Frequent and prolonged exposure to high levels of vibration and shock can cause neck and back pain and discomfort for many wheelchair users. Current methods to attenuate the vibration have shown to be ineffective and, in some cases, detrimental to health. Novel in-wheel suspension systems claim to offer a solution by replacing traditional spokes of the rear wheels with dampening elements or springs. The objective of this study was to investigate the effects of in-wheel suspension on reducing vibration and shock and improving comfort in manual wheelchair users. Twenty-four manual wheelchair users were propelled over nine different surfaces using a standard spoked wheel, a Spinergy CLX, and Loopwheels while accelerometry data was collected at the footrest, seat, and backrest. Loopwheels lowered vibrations by 10% at the backrest compared to the standard and CLX wheels (p-value < 0.001) and by 7% at the footrest compared to the CLX (p-value < 0.05). They also reduced shocks by 7% at the backrest compared to the standard wheel and CLX (p-value < 0.001). No significant differences were found in comfort between the wheels. Results indicate that Loopwheels is effective at reducing vibration and shock, but more long-term testing is required to determine effects on health. Full article

Early childhood caries (ECC) is a growing public health concern worldwide. Although numerous systematic reviews have been published regarding the association between breastfeeding and early childhood caries (ECC), the results remain inconclusive and equivocal. This systematic review synthesises the evidence on the association between breastfeeding and ECC. Five electronic databases and backward citation chasing were performed from inception until May 2023. A total of 31 studies (22 cohort studies and 9 case-control studies) were included in this review. The meta-analysis of the case-control studies showed statistically significant fewer dental caries in children who were breastfed for < 6 months compared to those who were breastfed for ≥6 months (OR = 0.53, 95% CI 0.41–0.67, p < 0.001). There was a statistically significant difference in dental caries between children who were breastfed for <12 months and those who were breastfed for ≥12 months (RR = 0.65, 95% CI 0.50–0.86, p < 0.002). Similarly, there was a statistically significant difference in dental caries in children who were breastfed for < 18 months compared to those who were breastfed for ≥18 months (RR = 0.41, 95% CI 0.18–0.92, p = 0.030). Nocturnal breastfeeding increases the risk of ECC compared with no nocturnal breastfeeding (RR = 2.35, 95% CI 1.42–3.89, p < 0.001). The findings suggest breastfeeding for more than 12 months and nocturnal breastfeeding increase the risk of ECC. Full article

As a recently developed high-strength aluminium alloy used specifically for laser additive manufacturing, AlMgMnSc alloy possesses superior mechanical properties and excellent processability. Extreme high-speed laser deposition (EHLD) is a novel surface-modification technique, which is characterised by high depositing speed, rapid cooling, rate and minimal dilution rate. To offer a new method for surface repairing high-strength aluminium alloys, an AlMgMnSc alloy coating, containing two deposition layers, is prepared on a 6061 aluminium-alloy axle using the EHLD technique. Meanwhile, the microstructure, composition distribution, and microhardness variation of the fabricated coating are studied. The results reveal that the coating is dense and crack-free, which is well-bonded with the substrate. Additionally, layer 1 is mainly composed of large columnar and equiaxed grains, while layer 2 consists of a fully equiaxed grain structure with an average grain size of about 4.5 μm. Moreover, the microhardness of the coating (about 104~118 HV) is similar to the substrate (about 105 HV), proving the feasibility of repairing high-strength aluminium alloys using AlMgMnSc alloy powders through the EHLD technique. Full article

This study optimized the input processing factors, namely compression force, pressing speed, heating temperature, and heating time, for extracting oil from desiccated coconut medium using a vertical compression process by applying a maximum load of 100 kN. The samples’ pressing height of 100 mm was measured using a vessel chamber of diameter 60 mm with a plunger. The Box–Behnken design was used to generate the factors’ combinations of 27 experimental runs with each input factor set at three levels. The response surface regression technique was used to determine the optimum input factors of the calculated responses: oil yield (%), oil expression efficiency (%), and energy (J). The optimum factors’ levels were the compression force 65 kN, pressing speed 5 mm min⁻¹, heating temperature 80 °C, and heating time 52.5 min. The predicted values of the responses were 48.48%, 78.35%, and 749.58 J. These values were validated based on additional experiments producing 48.18 ± 0.45%, 77.86 ± 0.72%, and 731.36 ± 8.04 J. The percentage error values between the experimental and the predicted values ranged from 0.82 ± 0.65 to 2.43 ± 1.07%, confirming the suitability of the established regression models for estimating the responses. Full article

This paper presents an intelligent system for the dynamic estimation of sheep body weight (BW). The methodology used to estimate body weight is based on measuring seven biometric parameters: height at withers, rump height, body length, body diagonal length, total body length, semicircumference of the abdomen, and semicircumference of the girth. A biometric parameter acquisition system was developed using a Kinect as a sensor. The results were contrasted with measurements obtained manually with a flexometer. The comparison gives an average root mean square error (RMSE) of 9.91 and a mean $R^2$ of 0.81. Subsequently, the parameters were used as input in a back-propagation artificial neural network. Performance tests were performed with different combinations to make the best choice of architecture. In this way, an intelligent body weight estimation system was obtained from biometric parameters, with a 5.8% RMSE in the weight estimations for the best architecture. This approach represents an innovative, feasible, and economical alternative to contribute to decision-making in livestock production systems. Full article

Alkali-activated cementitious materials, as an environmentally friendly cementitious material, can effectively reduce carbon emissions and improve the utilisation of solid wastes. However, traditional strong alkali activators have limitations such as high carbon emissions and poor safety. In order to overcome the defects of traditional strong alkaline activators and realise the high value-added use of calcium carbide residue (CCR), this paper adopts CCR as an alkaline activator to activate granulated blast furnace slag (GBFS)-steel slag (SS) cementitious systems for the preparation of alkaline-activated cementitious materials. The effects of CCR content and SS content on the compressive strength and working performance of CCR-GBFS-SS cementitious systems are analysed, along with the hydration process of CCR-GBFS-SS cementitious systems and the mechanism of action through the hydration products, their chemical structure and their microscopic morphology. The research results show that CCR-GBFS-SS cementitious systems have a 28-day compressive strength of 41.5 MPa and they can be controlled by the setting time; however, the flow performance is poor. The SS content can be increased to improve the flow performance; however, this will reduce the compressive strength. In CCR-GBFS-SS cementitious systems, CCR is the main driving force of hydration reactions, GBFS mainly provides active silica and aluminium and the amorphous C-(A)-S-H gel and ettringite formed by the synergistic action of multiple solid wastes are the main sources of compressive strength. With the extension of the curing time, the amount of hydration products in the cementitious systems gradually increases and the matrix of the cementitious systems gradually becomes denser. This study will provide a reference for the consumption of low-value solid waste such as CCR and the preparation of low-carbon cementitious materials from multi-component solid wastes. Full article

Fibromyalgia syndrome (FM) is a chronic pain condition that affects a significant portion of the population; yet, this condition is still poorly understood. Prior research has suggested that individuals with FM display a heightened sensitivity to pain and signs of autonomic dysfunction. Recent advances in functional MRI analysis methods to model blood-oxygenation-level-dependent (BOLD) responses across networks of regions, and structural and physiological modeling (SAPM) have shown the potential to provide more detailed information about altered neural activity than was previously possible. Therefore, this study aimed to apply novel analysis methods to investigate altered neural processes underlying pain sensitivity in FM in functional magnetic resonance imaging (fMRI) data from the brainstem and spinal cord. Prior fMRI studies have shown evidence of functional differences in fibromyalgia (FM) within brain regions associated with pain’s motivational aspects, as well as differences in neural activity related to pain regulation, arousal, and autonomic homeostatic regulation within the brainstem and spinal cord regions. We, therefore, hypothesized that nociceptive processing is altered in FM compared to healthy controls (HCs) in the brainstem and spinal cord areas linked to autonomic function and descending pain regulation, including the parabrachial nuclei (PBN) and nucleus tractus solitarius (NTS). We expected that new details of this altered neural signaling would be revealed with SAPM. The results provide new evidence of altered neural signaling in FM related to arousal and autonomic homeostatic regulation. This further advances our understanding of the altered neural processing that occurs in women with FM. Full article

This research utilized long short-term memory (LSTM) to oversee an RLS-based mass estimator based on longitudinal vehicle dynamics for heavy-duty vehicles (HDVs) instead of using the predefined rules. A multilayer LSTM network that analyzed parameters such as vehicle speed, longitudinal acceleration, engine torque, engine speed, and estimated mass from the RLS mass estimator was employed as the supervision method. The supervisory LSTM network was trained offline to recognize when the vehicle was operated so that the RLS estimator gave an estimate with the desired accuracy and the network was used as a reliability flag. High-fidelity simulation software was employed to collect data used to train and test the network. A threshold on the error percentage of the RLS mass estimator was used by the network to check the reliability of the algorithm. The preliminary findings indicate that the reliability of the RLS mass estimator could be predicted by using the LSTM network. Full article

The treatment of metastatic melanoma has been revolutionised by immunotherapy, yet a significant number of patients do not respond, and many experience autoimmune adverse events. Associations have been reported between patient outcome and monocyte subsets, whereas vitamin C (ascorbate) has been shown to mediate changes in cancer-stimulated monocytes in vitro. We therefore investigated the relationship of ascorbate with monocyte subsets and epigenetic modifications in patients with metastatic melanoma receiving immunotherapy. Patients receiving immunotherapy were compared to other cancer cohorts and age-matched healthy controls. Ascorbate levels in plasma and peripheral blood-derived mononuclear cells (PBMCs), monocyte subtype and epigenetic markers were measured, and adverse events, tumour response and survival were recorded. A quarter of the immunotherapy cohort had hypovitaminosis C, with plasma and PBMC ascorbate levels significantly lower than those from other cancer patients or healthy controls. PBMCs from the immunotherapy cohort contained similar frequencies of non-classical and classical monocytes. DNA methylation markers and intracellular ascorbate concentration were correlated with monocyte subset frequency in healthy controls, but correlation was lost in immunotherapy patients. No associations between ascorbate status and immune-related adverse events or tumour response or overall survival were apparent. Full article

In the inquisitorial archive of Pedro Onofre Cortés, alias Moixina, we see fellow practitioner protesting his son’s marriage to Clara Sureda because she was an Old Christian. The poor match was blamed on the breast milk that was ingested as an infant, “andaba con cristianos porque había mamado leche de una mujer cristiana” (he went with Christians because of the milk drunk milk from a Christian woman) (Picazo y Muntaner). In early modern Spain, breastmilk was seen as responsible for transmitting virtues and vices, religious expressions of faith and moral traits. Following Galenic medical understanding equating milk with blood, it was women who were responsible for the transmission of purity, impurity (Alexandre-Bidon 175), for contamination and difference (Martínez 47). This brief citation reflects the hybrid environment and the dual practices that deeply informed the lives of the converso Jews. Moreover, the understanding of the hereditary nature of these traits, and the traditions of Judaism and Christianity, so often mixed in unique combinations are clearly demonstrated in the Inquisition trials of Cortés and his Chueta brethren. As regulation over the mother and the female body became increasingly important in controlling Iberian subjects and its empire, conversos complicate the feminization of impurity. This article explores how the conversos known as the Chuetas of Mallorca understood their religiosity and difference as seen through the lens of hybridity, breast milk and maternal care. Full article

Residual film pollution and excessive nitrogen fertilizer have become limiting factors for agricultural development. To investigate the feasibility of replacing conventional plastic film with biodegradable plastic film in cold and arid environments under nitrogen application conditions, field experiments were conducted from 2021 to 2022 with plastic film covering (including degradable plastic film (D) and ordinary plastic film (P)) combined with nitrogen fertilizer 0 (N0), 160 (N1), 320 (N2), and 480 (N3) kg·ha⁻¹. The results showed no significant difference (p > 0.05) in dry matter accumulation, photosynthetic gas exchange parameters, soil enzyme activity, or yield of spring maize under degradable plastic film cover compared to ordinary plastic film cover. Nitrogen fertilizer is the main factor limiting the growth of spring maize. The above-ground and root biomass showed a trend of increasing and then decreasing with the increase in nitrogen application level. Increasing nitrogen fertilizer can also improve the photosynthetic gas exchange parameters of leaves, maintain soil enzyme activity, and reduce soil pH. Under the nitrogen application level of N2, the yield of degradable plastic film and ordinary plastic film coverage increased by 3.74~42.50% and 2.05~40.02%, respectively. At the same time, it can also improve water use efficiency and irrigation water use efficiency, but it will reduce nitrogen fertilizer partial productivity and nitrogen fertilizer agronomic use efficiency. Using multiple indicators to evaluate the effect of plastic film mulching combined with nitrogen fertilizer on the comprehensive growth of spring maize, it was found that the DN2 treatment had the best complete growth of maize, which was the best model for achieving stable yield and income increase and green development of spring maize in cold and cool irrigation areas. Full article

One of the crucial factors in grain storage is appropriate moisture content, which plays a significant role in reducing storage losses and ensuring quality. However, currently available humidity sensors on the market fail to meet the demands of modern large-scale grain storage in China in terms of price, size, and ease of implementation. Therefore, this study aims to develop an economical, efficient, and easily deployable grain humidity sensor suitable for large-scale grain storage environments. Simultaneously, it constructs humidity calibration models applicable to three major grain crops: millet, rice, and wheat. Starting with the probe structure, this study analyzes the ideal probe structure for grain humidity sensors. Experimental validations are conducted using millet, rice, and wheat as experimental subjects to verify the accuracy of the sensor and humidity calibration models. The experimental results indicate that the optimal length of the probe under ideal conditions is 0.67 m. Humidity calibration models for millet, rice, and wheat are constructed using SVM models, with all three models achieving a correlation coefficient R² greater than 0.9. The measured data and model-calculated data show a linear relationship, closely approximating y = x, with R² values of all three fitted models above 0.9. In conclusion, this study provides reliable sensor technological support for humidity monitoring in large-scale grain storage and processing, with extensive applications in grain storage and grain safety management. Full article

This study aimed to investigate how stakeholders in the United States beef industry incorporate animal welfare into their sustainability programs. A survey was administered online to the U.S. Roundtable for Sustainable Beef membership. Twenty-seven surveys were analyzed. Most respondents (n = 26, 96%) had sustainability programs that incorporated animal welfare. Most respondents believed that welfare positively impacted environmental (n = 25/26, 96%), economic (n = 25/26, 96%), and social (n = 26/26, 100%) sustainability. The thematic analysis of five free response questions identified ten themes: Animal Care, Regulations and Guidelines, Responsibility, Consumers and Stakeholders, Performance and Efficiency, Financial Impact, Connectedness, Critical Component, Animal-based Outcomes, and Employees. When asked to define welfare, the most common themes were Animal Care and Regulations and Guidelines. When asked why welfare was a component of their sustainability program, the top factors from a provided list were: cattle health (n = 20, 74%), cattle performance (n = 12, 44%), and consumer perceptions (n = 12, 44%). Findings suggest a widespread recognition of animal welfare’s importance within sustainable beef production. Full article

This article is about a framework for determining the degree of realism of any given passenger ride motion discomfort measurement formula. After providing some context and reviewing evidence of deficiency in currently popular ride motion discomfort measurement formulas, the article outlines the research program that needs to be carried out in order to establish such a framework. The research begins with gathering recordings of uncomfortable ride motion episodes encountered in a chosen type of passenger transport service. It then has test subjects compare the episodes via a ride motion simulator and adjust their amplitudes pair wise until they cause equal discomfort. It explains how to take the pair wise amplitude adjustments and determine amplitude adjustments that bring all of the motion episode recordings to a common level of discomfort so that they form a normalized set. Then, the lower the scatter of the scores assigned by any given discomfort measurement formula to the members of that set, the more realistic that formula will be for the chosen service. Full article

Nanosilver is a popular nanomaterial, the potential influence of which on humans is of serious concern. Herein, we exposed male Wistar rats to two regimens: a repeated oral dose of 30 mg/kg bw silver nanoparticles (AgNPs) over 28 days and a single-dose injection of 5 mg/kg bw of AgNPs. At three different time points, we assessed antioxidant defense, oxidative stress and inflammatory parameters in the colon, as well as toxicity markers in the liver and plasma. Both experimental scenarios showed increased oxidative stress and inflammation in the colon. Oral administration seemed to be linked to increased reactive oxygen species generation and lipid peroxidation, while the effects induced by the intravenous exposure were probably mediated by silver ions released from the AgNPs. Repeated oral exposure had a more detrimental effect than the single-dose injection. In conclusion, both administration routes had a similar impact on the colon, although the underlying mechanisms are likely different. Full article

Vibrio cholerae is the etiological agent of cholera in humans. The bacterium is frequently detected in aquatic products worldwide. However, the current literature on the genome evolution of V. cholerae of aquatic animal origins is limited. Here, we firstly characterized the growth and genome features of V. cholerae isolates with different resistance phenotypes from three species of common freshwater fish. The results revealed that the non-O1/O139 V. cholerae isolates (n = 4) were halophilic and grew optimally at 2% NaCl and pH 8.0. Their draft genome sequences were 3.89 Mb–4.15 Mb with an average GC content of 47.35–47.63%. Approximately 3366–3561 genes were predicted to encode proteins, but 14.9–17.3% of them were of an unknown function. A number of strain-specific genes (n = 221–311) were found in the four V. cholerae isolates, 3 of which belonged to none of any of the known sequence types (STs). Several putative mobile genetic elements (MGEs) existed in the V. cholerae isolates, including genomic islands (n = 4–9), prophages (n = 0–3), integrons (n = 1–1), and insertion sequences (n = 0–3). Notably, CRISPR-Cas system arrays (n = 2–10) were found in the V. cholerae genomes, whereby the potential immunity defense system could be active. Comparative genomic analyses also revealed many putative virulence-associated genes (n = 106–122) and antibiotic resistance-related genes (n = 6–9). Overall, the results of this study demonstrate the bacterial broader-spectrum growth traits and fill prior gaps in the genomes of V. cholerae originating from freshwater fish. Full article

Background and Aims: Accurate recognition of endoscopic instruments facilitates quantitative evaluation and quality control of endoscopic procedures. However, no relevant research has been reported. In this study, we aimed to develop a computer-assisted system, EndoAdd, for automated endoscopic surgical video analysis based on our dataset of endoscopic instrument images. Methods: Large training and validation datasets containing 45,143 images of 10 different endoscopic instruments and a test dataset of 18,375 images collected from several medical centers were used in this research. Annotated image frames were used to train the state-of-the-art object detection model, YOLO-v5, to identify the instruments. Based on the frame-level prediction results, we further developed a hidden Markov model to perform video analysis and generate heatmaps to summarize the videos. Results: EndoAdd achieved high accuracy (>97%) on the test dataset for all 10 endoscopic instrument types. The mean average accuracy, precision, recall, and F1-score were 99.1%, 92.0%, 88.8%, and 89.3%, respectively. The area under the curve values exceeded 0.94 for all instrument types. Heatmaps of endoscopic procedures were generated for both retrospective and real-time analyses. Conclusions: We successfully developed an automated endoscopic video analysis system, EndoAdd, which supports retrospective assessment and real-time monitoring. It can be used for data analysis and quality control of endoscopic procedures in clinical practice. Full article

The judiciary is a field lacking research in relation to its administration and innovation; however, different theoretical perspectives can be followed. This work reviews this trend while adding to it. An institutional perspective is presented, as is its explanatory potential. This perspective captures the context of the public sector; however, when analyzing its interpretation in terms of innovation, it is revealed to be doubly paradoxical. From the theoretical point of view, institutionalization focuses on the maintenance of processes, while innovation, gradually or abruptly, investigates their disruptions. Nevertheless, institutionalization can be observed as part of the sedimentation of innovation. Institutionalization is presented, in the context of innovation, as a selection mechanism that shapes such innovation. This paradox is presented under the review of organizational institutionalism vis-à-vis innovation and, for its unfolding, considers the adoption of innovation as an adaptation to the prevalent rationalized elements. This presentation is paralleled with the interpretation that innovation is limited by a structure that, sometimes rationalized, forms its trajectory. Considering the social function of the judiciary that is anchored in institutionalism, historical institutionalism is thus added, centrally placing the judiciary in the current institutional matrix and associating its path dependence with the dimensions of its innovation. Based on these outlines, propositions and a suggested agenda for future research are presented. Full article

In this paper, we introduce a novel rate control scheme specifically tailored for live broadcasting scenarios. Notably, in high-definition live transmissions of sports events and video game competitions that typically exceed 1080 p resolution and run at frame rates of 60 fps or higher, the transcoding speed of encoders often becomes a limiting factor, leading to streams with substantial bitrates but unsatisfactory quality metrics. To enhance the overall Quality of Service (QoS) without increasing the bitrate, it is essential to improve the quality of Regions of Interest (ROI).Our proposed solution presents an ROI-based rate reservoir model that ingeniously leverages Convolutional Neural Networks (CNNs) to predict rate control parameters. This approach aims to optimize the bitrate allocation within high bitrate live broadcasts, thus enhancing the image quality within ROIs. Experimental outcomes demonstrate that this algorithm manages to increase the bitrate by no more than 5%, effectively redistributing the reduced bitrate across the entire Group of Pictures (GOP). As a result, it ensures a gradual decrease in the quality of Regions of Uninterest (ROU), thereby maintaining a balanced quality experience throughout the broadcasted content. Full article

Phthalates are chemical compounds, mainly used as additives in plastics, which are known to induce harmful impacts to the environment and human health due to their ability to act as hormone-mimics. Few studies have been reported on the relationship between human exposure to phthalates and the level of circulating microRNAs (miRs), especially those miRs encapsulated in extracellular vesicles/exosomes or exosome-like vesicles (ELVs). We examined the relationship of ELV-miR expression patterns and urine of adult men with five phthalate metabolites (i.e., mono isobutyl phthalate, mono-n-butyl phthalate, mono benzyl phthalate, mono-(2-ethyl-5-oxohexyl) phthalate, mono-(2-ethylhexyl) phthalate) to identify potential biomarkers and relevant pathways. We found significant positive associations which were further confirmed by multivariable analysis. Overall, our analyses showed that the Σ phthalate metabolite concentration was associated with a significant increase in the expression level of two miRs found in ELV: miR-202 and miR-543. Different pathways including cancer and immune-related responses were predicted to be involved in this relationship. Analyzing the specific downstream target genes of miR-202 and miR-543, we identified the phosphatase and tensin homolog (PTEN) as the key gene in several converging pathways. In summary, the obtained results demonstrate that exposure to environmental phthalates could be related to altered expression profiles of specific ELV-miRs in adult men, thereby demonstrating the potential of miRs carried by exosomes to act as early effect biomarkers. Full article

Forest fires represent a significant menace to both the ecological equilibrium of forests and the safety of human life and property. Upon ignition, fires frequently generate billowing smoke. The prompt identification and management of fire sources and smoke can efficiently avert the occurrence of extensive forest fires, thereby safeguarding both forest resources and human well-being. Although drone patrols have emerged as a primary method for forest-fire prevention, the unique characteristics of forest-fire images captured from high altitudes present challenges. These include remote distances, small fire points, smoke targets with light hues, and complex, ever-changing background environments. Consequently, traditional target-detection networks frequently exhibit diminished accuracy when handling such images. In this study, we introduce a cutting-edge drone-based network designed for the detection of forest fires and smoke, named FSNet. To begin, FSNet employs the YOCO data-augmentation method to enhance image processing, thereby augmenting both local and overall diversity within forest-fire images. Next, building upon the transformer framework, we introduce the EBblock attention module. Within this module, we introduce the notion of “groups”, maximizing the utilization of the interplay between patch tokens and groups to compute the attention map. This approach facilitates the extraction of correlations among patch tokens, between patch tokens and groups, and among groups. This approach enables the comprehensive feature extraction of fire points and smoke within the image, minimizing background interference. Across the four stages of the EBblock, we leverage a feature pyramid to integrate the outputs from each stage, thereby mitigating the loss of small target features. Simultaneously, we introduce a tailored loss function, denoted as $L_{forest}$, specifically designed for FSNet. This ensures the model’s ability to learn effectively and produce high-quality prediction boxes. We assess the performance of the FSNet model across three publicly available forest-fire datasets, utilizing mAP, Recall, and FPS as evaluation metrics. The outcomes reveal that FSNet achieves remarkable results: on the Flame, Corsican, and D-Fire datasets, it attains mAP scores of 97.2%, 87.5%, and 94.3%, respectively, with Recall rates of 93.9%, 87.3%, and 90.8%, respectively, and FPS values of 91.2, 90.7, and 92.6, respectively. Furthermore, extensive comparative and ablation experiments validate the superior performance of the FSNet model. Full article

Maize residue cover (MRC) is an important parameter to quantify the degree of crop residue cover in the field and its spatial distribution characteristics. It is also a key indicator of conservation tillage. Rapid and accurate estimation of maize residue cover (MRC) and spatial mapping are of great significance to increasing soil organic carbon, reducing wind and water erosion, and maintaining soil and water. Currently, the estimation of maize residue cover in large areas suffers from low modeling accuracy and poor working efficiency. Therefore, how to improve the accuracy and efficiency of maize residue cover estimation has become a research hotspot. In this study, adaptive threshold segmentation (Yen) and the CatBoost algorithm are integrated and fused to construct a residue coverage estimation method based on multispectral remote sensing images. The maize planting areas in and around Sihe Town in Jilin Province, China, were selected as typical experimental regions, and the unmanned aerial vehicle (UAV) was employed to capture maize residue cover images of sample plots within the area. The Yen algorithm was applied to calculate and analyze maize residue cover. The successive projections algorithm (SPA) was used to extract spectral feature indices from Sentinel-2A multispectral images. Subsequently, the CatBoost algorithm was used to construct a maize residue cover estimation model based on spectral feature indices, thereby plotting the spatial distribution map of maize residue cover in the experimental area. The results show that the image segmentation based on the Yen algorithm outperforms traditional segmentation methods, with the highest Dice coefficient reaching 81.71%, effectively improving the accuracy of maize residue cover recognition in sample plots. By combining the spectral index calculation with the SPA algorithm, the spectral features of the images are effectively extracted, and the spectral feature indices such as NDTI and STI are determined. These indices are significantly correlated with maize residue cover. The accuracy of the maize residue cover estimation model built using the CatBoost model surpasses that of traditional machine learning models, with a maximum determination coefficient (R²) of 0.83 in the validation set. The maize residue cover estimation model constructed based on the Yen and CatBoost algorithms effectively enhances the accuracy and reliability of estimating maize residue cover in large areas using multispectral imagery, providing accurate and reliable data support and services for precision agriculture and conservation tillage. Full article