive Regularization (TKLMR) image processing algorithm. Additionally, the DyHead detection head and Wise-IOU loss function are introduced to optimize YOLOv8s and improve 2D detection performance.The LIDROR algorithm preprocesses point cloud data for the SECOND detector, yielding 3D object detection results. The CLOCs back-end fusion algorithm is then employed to merge the 2D and 3D detection outcomes, thereby enhancing overall object detection capabilities. The experimental results show that the Sec-CLOCs algorithm achieves a vehicle detection accuracy of 82.34% in moderate mode (30–100 m) and 81.76% in hard mode (more than 100 m) under heavy snowfall, which demonstrates the algorithm’s high detection performance and robustness.

The purpose of the current research was to evaluate the influence of lactic acid bacteria and cellulase supplementation on the chemical composition, fermentation parameters, aerobic stability, microbial count, and in vitro nutrients digestibility of silage prepared with Pennisetum giganteum and rice straw. This study consisted of four treatments: a control group with no additive supplementation (CON), a lactic acid bacteria supplementation group (LAB), a cellulase supplementation group (CEL), and a combined supplementation group (LAC). After ensiling for 60 d, the chemical composition, fermentation parameters, microbial count, and aerobic stability were determined. Additionally, ruminal fermentation characteristics were evaluated by an in vitro incubation technique. Compared with CON silage, the quality of LAB and CEL silages was enhanced to a certain degree. Combined supplementation with lactic acid bacteria and cellulase in mixed silage of Pennisetum giganteum and rice straw noticeably increased (p < 0.05) the dry matter, crude protein, and lactic acid contents, whereas it reduced (p < 0.05) the pH and ammonia nitrogen/total nitrogen as well as the neutral detergent fiber and acid detergent fiber concentrations. The lactic acid bacteria count in LAC silage was higher (p < 0.05) than that of CON silage, whereas an opposite trend of yeast, aerobic bacteria, and mold was observed between the two groups. The aerobic stability time, in vitro crude protein, and neutral detergent fiber digestibility in LAC silage were significantly increased (p < 0.05) compared with those in CON silage. Moreover, the in vitro ruminal ammonia nitrogen content was reduced (p < 0.05), and the microbial protein and propionic acid concentrations were increased (p < 0.05) in silage after combined inoculation with additives. Taken together, the quality of Pennisetum giganteum and rice straw mixed silage can be improved by inoculation with lactic acid bacteria and cellulase, and combined supplementation shows the greatest improvement in silage quality.

Excessive application of phosphorus (P) fertilizers does not alleviate P deficiency in soils and may cause water eutrophication. The available P in acidic soils is bound to minerals, such as iron and aluminum, in forms that are difficult to utilize by plants. The low availability of P is detrimental to soil health and crop growth. To address the P imbalance in the soil, different bioremediation techniques, such as phosphate-solubilizing bacteria (PSB) application, have been employed. However, the systematic analysis of the effects of composite inoculation of PSB on crops remains elusive. In this study, the effects of composite-inoculated PSB on plant growth were systematically evaluated by two scales: plate experiment and soil test. This study employed six different strains of PSB including Lelliottia amnigena 1-1 (A), Kluyvera intermedia 1-2 (B), Pseudomonas tolaasii 1-6 (C), Burkholderia cepacia 2-5 (D), Pseudomonas frederiksbergensis 2-11 (E), and Pseudomonas rhodesiae 2-47 (F). Among the 57 different combinations of these strains, four combinations (AE, AF, ADF, and AEF) indicated higher phosphate-solubilizing abilities than the single strains. These combinations were used for subsequent experiments. The plate experiment revealed that composite strains were more effective than single strains in promoting the growth and development of seedlings and roots of oilseed rape. Furthermore, AE, AF, and AEF combinations indicated excellent growth-promoting effects. Moreover, the soil test revealed that the composite inoculation of AE and AEF significantly enhanced biomass accumulation and root development in oilseed rape. The increased growth-promoting effects of the composite strains were observed to be associated with to their phosphate-solubilizing capacities. Both scales confirmed that compared to single inoculation, composite inoculation of PSB is more beneficial for plant growth. This study provides composite inoculation materials and foundational data to support the bioremediation of P imbalance in soil.

This article takes representative uncultivated riverfront internet-famous sites (uncultivated RIFSs) in Changsha city, China, as an example to explore the internal mechanism of their formation and finds that they are closely related to the “urban subculture” and the “informality of urban public space”. In terms of methodology, through questionnaire surveys and in-depth interviews, this study investigates the behavioral characteristics of onsite visitors, the overall perceptions and satisfaction of public spaces, and the perceptions of spatial and humanistic elements of visitors. The main findings are as follows: ① Onsite visitors are mainly male, with local tourists and nearby residents accounting for over 80%. Furthermore, over half of the visitors have limited understanding of the uncultivated RIFSs. ② People’s overall attitudes towards the uncultivated RIFSs are positive. And the ability to carry out meaningful activities and find comfort and safety are of the greatest concern to onsite tourists. ③ Among the visiting reasons, leisure stays accounted for the highest proportion, followed by sightseeing, sports stays and social stays. ④ The onsite visitors’ main focus of spatial elements and humanistic elements is different according to the different sites. However, visitors’ dissatisfaction is mainly reflected in poor site safety and sanitation conditions, inadequate facilities and poor surrounding environments. This paper also compares the online–offline differences in the spatial perceptions of the uncultivated RIFSs between this study and previous research; instead of focusing on the urban physical spaces, online social media users pay more attention to their self-presentation. Meanwhile, the visitors place greater emphasis on the functionality, practicality and experiential activities of the urban physical spaces. Finally, this article proposes optimization strategies for uncultivated RIFSs from planning and governance and public space design aspects to protect and strengthen the composite utilization of space, therefore enhancing diverse vitality.

Exopolysaccharides (EPSs) produced by microorganisms play an important role in biotolerance and reducing heavy metal (HM) contamination by limiting the migration of HMs into plants. However, research on the application of EPS-producing marine bacteria for soil heavy metal remediation remains limited, particularly regarding their mechanisms of HM immobilization in soil and impact on plant growth. In this study, the EPS-producing marine bacterium Micrococcus antarcticus HZ was investigated for its ability to immobilize Pb and produce EPSs in soil filtrate. The effects on the growth quality and biomass of pakchoi (Brassica chinensis L.), as well as bacterial communities in inter-root soil contaminated with Pb, were also investigated. The results indicated that HZ could reduce the Pb concentration in the soil filtrate, achieving a removal rate of 43.25–63.5%. The EPS content and pH levels increased in the presence of Pb. Pot experiments showed that adding HZ significantly increased the biomass of pakchoi (9.45–14.69%), vitamin C (Vc) (9.69–12.92%), and soluble protein content (22.58–49.7%). HZ reduced the Pb content in the roots (17.52–47.48%) and leaves (edible tissues) (43.82–52.83%) of pakchoi. HZ increased soil enzyme activities (alkaline phosphatase, dehydrogenase, and urease), and the contents of ammonium nitrogen and nitrate nitrogen. Additionally, HZ also increased the relative abundance of beneficial bacteria (e.g., Proteobacteria, Cyanobacteria, and Chlorobacteria) in the inter-root soil, which have prophylactic and heavy-metal fixation functions. In summary, HZ reduces effective Pb content in edible tissues, roots, and inter-root soil by regulating inter-root soil microbial community structure, increasing soil pH, nitrogen content, and soil enzyme activity, and altering dominant phylum abundance.

This study examines the scientific production focused on the Maximum Principle between 1962 and 2021. Results indicate a consistent increase in the absolute number of publications over time. In relative terms, there is a resurgence of interest in this research field after the period between 2004 and 2009. Overall, these findings support the idea of strategic complementarity between the Maximum Principle and optimal control. However, there is a notable exception during the period 2010–2015, characterised by a decline in scientific production focused on the Maximum Principle and a simultaneous increase in focus on optimal control. Academic journals that play a role in promoting this research field tend to have high impact factors and interesting cite scores. Using a modified Boston Consulting Group matrix, the results reveal the persistence of two researchers labelled as stars and three as cash cows. A multiple linear regression analysis confirms that reputation significantly influences the clustering trends. A critical discussion is provided to highlight the dichotomy between popularity and effective contributions in this research field.

Megalurothrips usitatus (Bagnall) feeds on the young tissues of plants, causing wilting and deformity of leaves as well as damage to flowers and fruits, thereby seriously affecting plant yield. Due to its small size and difficulty of control, the species is one of the most important pests in the legume family. To clarify the occurrence and damage pattern of M. usitatus on field crops, a study was conducted using eight different crops as experimental materials, and an age-stage, two-sex life table was constructed. The population density of M. usitatus was the highest on cowpeas (Vigna unguiculata L. Walp.), followed by green beans (Phaseolus vulgaris L.) and Vigna cylindrica (Vigna unguiculata subsp. cylindrica (L.) Verdc.) in terms of net reproductive rate and the intrinsic rate of increase. In terms of reproductive capacity, cowpeas and V. cylindrica were more suitable for M. usitatus growth and reproduction, followed by green beans. M. usitatus could develop into adults on courgettes (Cucurbita pepo L.), wax gourds (Benincasa hispida Thunb. Cogn.), Momordica charantia (Momordica charantia L.), and soybeans (Glycine max L. Merr.) but had difficulty reproducing on those plants. Cucumber (Cucumis sativus L.) was the least suitable for the survival of M. usitatus. Population parameter analysis showed that the cowpea was the most suitable host plant for M. usitatus, followed by green beans and V. cylindrica. M. usitatus had difficulty reproducing on courgette, wax gourd, M. charantia, and soybeans, and feeding on cucumbers inhibited M. usitatus development and reproduction.

Dominant species are crucial in regulating the structure and productivity of plant communities. Adaptation strategies to climate change vary among the dominant species of different life types. However, the responses of the ecological niches of dominant species to warming and precipitation in semi-arid grasslands and their impacts on community structure and function are unknown. This study involved conducting a long-term experimental simulation of warming and increased precipitation on grasslands in Inner Mongolia and studying population dynamics, ecological niches, and their responses to the structure and function of the community species of two dominant plants, L. chinensis (perennial rhizome grass) and S. krylovii (perennial clumped grass). The results show that the niche width of L. chinensis increased and S. krylovii decreased under warming and increased precipitation conditions. The overlap of L. chinensis and S. krylovii decreased under the same conditions. The niche widths of L. chinensis and S. krylovii were 1.22 for the control (C), 1.19 and 1.04 under warming (W) conditions, 1.27 and 0.97 under warming plus precipitation (WP) conditions, and 1.27 and 1.24 under the conditions of precipitation addition (P). The niche overlap of L. chinensis and S. krylovii were 0.72 in C, 0.69 in W, 0.68 in WP, and 0.82 in P. The biomass share and importance value of L. chinensis increased, and those of S. krylovii decreased in response to warming and precipitation. The effects of warming on species diversity and community stability are primarily influenced by the effects on the niche breadth of S. krylovii. Combined with our previous study, L. chinensis will offer more resources in communities in warmer and wetter steppe climates in the future. However, this is not conducive to community diversity.

The development and application of new materials is one of the main driving forces of technical development in the field of civil engineering [...]

In the present study, a green and readily effective route is presented, using for the first time, methanesulfonic acid (MSA) as a catalyst to produce alkyl levulinates (ALs) via the addition of alcohols to α-angelica lactone (α-AL). A smooth procedure was developed that resulted in the production of high-purity ALs, with complete conversions and high yields (99.1–99.8%), within 20 to 60 min of reaction in the presence of 0.5 mol% MSA. The reactions were carried out solvent-free, at room temperature, and in atmospheric air. Reaction conditions were optimized, and equimolar amounts of alcohol reagent were used. This work presents the main advantages of the use of a catalyst (MSA) that is low cost, easily biodegradable, and does not release toxic gases into the environment, but has an acidic strength comparable to that of other mineral acids. Therefore, this study proves the remarkable efficiency of MSA as a catalyst in the synthesis of ALs through an economically and environmentally favorable route.

Maintaining the confidentiality and integrity of the messages during a transmission is one of the most important aims of encrypted communication systems. Many achievements were made using biomolecules to improve the quality of the messages in communication. At the same time, it is still a challenge to construct cooperative communications based on the interactions between biomolecules to achieve the confidentiality and integrity of the transmitted messages. DNA-based encrypted communications have been developed, and in particular, DNA-origami-based message encryption can combine steganography and pattern encryption and exhibits extremely high confidentiality. Nevertheless, limited by biological characteristics, encrypted messages based on DNA require a strict storage environment in the process of transmission. The integrity of the message encoded in the DNA may be damaged when the DNA is in an unfriendly and hard environment. Therefore, it is particularly significant to improve the stability of DNA when it is exposed to a harsh environment during transmission. Here, we encoded the information into the DNA strands that were condensed for encryption to form a nanosphere covered with a shell of SiO2, which brings high-density messages and exhibits higher stability than separated DNA. The solid shell of SiO2 could prevent DNA from contacting the harsh environment, thereby protecting the DNA structure and maintaining the integrity of the information. At the same time, DNA nanospheres can achieve high throughput input and higher storage density per unit volume, which contribute to confusing the message strand (M-strand) with the interference strand in the stored information. Condensing DNA into the nanosphere that is used for DNA origami cryptography has the potential to be used in harsh conditions with higher confidentiality and integrity for the transmitted messages.

This study is focused on the modelling of the production of bio-oil by thermochemical liquefaction. Species Acacia melanoxylon was used as the source of biomass, the standard chemical 2-Ethylhexanol (2-EHEX) was used as solvent, p-Toluenesulfonic acid (pTSA) was used as the catalyst, and acetone was used for the washing process. This procedure consisted of a moderate acid-catalysed liquefaction process and was applied at 3 different temperatures to determine the proper model: 100, 135, and 170 °C, and at 30-, 115-, and 200-min periods with 0.5%, 5.25%, and 10% (m/m) catalyst concentrations of overall mass. Optimized results showed a bio-oil yield of 83.29% and an HHV of 34.31 MJ/kg. A central composite face-centred (CCF) design was applied to the liquefaction reaction optimization. Reaction time, reaction temperature, as well as catalyst concentration, were chosen as independent variables. The resulting model exhibited very good results, with a highly adjusted R-squared (1.000). The liquefied products and biochar samples were characterized by Fourier-transformed infrared (FTIR) and thermogravimetric analysis (TGA); scanning electron microscopy (SEM) was also performed. The results show that invasive species such as acacia may have very good potential to generate biofuels and utilize lignocellulosic biomass in different ways. Additionally, using acacia as feedstock for bio-oil liquefaction will allow the valorisation of woody biomass and prevent forest fires as well. Besides, this process may provide a chance to control the invasive species in the forests, reduce the effect of forest fires, and produce bio-oil as a renewable energy.

In this work, we intended to study the effect of heat treatments (T5 and flash T6) on blistering, mechanical properties and microstructure for different parts produced by vacuum-assisted HPDC. These parts were produced with primary and secondary aluminium alloys (AlSi10MnMg alloy and AlSi10Mg(Fe) alloy, respectively). The parts presented blisters for all combinations of temperature (between 360 °C and 520 °C) and stage times (15 and 30 min) of solution heat treatments. However, when subjected to the T5 heat treatment, blisters were no longer visible. With this heat treatment, there was an increase in yield strength of 64% for both aluminium alloys and an increase in UTS of 31% in AlSi10Mg(Fe) alloy and of 24% in AlSi10MnMg alloy, when compared to the mechanical properties in the as-cast state. However, there was a decrease in ductility. The AlSi10Mg(Fe) alloy presented a lot of contaminations (especially iron), which impaired the mechanical properties compared to the primary aluminium alloy, AlSi10MnMg.

Sulforaphene (4-methylsufinyl-3-butenyl isothiocyanate, SFE), produced by myrosinase hydrolysis of glucoraphenin (4-methylsulfinyl-3-butenyl glucosinolate) found in radish seeds, is strongly associated with cancer prevention. In this study, we investigated the stability of SFE (purity above 98%) under various thiol-containing compounds at 25 °C, such as sodium hydrosulfide (NaHS), glutathione (GSH), and cysteine (Cys). We observed that the degradation of SFE was closely related to the presence and dissociation capacity of thiol-containing compounds in the solution, particularly the thiol group. We found that the degradation rate of SFE was influenced by incubation with NaHS, GSH, and Cys, with distinct degradation products detected for each of these thiol-containing compounds. Compared to GSH, sulfide and Cys played important roles in promoting the degradation of SFE. Furthermore, we found substantial quantities of hydrogen sulfide in conjunction with SFE during the hydrolysis process of seeds, and a heat treatment of the seeds resulted in increased production of SFE. However, the introduction of sulfide-oxidizing bacteria to the hydrolytic system did not exhibit any inhibitory effect on the degradation of SFE. These results provided a guideline for industries to improve the stability of SFE during preparation.

Phthalic acid esters (PAEs) are a class of common environmental endocrine disruptors (EEDs), capable of causing considerable pollution to water, soil, and air and producing a range of adverse health impacts in humans. Although various studies have investigated the pollution characteristics and health hazards of PAEs in different media, a systematic review of PAEs in the broader environmental context is still lacking. In order to comprehensively explore current issues and suggest prospects, the current status, detection technology, toxicity, and health hazards of PAEs were investigated. The results suggest that PAE pollution is a widespread and complex global phenomenon, transported over long distances. The traditional techniques used for determination include high-performance liquid chromatography–mass spectrometry (HPLC-MS), gas chromatography–mass spectrometry (GC-MS), and high-performance liquid chromatography (HPLC). Various detection techniques offer distinct advantages and disadvantages. Moreover, PAEs can cause differing extents of harm to the nervous and reproductive systems of mammals. In the future, it is imperative to improve the detection of PAEs, establish rapid identification approaches, refine toxicological research methods, and investigate more comprehensive health risk assessment methods. These efforts will provide scientific support for the prevention and management of the resulting contaminants.

Aim: To compare the levels of serum inflammatory indicators in psoriasis vulgaris patients who progress to PsA and those not, as well as to establish and validate a simple score scale for predicting PsA for psoriasis vulgaris patients. Methods: A cross-sectional study was performed at a university hospital in China to recruit five hundred and seventy-seven patients who had been diagnosed with psoriasis vulgaris for at least 10 years. After evaluation, 86 were enrolled in the PsA group, and the others were selected as the control group. Eight serum inflammatory factors were detected and compared between the two groups. A simple score scale for PsA prediction was established and validated. Results: Serum CRP, IL-6, and TNF-α levels were significantly higher in the PsA group than in the control group. A simple score scale composed of CRP, IL-6, and TNF-α was established. The sensitivity was 59.30% and the specificity was 83.50% for predicting PsA among all psoriasis vulgaris patients when the cut-off value of the total score was set as 1.8 points. The simple score scale presented a predictive value for progressing to PsA among all psoriasis vulgaris patients internally (AUC = 0.788), and the performance was also conformed in psoriasis vulgaris patients receiving topical treatment (AUC = 0.746), systemic treatment (AUC = 0.747) and biological treatment (AUC = 0.808), respectively. The predictive performance of this scale was also validated by an external retrospective cohort (AUC = 0.686). Conclusions: CRP, IL-6, and TNF-α were potential indicators to recognize PsA risk in patients with psoriasis vulgaris. A simple score scale may provide new insights for early prediction of PsA among psoriasis vulgaris patients.

To investigate the mechanical properties and a compressive constitutive model of recycled concrete under sulfate attack considering the effects of multiple factors, two waste concrete strengths (i.e., C30 and C40), four replacement ratios of recycled coarse aggregates (i.e., 0, 30%, 50% and 100%), and two water–cement ratios (i.e., 0.50 and 0.60) were considered in this study, and a total of 32 recycled concrete specimens were designed and tested. The results indicated that the failure processes and patterns of recycled concrete were not significantly influenced by the replacement ratio of recycled coarse aggregates, the waste concrete strength, the water–cement ratio, or sulfate attack. The higher the replacement ratio of recycled coarse aggregates and the water–cement ratio and the lower the waste concrete strength, the more obvious the reduction in cubic compressive strength, with a maximum reduction of 38.48%. A prediction model for the cubic compressive strength of recycled concrete under sulfate attack was proposed. The higher the replacement ratio of recycled coarse aggregates and the water–cement ratio and the lower the waste concrete strength, the more significant the reduction in axial compressive strength, with a maximum reduction of 37.82%. A prediction model for the axial compressive strength of recycled concrete under sulfate attack was established. A compressive constitutive model of recycled concrete under sulfate attack considering the effects of the replacement ratio of recycled coarse aggregates, the waste concrete strength, and the water–cement ratio was established. The pore structure of recycled concrete was significantly destroyed by the expansion stress generated by Na2SO4 crystals: a large number of Na2SO4 crystals were attached to the surface of concrete matrix, and the concrete matrix became loose. The research results can provide a theoretical basis and data support for engineering applications of recycled concrete.

Achieving formation tracking control of underactuated autonomous underwater vehicles (AUVs) under communication delays presents a significant challenge. To address this challenge, a distributed prescribed performance control protocol based on a real-time state information online predictor (RSIOP) is proposed in this paper. First, we innovatively designed an RSIOP to achieve active compensation for the delayed state information of neighboring AUVs. Next, considering formation performance and safety, a low-complexity and practical nonlinear mapping function was used to implement prescribed performance tracking control for the AUV formation. Additionally, the adverse effects of external disturbance uncertainties and input saturation are also considered. Finally, the simulation tests demonstrated that the proposed formation control protocol can successfully achieve the predetermined formation tracking tasks in the presence of time-varying communication delays and external disturbances, while also enabling real-time changes in formation configuration during the process. Throughout, the protocol maintains input saturation limits, and the actual control inputs remain smooth, with no significant oscillations. Furthermore, comparative simulation tests verified the necessity of the RSIOP developed in this study and quantitatively demonstrated that the proposed control method exhibits superior performance in terms of formation control accuracy, error convergence speed, and transient-state constraints.

Irreversible fibrosis following myocardial infarction (MI) stiffens the infarcted myocardium, which remains challenging to restore. This study aimed to investigate whether the injectable RLP12 hydrogel, derived from recombinant resilin protein, could serve as a vehicle for stem cells to enhance the function of the infarcted myocardium. The RLP12 hydrogel was prepared and injected into the myocardium of rats with MI, and brown adipose-derived mesenchymal stem cells (BADSCs) were loaded. The survival and differentiation of BADSCs in vivo were investigated using immunofluorescence one week and four weeks after treatment, respectively. The heart function, MI area, collagen deposition, and microvessel density were further assessed four weeks after treatment through echocardiography, histology, immunohistochemistry, and immunofluorescence. The RLP12 hydrogel was prepared with a shear modulus of 10–15 kPa. Four weeks after transplantation, the RLP12 hydrogel significantly improved cardiac function by increasing microvessel density and reducing infarct area size and collagen deposition in MI rats. Furthermore, the distribution ratio of collagen III to I increased in both the centre and edge areas of the MI, indicating the improved compliance of the infarct heart. Moreover, the RLP12 hydrogel also promoted the survival and differentiation of BADSCs into cardiac troponin T- and α-smooth muscle-positive cells. The RLP12 hydrogel can be utilised as an injectable vehicle of BADSCs for treating MI and regulating collagen I and III expression profiles to improve the mechanical microenvironment of the infarct site, thereby restoring heart function. The study provides novel insights into the mechanical interactions between the hydrogel and the infarct microenvironment.

Ubiquitination modifications permit the degradation of labelled target proteins with the assistance of proteasomes and lysosomes, which is the main protein degradation pathway in eukaryotic cells. Polyubiquitination modifications of proteins can also affect their functions. De-ubiquitinating enzymes reverse the process of ubiquitination via cleavage of the ubiquitin molecule, which is known as a de-ubiquitination. It was demonstrated that ubiquitination and de-ubiquitination play key regulatory roles in fatty acid transport, de novo synthesis, and desaturation in dairy mammary epithelial cells. In addition, natural plant extracts, such as stigmasterol, promote milk fat synthesis in epithelial cells via the ubiquitination pathway. This paper reviews the current research on ubiquitination and de-ubiquitination in dairy milk fat production, with a view to providing a reference for subsequent research on milk fat and exploring new directions for the improvement of milk quality.

An accurate description of short-range interactions among atoms is crucial for simulating irradiation effects in applications related to ion modification techniques. A smooth integration of the Ziegler–Biersack–Littmark (ZBL) potential with the adaptive intermolecular reactive empirical bond-order (AIREBO) potential was achieved to accurately describe the short-range interactions for carbon-based materials. The influence of the ZBL connection on potential energy, force, and various AIREBO components, including reactive empirical bond-order (REBO), Lennard–Jones (LJ), and the torsional component, was examined with configurations of the dimer structure, tetrahedron structure, and monolayer graphene. The REBO component is primarily responsible for the repulsive force, while the LJ component is mainly active in long-range interactions. It is shown that under certain conditions, the torsional energy can lead to a strong repulsive force at short range. Molecular dynamics simulations were performed to study the collision process in configurations of the C-C dimer and bulk graphite. Cascade collisions in graphite with kinetic energies of 1 keV and 10 keV for primary knock-on atoms showed that the short-range description can greatly impact the number of generated defects and their morphology.

Due to the increasing prevalence of articular cartilage diseases and limitations faced by current therapeutic methodologies, there is an unmet need for new materials to replace damaged cartilage. In this work, poly(vinyl alcohol) (PVA) hydrogels were reinforced with different amounts of Nomex® (known for its high mechanical toughness, flexibility, and resilience) and sterilized by gamma irradiation. Samples were studied concerning morphology, chemical structure, thermal behavior, water content, wettability, mechanical properties, and rheological and tribological behavior. Overall, it was found that the incorporation of aramid nanostructures improved the hydrogel’s mechanical performance, likely due to the reinforcement’s intrinsic strength and hydrogen bonding to PVA chains. Additionally, the sterilization of the materials also led to superior mechanical properties, possibly related to the increased crosslinking density through the hydrogen bonding caused by the irradiation. The water content, wettability, and tribological performance of PVA hydrogels were not compromised by either the reinforcement or the sterilization process. The best-performing composite, containing 1.5% wt. of Nomex®, did not induce cytotoxicity in human chondrocytes. Plugs of this hydrogel were inserted in porcine femoral heads and tested in an anatomical hip simulator. No significant changes were observed in the hydrogel or cartilage, demonstrating the material’s potential to be used in cartilage replacement.

African swine fever virus (ASFV), a highly virulent double-stranded DNA virus, poses a significant threat to global pig farming, with mortality rates in domestic pigs reaching up to 100%. Originating in Kenya in 1921, ASFV has since proliferated to Western Europe, Latin America, Eastern Europe, and most recently China in 2018, resulting in substantial global agricultural losses. Antigenic epitopes, recognized by the immune system’s T cells and B cells, are pivotal in antiviral immune responses. The identification and characterization of these antigenic epitopes can offer invaluable insights into the immune response against ASFV and aid in the development of innovative immunotherapeutic strategies. Vaccine adjuvants, substances that amplify the body’s specific immune response to antigens, also play a crucial role. This review provides an overview of the progress in studying T/B-cell epitopes in ASFV proteins and ASFV vaccine adjuvants, highlighting their role in the immune response and potential use in new vaccine development.

This paper proposes a composite model that combines convolutional neural network models and mechanical analysis to determine the forces acting on an object. First, we establish a model using Newtonian mechanics to analyze the forces experienced by the human body during movement, particularly the forces on joints. The model calculates the mapping relationship between the object’s movement and the forces on the joints. Then, by analyzing a large number of fencing competition videos using a deep learning model, we extract video features to study the torques and forces on human joints. Our analysis of numerous images reveals that, in certain movement patterns, the peak pressure on the knee joint can be two to three times higher than in a normal state, while the driving knee can withstand peak torques of 400–600 Nm. This straightforward model can effectively capture the forces and torques on the human body during movement using a deep neural network. Furthermore, this model can also be applied to problems involving non-rigid body motion.

Accurately estimating rice yield is essential for ensuring global food security, enhancing agricultural productivity, and promoting agricultural economic growth. This study constructed a dataset of rice panicles at different growth stages and combined it with an attention mechanism and the YOLOv8 network to propose the YOLOv8s+LSKA+HorNet rice panicle detection and counting model, based on a drone remote sensing platform. Using the panicle count data collected by this model, along with the thousand-grain weight, number of grains per panicle, and actual yield data from a rice nitrogen gradient experimental field, various machine learning models were trained to ultimately propose a field-level rapid rice yield estimation model, RFYOLO. The experimental results show that the rice panicle detection and counting model can achieve an average precision (AP) of 98.0% and a detection speed of 20.3 milliseconds. The final yield estimation model achieved a prediction R2 value of 0.84. The detection and counting model significantly reduced missed and duplicate detections of rice panicles. Additionally, this study not only enhanced the model’s generalization ability and practicality through algorithmic innovation but also verified the impact of yield data range on the stability of the estimation model through the rice nitrogen gradient experiment. This is significant for early rice yield estimation and helping agricultural producers make more informed planting decisions.

The freeze–thaw effect has a significant impact on the strength deterioration of tunnel-lining concrete in cold regions. Therefore, the strength deterioration characteristics of concrete in a tunnel were studied, and silicone coating materials were used to improve its frost resistance and durability under freeze–thaw cycles. Freeze–thaw cycle tests were conducted on concrete specimens with different coatings. The freeze–thaw damage phenomenon, dynamic elastic modulus, and mass loss of the specimens were used to evaluate the freeze–thaw durability of concrete strengthened with coatings. The results demonstrated that silicone coatings effectively prevented moisture and corrosive substances from infiltrating the concrete, thereby enhancing its durability; the silicone–polyether hybrid had the most significant frost resistance at 500 g/m2 and silane type III at 300 g/m2, with freezing resistance times of 175 and 300, respectively. During the freeze–thaw process, the strength reduction rate of specimens was much greater than the mass loss rate of concrete. Taking into account the water environment surrounding the lining concrete and the site temperature, an equivalent indoor freeze–thaw cycle conversion model was established. The results can provide an experimental basis for selecting better frost-resistant materials for tunnel concrete in cold regions.

Background: Preterm birth and prolonged neonatal hospitalization are potential sources of stress for mothers of preterm and low birth weight infants. Aim: To evaluate maternal stress and its association with neurobehavioral indicators of preterm infants during hospitalization in the neonatal intensive care unit. Methods: A cross-sectional study was conducted in a neonatal intensive care unit of a hospital in Goiânia, Brazil. The study included preterm and low birth weight infants of both genders and their mothers. The Parental Stressor Scale: Neonatal Intensive Care Unit and the Neurobehavioral Assessment of the Preterm Infant were respectively applied to mothers and infants in the neonatal intensive care unit. Results: The study involved 165 premature infants and their mothers. The mean age of the mothers was 26.3 years and most had a high school education level (57.6%). Mothers perceived the experience of having an infant in the neonatal intensive care unit as moderately stressful (2.96 ± 0.81). The parental role alteration (4.11 ± 1.03) and sights and sounds (2.15 ± 0.90) subscales exhibited the highest and lowest stress levels, respectively. Significant correlations (rho < −0.3; p < 0.05) were found between maternal stress and neurobehavioral indicators of infants. In the multivariate analysis, low leg tone was a predictor of higher maternal stress. Low tone and limited arm movement were predictors of higher maternal stress in the maternal role item. Conclusions: The experience of having a preterm infant hospitalized was considered moderately stressful for mothers. Maternal stress levels were significantly correlated with low scores on neonatal neurobehavioral indicators.

The rapid growth of electronic devices, electric vehicles, and mobile energy storage has produced large quantities of spent batteries, leading to significant environmental issues and a shortage of lithium resources. Recycling spent batteries has become urgent to protect the environment. The key to treating spent lithium-ion batteries is to implement green and efficient regeneration. This study proposes a recycling method for the direct regeneration of spent lithium iron phosphate (LFP) batteries using hydrothermal reduction. Ascorbic acid (AA) was used as a low-cost and environmentally friendly reductant to reduce Fe3+ in spent LiFePO4. We also investigated the role of AA in the hydrothermal process and its effects on the electrochemical properties of the regenerated LiFePO4 cathode material (AA-SR-LFP). The results showed that the hydrothermal reduction direct regeneration method successfully produced AA-SR-LFP with good crystallinity and electrochemical properties. AA-SR-LFP exhibited excellent electrochemical properties, with an initial discharge specific capacity of 144.4 mAh g−1 at 1 C and a capacity retention rate of 98.6% after 100 cycles. In summary, the hydrothermal reduction direct regeneration method effectively repairs the defects in the chemical composition and crystal structure of spent LiFePO4. It can be regarded as a green and effective regeneration approach for spent LiFePO4 cathode materials.

The grain moisture content of maize inbred lines at maturity is one of the most important indicators for mechanical harvesting of kernels. In this study, 116 maize inbred lines from a wide range of sources were used as research materials and 30 traits of grain moisture content were analyzed using multivariate statistical analysis. The results showed that all 30 traits had some correlations. Principal component analysis downscaled the 30 traits into 10 principal component factors, reflecting 77.674% of the information in the original traits. Cluster analysis categorized the 116 inbred lines into 5 major groups containing 26, 29, 31, 16 and 14 inbred lines. Based on the D value of the overall evaluation, discriminant analysis reclassified the maize inbred lines by principal component scores and 98 maize inbred lines were correctly discriminated with a probability of 84.48%, which can be regarded as a relatively reliable clustering result. The stepwise regression method was further used to screen seven traits: GMC2, GDR1, HMC3, NH, GDR2, CD and EL and to establish a comprehensive evaluation model for the grain moisture content of maize inbred lines. Among 116 maize inbred lines, 14, represented by H21 and MS71, had the lowest grain moisture content at maturity.

To characterize the complex creep behavior of steel slag–asphalt mixture influenced by both stress and temperature, predictive models employing Back Propagation (BP) and Long Short-Term Memory (LSTM) neural networks are described and compared in this paper. Multiple stress repeated creep recovery tests on AC-13 grade steel slag–asphalt mix samples were conducted at different temperatures. The experimental results were processed into a group of independent creep recovery test results, then divided into training and testing datasets. The K-fold cross-validation was applied to the training datasets to fine-tune the hyperparameters of the neural networks effectively. Compared with the experimental curves, both the effects of BP and LSTM models were investigated, and the broad applicability of the models was proven. The performance of the trained LSTM model was observed by a 95% confidence interval around the fit errors, thereby the creep strain intervals for the testing dataset were obtained. The results suggest that the LSTM model had enhanced prediction compared the BP model for creep deformation trends of steel slag–asphalt mixture at various temperatures. Due to the potent generalization strength of artificial intelligence technology, the LSTM model can be further expanded for forecasting road rutting deformations.

The modern society produces large amounts of household waste with high organic matter content. The vermicomposting of household waste produces high-value humic substances and is a way to stabilize organic material for later use as raw material (3rd generation biomass) for bioenergy proposes. A 6-month matured compost, combining vegetable and fruit scraps from domestic trash and grass and shrub clippings from yard waste, was evaluated to assess its potential as a raw material in pyrolysis processes. The pyrolysis activation energy (Kissinger) of the composted material showed values in the range of 200–300 kJ/mol, thus confirming its suitability for pyrolysis processes with promising H2 yields. The treatment of the composted material with H2SO4 and NaOH solution (boiling; 1 mol/L) led to the production of solid residues that present higher pyrolysis activation energies, reaching 550 kJ/mol for the most resilient fraction, which makes them suitable to produce carbonaceous materials (biochar) that will have incorporated the inorganics existing in the original compost (ashes 37.6%). The high content of inorganics would play a chief role during pyrolysis since they act as gasification promoters.

The impact of microplastics (MPs) as emerging pollutants on plant heavy metal toxicity has been extensively reported in vegetable–soil systems over recent years. However, little attention has been given to cultivar variations between degradable and non-degradable MPs. This study investigated the effects of degradable polylactic acid (PLA) and nondegradable polypropylene (PP) MPs on plant growth and biomarker (malonaldehyde (MDA) and antioxidant enzymes) performance in Cd-contaminated arable soil. The results show that both types of MPs significantly impacted plant biomass and biomarker contents across all three Cd levels. The degree of impact was significantly sensitive to both the type and dose of MPs, as they reduced the soil pH and cation exchange capacity (CEC) while increasing soil dissolved organic carbon (DOC), microbial biomass carbon, and nitrogen. PP exhibited greater root growth inhibition and phytotoxicity at higher doses of 1% and 5% compared to PLA. Specifically, the highest MDA contents were 1.44 and 2.20 mmol mg−1 protein for shoots and roots, respectively, in the 5% PLA treatment under a 10.1 mg kg−1 Cd level, which were 1.22 and 1.18 times higher than those in corresponding treatments of 5% PP. Overall, PLA had less significant effects on plant phytotoxicity, Cd availability, and soil properties compared to PP. Regression pathway analysis indicated that MPs increased shoot Cd uptake by altering both soil physical–chemical and microbial characteristics. Among the soil variables, pH, CEC, and Cd bioavailability were found to play vital roles. Yet, no single variable acts alone in the mechanism for plant Cd uptake. PLAs are suggested to replace conventional non-biodegradable plastics to control environmental MP pollution, particularly in agricultural systems with higher Cd contamination. However, the long-term effects of the by-products generated during the biodegradation process require further investigation.

With the increase in uptake of multi-month antiretroviral therapy dispensing (MMD) for children, little is known about consistency of MMD receipt over time and its association with virological outcomes. This analysis aims to assess the uptake of 3-month MMD among children, consistent receipt of MMD after uptake, and clinical outcomes following transition to MMD in 16 health facilities in Gaza and Inhambane Provinces. This is a secondary analysis involving children

With the modernization of global navigation satellite systems (GNSS), especially the rapid development of the BeiDou Navigation Satellite System (BDS), more observations of satellites and signals have become available. Using data of the globally distributed MGEX stations, a systematic and comprehensive evaluation of signal characteristics for BDS-3, BDS-2, GPS, and Galileo is conducted in terms of carrier-to-noise ratio (C/N0), code noise, and multipath in the contribution. First, a comprehensive signal quality assessment method for BDS/Galileo/GPS satellites and signals is proposed, including C/N0 modeling and MP modeling. For BDS, the BDS-3 satellites apparently have higher signal power than the BDS-2 satellites at the same frequency such as B1I and B3I, and the signal B2a of BDS-3 is superior to other signals in regard to signal power, which is comparable with the superior Galileo E5 signals and GPS L5. Among all the signals, the observation accuracy of E5 is the highest regardless of receiver types, and next highest are BDS-3 B2a and GPS L5. Due to not being affected by the systematic code errors of BDS-2, the observations of BDS-3 satellites contain smaller multipath errors than that of BDS-2 satellites. As for the multipath suppression performance, the BDS-3 signal B2a, GPS L5, and Galileo E5 and E5b perform better than the other signals, which may be related to their wide signal bandwidths.

Although existing 3D object-detection methods have achieved promising results on conventional datasets, it is still challenging to detect objects in data collected under adverse weather conditions. Data distortion from LiDAR and cameras in such conditions leads to poor performance of traditional single-sensor detection methods. Multi-modal data-fusion methods struggle with data distortion and low alignment accuracy, making accurate target detection difficult. To address this, we propose a multi-modal object-detection algorithm, Snow-CLOCs, specifically for snowy conditions. In image detection, we improved the YOLOv5 algorithm by integrating the InceptionNeXt network to enhance feature extraction and using the Wise-IoU algorithm to reduce dependency on high-quality data. For LiDAR point-cloud detection, we built upon the SECOND algorithm and employed the DROR filter to remove noise, enhancing detection accuracy. We combined the detection results from the camera and LiDAR into a unified detection set, represented using a sparse tensor, and extracted features through a 2D convolutional neural network to achieve object detection and localization. Snow-CLOCs achieved a detection accuracy of 86.61% for vehicle detection in snowy conditions.

Maize productivity in the central belt plays a significant role in the food security of China. With good adaptability and disease resistance, landrace germplasm is important for maize improvement. A total of 246 landrace accessions were collected from the maize belts in central China and genotyped with the SLAF-seq (Specific-Locus Amplified Fragment Sequencing) method, and 144,650 SNPs were obtained for each accession. The results showed that the landrace accessions could be divided into three major groups. In the cluster results, Group I included 64 accessions, which mainly belonged to the landrace of White horse teeth; Group II had 71 accessions, which mainly belonged to the lantern red landraces; the rest of the 116 accessions were clustered as Group III, including a variety of types landraces and seven indicator inbred lines. In the results of structure and multidimensional scaling, the accessions’ attribution differed with the clusters, the main reason for which is the attribution change in intermediate germplasms. Linkage disequilibrium decay distance was 0.98 kb, which was much lower than that of temperate and tropical maize inbred lines, indicated the much higher genetic diversity of landrace germplasms. The results can help us select suitable landrace germplasms and speed up the process of inbred line development and maize improvement.

The nutritional value of goat milk is determined by the composition of its fatty acids, with particular importance placed on the role of unsaturated fatty acids in promoting human health. CircRNAs have been known to affect fatty acid metabolism through different pathways. In this study, high-throughput sequencing was employed to construct expression profiles of mammary tissue harvested during the dry period and peak lactation stages of dairy goats. Differentially expressed circRNAs and mRNAs were screened, revealing significantly higher expression levels of circRNA-08436 and ELOVL6 during the peak lactation period compared with the dry period. Thus, circRNA-08436 and ELOVL6 were chosen for subsequent studies. The findings demonstrated that circRNA-08436 not only promotes the synthesis of triglyceride (TAG) and cholesterol in goat mammary epithelial cells (GMECs), but also increases the concentrations of saturated fatty acids in the cells. Through the utilization of software prediction, the dual luciferase reporter system, and qRT-PCR, it was observed that circRNA-08436 binds to miR-195, with its overexpression reducing the expression levels of miR-195 and inhibiting TAG synthesis. In addition, circRNA-08436 upregulated the expression levels of the miR-195 target gene ELOVL6. The data also revealed that YTHDC1 facilitated the transport of circRNA-08436 from the nucleus to the cytoplasm, while YTHDC2 in the cytoplasm functioned as a “reader” to identify and degrade circRNA-08436. Taken together, these findings contribute to a better understanding of the molecular regulation of fatty acid metabolism in the mammary glands of dairy goats, thus offering a sound theoretical basis for the production of high-quality goat milk.

This research aimed to explore the diverse phenotypic characteristics of moso bamboo in China and pinpoint essential characteristics of moso bamboo. In this study, 63 grids were selected using the grid method to investigate 28 phenotypic traits of moso bamboo across the entire distribution area of China. The results suggest that the phenotypic traits of moso bamboo exhibit rich diversity, with coefficients of variation ranging from 5.87% to 36.57%. The phenotypic traits of moso bamboo showed varying degrees of correlation. A principal component analysis was used to identify seven main phenotypic trait indicators: diameter at breast height (DBH), leaf area (LA), leaf weight (LW), branch-to-leaf ratio (BLr), leaf moisture content (Lmc), wall-to-cavity ratio (WCr), and node length at breast height (LN), which accounted for 81.64% of the total information. A random forest model was used, which gave good results to validate the results. The average combined phenotypic trait value (D-value) of most germplasm was 0.563. The highest D-value was found in Wuyi 1 moso in Fujian (0.803), while the lowest D-value was observed in Pingle 2 moso in Guangxi (0.317). The clustering analysis of phenotypic traits classified China’s moso bamboo germplasm into four groups. Group I had the highest D-value and is an important candidate germplasm for excellent germplasm screening.

The rapid and accurate identification of rail surface defects is critical to the maintenance and operational safety of the rail. For the problems of large-scale differences in rail surface defects and many small-scale defects, this paper proposes a rail surface defect detection algorithm, RSDNet (Rail Surface Defect Detection Net), with YOLOv8n as the baseline model. Firstly, the CDConv (Cascade Dilated Convolution) module is designed to realize multi-scale convolution by cascading the cavity convolution with different cavity rates. The CDConv is embedded into the backbone network to gather earlier defect local characteristics and contextual data. Secondly, the feature fusion method of Head is optimized based on BiFPN (Bi-directional Feature Pyramids Network) to fuse more layers of feature information and improve the utilization of original information. Finally, the EMA (Efficient Multi-Scale Attention) attention module is introduced to enhance the network’s attention to defect information. The experiments are conducted on the RSDDs dataset, and the experimental results show that the RSDNet algorithm achieves a mAP of 95.4% for rail surface defect detection, which is 4.6% higher than the original YOLOv8n. This study provides an effective technical means for rail surface defect detection that has certain engineering applications.