In the face of persistent soil degradation in Benin caused by poor agricultural practices, including excessive use of chemical fertilizers, it is urgent to find solutions that take into account the microorganisms of interest. This study aimed to assess the effect of combining three strains of indigenous arbuscular mycorrhizal fungi (AMF) on maize production in northern Benin. The study involved 34 growers in Ouénou, Bagou and Kokey. The experimental setup consisted of three elementary plots with three treatments. Growth parameters were measured every 15 days, from the 15^th to the 60^th day after sowing, on ten plants per plot. Plant nutritional status, grain yield and mycorrhization were measured. The results showed that biostimulant + 50% NPK_Urea (N = nitrogen, P = phosphorus and K = potassium) had similar positive effects on growth parameters to those induced by the application of 100% NPK_Urea. Gains of 30.25% to 36.35% were recorded in plant height at Kokey. On the other hand, biostimulant+ 50% NPK_Urea induced a better phosphorus uptake of 21.08% to 27.77%. In addition, the grain yield of mycorrhizal plants was 8.37% higher than that of plants receiving 100% NPK_Urea at Ouénou. These results show that this technology could be integrated into the agricultural system to promote sustainable maize growing in Benin. Full article

Background: Patients with advanced-stage epithelial ovarian cancer (EOC) receive treatment with a poly-ADP ribose-polymerase (PARP) inhibitor (PARPi) as maintenance therapy after surgery and chemotherapy. Unfortunately, many patients experience disease progression because of acquired therapy resistance. This study aims to characterize epigenetic and genomic changes in cell-free DNA (cfDNA) associated with PARPi resistance. Materials and Methods: Blood was taken from 31 EOC patients receiving PARPi therapy before treatment and at disease progression during/after treatment. Resistance was defined as disease progression within 6 months after starting PARPi and was seen in fifteen patients, while sixteen patients responded for 6 to 42 months. Blood cfDNA was evaluated via Modified Fast Aneuploidy Screening Test-Sequencing System (mFast-SeqS to detect aneuploidy, via Methylated DNA Sequencing (MeD-seq) to find differentially methylated regions (DMRs), and via shallow whole-genome and -exome sequencing (shWGS, exome-seq) to define tumor fractions and mutational signatures. Results: Aneuploid cfDNA was undetectable pre-treatment but observed in six patients post-treatment, in five resistant and one responding patient. Post-treatment ichorCNA analyses demonstrated in shWGS and exome-seq higher median tumor fractions in resistant (7% and 9%) than in sensitive patients (7% and 5%). SigMiner analyses detected predominantly mutational signatures linked to mismatch repair and chemotherapy. DeSeq2 analyses of MeD-seq data revealed three methylation signatures and more tumor-specific DMRs in resistant than in responding patients in both pre- and post-treatment samples (274 vs. 30 DMRs, 190 vs. 57 DMRs, Χ²-test p < 0.001). Conclusion: Our genome-wide Next-Generation Sequencing (NGS) analyses in PARPi-resistant patients identified epigenetic differences in blood before treatment, whereas genomic alterations were more frequently observed after progression. The epigenetic differences at baseline are especially interesting for further exploration as putative predictive biomarkers for PARPi resistance. Full article

Deep learning-based 3D target detection methods need to solve the problem of insufficient 3D target detection accuracy. In this paper, the KM3D network is selected as the benchmark network after the experimental comparison of current mainstream algorithms, and the IAE-KM3D network algorithm based on the KM3D network is proposed. First, the Resnet V2 network is introduced, and the residual module is redesigned to improve the training capability of the new residual module with higher generalization. IBN NET is then introduced to carefully integrate instance normalization and batch normalization as building blocks to improve the model’s detection accuracy in hue- and brightness-changing scenarios without increasing time loss. Then, a parameter-free attention mechanism, Simam, is introduced to improve the detection accuracy of the model. After that, the elliptical Gaussian kernel is introduced to improve the algorithm’s ability to detect 3D targets. Finally, a new key point loss function is proposed to improve the algorithm’s ability to train. Experiments using the KITTI dataset conclude that the IAE-KM3D network model significantly improves detection accuracy and outperforms the KM3D algorithm regarding detection performance compared to the original KM3D network. The improvements for AP_2D, AP_3D, and AP_BEV are 5%, 12.5%, and 8.3%, respectively, and only a tiny amount of time loss and network parameters are added. Compared with other mainstream target detection algorithms, Monn3D, 3DOP, GS3D, and FQNet, the improved IAE-KM3D network in this paper significantly improves AP_3D and AP_BEV, with fewer network parameters and shorter time consumption. Full article

Over recent decades, Landsat satellite data has evolved into a highly valuable resource across diverse fields. Long-term satellite data records with integrity and consistency, such as the Landsat series, provide indispensable data for many applications. However, the malfunction of the Scan Line Corrector (SLC) on the Landsat 7 satellite in 2003 resulted in stripping in subsequent images, compromising the temporal consistency and data quality of Landsat time-series data. While various methods have been proposed to improve the quality of Landsat 7 SLC-off data, existing gap-filling methods fail to enhance the temporal resolution of reconstructed images, and spatiotemporal fusion methods encounter challenges in managing large-scale datasets. Therefore, we propose a method for reconstructing dense time series from SLC-off data. This method utilizes the Neighborhood Similar Pixel Interpolator to fill in missing values and leverages the time-series information to reconstruct high-resolution images. Taking the blue band as an example, the surface reflectance verification results show that the Mean Absolute Error (MAE) and BIAS reach minimum values of 0.0069 and 0.0014, respectively, with the Correlation Coefficient (CC) and Structural Similarity Index Metric (SSIM) reaching 0.93 and 0.94. The proposed method exhibits advantages in repairing SLC-off data and reconstructing dense time-series data, enabling enhanced remote sensing applications and reliable Earth’s surface reflectance data reconstruction. Full article

In a multi-source permanent magnet synchronous motor (PMSM) drive, three distinct winding structures can be implemented: multi-sector, multi-three-phase, and highly coupled. However, due to variations in the magnetic coupling between windings, their low-frequency DC-link current ripple components differ. This paper presents a method to identify the phenomena associated with each low-frequency harmonic content. Three analytical models are developed for the DC current ripple induced by unbalanced winding, counter-electromotive force (back-EMF) harmonics and aliasing effects, respectively, with the results validated through simulations. Experimental validation is conducted for highly coupled winding drives, demonstrating agreement with the analytical models and simulations. The maximum DC current ripple ratio found in the analytical model, the simulation and the experiments is less than $15\%$, which is deemed acceptable for motor drive applications. Full article

This study aimed to explore the potential of Urtica dioica (U. dioica) ethanolic leaf extract for cancer treatment by identifying its components, evaluating its effects on cancer cell lines, and analyzing its molecular docking. The objective of this study was to investigate the anticancer properties of U. dioica ethanolic leaf extract and assess its potential as a therapeutic strategy for cancer treatment. This study utilized high-performance liquid chromatography (HPLC) to analyze the chemical composition of U. dioica ethanolic leaf extract. The anticancer effects of the extract were evaluated by assessing cell viability, determining IC50 values, and conducting ADMET analysis after oral administration. U. dioica ethanolic leaf extract was found to contain methyl hexadecanoate as its primary component, along with flavonoids and polyphenols. It effectively reduced cell viability in various tested cancer cell lines, with IC50 values varying for each cell line. The duration of treatment significantly influenced cell viability, with the most significant reduction observed after 48 h. Molecular docking studies suggested that catechin, kaempferol, and quercetin-3-O-rutinoside may have potential as inhibitors of the MTHFD2 enzyme. This study revealed the potential of U. dioica and its compounds in cancer treatment. Ethanolic leaf extract has been shown to have anticancer effects on various cancer cell lines, with catechin and kaempferol showing promise as inhibitors of the MTHFD2 enzyme. Further research is warranted to explore the therapeutic implications of U. dioica in cancer treatment. Full article

Cybersecurity has become a major concern in the modern world due to our heavy reliance on cyber systems. Advanced automated systems utilize many sensors for intelligent decision-making, and any malicious activity of these sensors could potentially lead to a system-wide collapse. To ensure safety and security, it is essential to have a reliable system that can automatically detect and prevent any malicious activity, and modern detection systems are created based on machine learning (ML) models. Most often, the dataset generated from the sensor node for detecting malicious activity is highly imbalanced because the Malicious class is significantly fewer than the Non-Malicious class. To address these issues, we proposed a hybrid data balancing technique in combination with a Cluster-based Under Sampling and Synthetic Minority Oversampling Technique (SMOTE). We have also proposed an ensemble machine learning model that outperforms other standard ML models, achieving 99.7% accuracy. Additionally, we have identified the critical features that pose security risks to the sensor nodes with extensive explainability analysis of our proposed machine learning model. In brief, we have explored a hybrid data balancing method, developed a robust ensemble machine learning model for detecting malicious sensor nodes, and conducted a thorough analysis of the model’s explainability. Full article

A hypothesis is presented to explain how the ageing process might be influenced by optimizing mitochondrial efficiency to reduce intracellular entropy. Research-based quantifications of entropy are scarce. Non-equilibrium metabolic reactions and compartmentalization were found to contribute most to lowering entropy in the cells. Like the cells, mitochondria are thermodynamically open systems exchanging matter and energy with their surroundings—the rest of the cell. Based on the calculations from cancer cells, glycolysis was reported to produce less entropy than mitochondrial oxidative phosphorylation. However, these estimations depended on the CO₂ concentration so that at slightly increased CO₂, it was oxidative phosphorylation that produced less entropy. Also, the thermodynamic efficiency of mitochondrial respiratory complexes varies depending on the respiratory state and oxidant/antioxidant balance. Therefore, in spite of long-standing theoretical and practical efforts, more measurements, also in isolated mitochondria, with intact and suboptimal respiration, are needed to resolve the issue. Entropy increases in ageing while mitochondrial efficiency of energy conversion, quality control, and turnover mechanisms deteriorate. Optimally functioning mitochondria are necessary to meet energy demands for cellular defence and repair processes to attenuate ageing. The intuitive approach of simply supplying more metabolic fuels (more nutrients) often has the opposite effect, namely a decrease in energy production in the case of nutrient overload. Excessive nutrient intake and obesity accelerate ageing, while calorie restriction without malnutrition can prolong life. Balanced nutrient intake adapted to needs/activity-based high ATP requirement increases mitochondrial respiratory efficiency and leads to multiple alterations in gene expression and metabolic adaptations. Therefore, rather than overfeeding, it is necessary to fine-tune energy production by optimizing mitochondrial function and reducing oxidative stress; the evidence is discussed in this paper. Full article

The study of the properties of ferroelectric materials against irradiation has a long history. However, anti−irradiation research on the ferroelectric domain has not been carried out. In this paper, the irradiation of switched domain structure is innovatively proposed. The switched domain of 700 nm lithium niobate (LiNbO₃, LN) thin film remains stable after gamma irradiation from 1 krad to 10 Mrad, which was prepared by piezoresponse force microscopy (PFM). In addition, the changing law of domain wall resistivity is explored through different sample voltages, and it is verified that the irradiated domain wall conductivity is still larger than the domain. This domain wall current (DWC) property can be applied to storage, logic, sensing, and other devices. Based on these, a ferroelectric domain irradiation resistance model is established, which explains the reason at an atomic level. The results open a possibility for exploiting ferroelectric materials as the foundation in the application of space and nuclear fields. Full article

Colorectal cancer (CRC) outcomes in terms of incidence and mortality are significantly worse in African Americans than other Americans. While differences in primary preventions for neoplasia (diet, obesity remediation, aspirin prophylaxis) are being elucidated, genetic mutations affecting premalignant lesions and immune response mechanisms may possibly also explain the increased incidence and mortality, particularly from right-sided disease. Objective: Our team therefore examined colonic segments seeking to test the hypothesis that the immune response and somatic genetic profiles of the colonic anatomic segments may vary and thus account for variations in neoplasia risk among the various colonic segments revealing an antigenic relationship with precancerous lesions. The p87 antigenic field effect is recognized via Adnab-9 antibody immunohistochemistry to be significantly less in the right colon in African Americans, particularly in the cecum. Method: Since small high-grade dysplastic adenomas (SHiGDA) likely missed by CRC screening may progress to cancer, we used Ion Torrent™ sequencing of DNA extracted from four normal colonic segments (two left-sided and two right) of patients with SHiGDAs. We also contrasted unique mutational fields in one patient with a large HiGDA (APC with unique mutations) and one patient who prospectively developed a SHiGDA (JAK3). Result: The SHiGDA (small high-grade dysplastic polyp) patient was p87 negative for any extracted stool, saliva, or colonic effluent via ELISA (enzyme linked immunoadsorbant assay). Furthermore, mean values of expression in segments from the right colon were reduced with respect to the means obtained from the left segments in 233 patients evaluated for a p87 field effect. This has recently been shown to be the case in a large cohort of AA and Caucasian 2294 patients, possibly explaining the right-sided CRC disparity in African Americans and the subsequent increase in mortality. This field effect disparity is also true for two cancers contracted by the SHiGDa patient (lung and prostate). Conclusion: Thus, this pilot study suggests that the reduction in p87 in the right colon is possibly correlated with JAK3 mutations. If confirmed, JAK3 mutations, known to be associated with immune aberrations, may provide a mechanistic explanation for the lack of a p87 (protein 87 kilodaltons) field in some patients with HGD polyps who might benefit from possible intervention such as more intensive screening. Limited microbiome studies were also performed on two patients with familial cancer syndromes and these compared favorably with controls available from the literature. Full article

The dropout rate in underdeveloped and emerging countries is a pressing social issue, as highlighted by studies conducted by The Organization for Economic Co-operation and Development. This study compares five feature selection techniques to address this challenge and improve the automatic detection of dropout risk. The methodological design involves three distinct phases: data preparation, feature selection, and model evaluation utilizing machine learning algorithms. The results demonstrate that (1) the top features identified by feature selection techniques, i.e., those constructed through feature engineering, proved to be among the most effective in classifying student dropout; (2) the F-score of the best model increased by 5% with feature selection techniques; and (3) depending on the type of feature selection, the performance of the machine learning algorithm can vary, potentially increasing or decreasing based on the sensitivity of features with higher noise. At the same time, metaheuristic algorithms demonstrated significant precision improvements, but there was a risk of increasing errors and reducing recall. Full article

Background: Disasters have caused suffering across the world throughout history. Different types of disaster events can manifest themselves in different ways, originating from natural phenomena, human actions and their interconnected interactions. In recent years, organizations in charge of disaster management have faced a series of challenges in humanitarian logistics, leading to an increasing consideration of the use of models of prioritization, in most multi-criteria models, to define the best alternatives for more assertive and strategic decision-making. Methods: This article aims to conduct a systematic review of the literature on the application of prioritization models in humanitarian logistics. To this end, an analysis was carried out of 40 articles, indexed in the Scopus or Web of Science databases. Results: The descriptive analysis revealed that the majority of applications are aimed at dealing with sudden-onset natural-induced disasters. However, there are still gaps in relevant areas, such as addressing inventory management problems at a tactical decision level. Conclusions: The development of prioritization models necessitates the integration of various methodologies, combining optimization models with multi-criteria decision analysis to yield superior outcomes. It is advised to incorporate four distinct criteria—efficiency, effectiveness, equity, and sustainability—to ensure a comprehensive assessment of the decision-making process. Full article

During cycling, prolonged compression by the bicycle saddle on the anatomical structures located in the perineum area occurs. An additional factor that may have a negative impact on organs located in the pelvic area may be a prolonged sitting position resulting in increased intraabdominal pressure. This situation has the potential to adversely affect pelvic floor function. Therefore, the aim of this study was to assess the incidence of lower urinary tract symptoms (LUTSs) in female competitive road cyclists and cross-country cyclists. The study included 76 female competitive road cyclists and cross-country cyclists and 76 women not practising competitive sport. The Core Lower Urinary Tract Symptom Score (CLSS) questionnaire was used to assess the lower urinary tract condition. Female competitive cyclists had a statistically significantly higher LUTSs score (95% CI: 3.12–4.2 vs. 2.31–3.16; p < 0.05) compared to women not practising competitive sports. Female cyclists had a statistically significantly higher overall CLSS score (95% CI: 3.99–5.61 vs. 2.79–3.97; p < 0.05). Female cyclists had a statistically significantly higher incidence and severity of urinary frequency (p < 0.05 and p < 0.02), urge (p < 0.001 and p < 0.02) and stress incontinence (p < 0.001 and p < 0.001), and pain in the bladder (p < 0.01 and p < 0.01), while physically inactive women recorded a statistically higher incidence of slow urinary stream (p < 0.01 and p < 0.04). A statistically significant association was recorded between the years of cycling and the number of hours per week spent on training and the number of symptoms and their severity. The number of natural births experienced by women involved in competitive cycling significantly affects the severity of LUT symptoms. Compared to women not practising competitive sports, competitive female cyclists are found to have a higher prevalence of LUTSs and a greater degree of severity. LUTSs in competitive female cyclists are negatively influenced by years of competitive career and weekly number of training hours and the number of natural births experienced. Full article

Given the importance of biological nitrogen (N) fixation in agroecosystems, using inoculants with phyllosphere N fixers effective across various crops would revolutionize agriculture. In this study, the application of an inoculant prepared from Methylobacterium symbioticum was tested on young olive trees. The pot experiment was arranged in a factorial design, with inoculant (Yes and No) and mineral N applied to the soil (0 (aN0), 25 (N25), 50 (N50), and 100 (N100) kg ha⁻¹), and four replicates. The inoculant application did not increase plant dry matter yield (DMY), whereas the application of mineral N had a significant and pronounced effect. The inoculant also did not significantly increase N concentration in tissues, unlike the strong increase observed with N applied to the soil. The inoculant significantly increased plant N recovery, a cumulative effect resulting from small increases in DMY and N concentration in tissues. This increase represented 5.2% more N in plants receiving the inoculant compared to untreated ones. However, only treatments receiving mineral N recorded positive values of fixed N, with the highest value observed in the N50 treatment (12.4%), whereas a negative value (−7.7%) was observed in the N0 treatment. Overall, these low values of fixed N question the economic rationale of using this inoculant by farmers and especially render it unsuitable for organic farming systems, where plants tend to have lower N levels in tissues. Full article

Aircraft failures can result in the leakage of fuel, hydraulic oil, or other lubricants onto the runway during landing or taxiing. Damage to fuel tanks or oil lines during hard landings or accidents can also contribute to these spills. Further, improper maintenance or operational errors may leave oil traces on the runway before take-off or after landing. Identifying oil spills in airport runway videos is crucial to flight safety and accident investigation. Advanced image processing techniques can overcome the limitations of conventional RGB-based detection, which struggles to differentiate between oil spills and sewage due to similar coloration; given that oil and sewage have distinct spectral absorption patterns, precise detection can be performed based on multispectral images. In this study, we developed a method for spectrally enhancing RGB images of oil spills on airport runways to generate HSI images, facilitating oil spill detection in conventional RGB imagery. To this end, we employed the MST++ spectral reconstruction network model to effectively reconstruct RGB images into multispectral images, yielding improved accuracy in oil detection compared with other models. Additionally, we utilized the Fast R-CNN oil spill detection model, resulting in a 5% increase in Intersection over Union (IOU) for HSI images. Moreover, compared with RGB images, this approach significantly enhanced detection accuracy and completeness by 25.3% and 26.5%, respectively. These findings clearly demonstrate the superior precision and accuracy of HSI images based on spectral reconstruction in oil spill detection compared with traditional RGB images. With the spectral reconstruction technique, we can effectively make use of the spectral information inherent in oil spills, thereby enhancing detection accuracy. Future research could delve deeper into optimization techniques and conduct extensive validation in real airport environments. In conclusion, this spectral reconstruction-based technique for detecting oil spills on airport runways offers a novel and efficient approach that upholds both efficacy and accuracy. Its wide-scale implementation in airport operations holds great potential for improving aviation safety and environmental protection. Full article

The COVID-19 pandemic, propelled by the highly transmissible Omicron variant, had a global impact and significantly affected Shanghai, a major city in China. This study investigates how food media exposure influenced unhealthy eating habits among older adults during the COVID-19 lockdown in Shanghai, focusing on the roles of negative emotions, food literacy, health consciousness, and eating self-efficacy. The random sample comprised 400 individuals aged ≥50 years who lived in Shanghai from March to June 2022. A path and correlation analysis was performed. The exposure of older adults to food media resulted in the acceleration of unhealthy eating. The relationship was significantly exacerbated by food literacy and negative emotions. In contrast, eating self-efficacy and health consciousness effectively countered the media. The enhanced pathway from food-related media influence to eating habits through negative emotions or self-efficacy towards health awareness and food literacy showed significant effects. The findings provide insights for future research and public health strategies. Importantly, this study has practical significance for media professionals, public health decision-makers, and healthy food businesses regarding how to enhance older adults’ cognition to respond to unhealthy eating crises. Full article

To guarantee that the cement sheath has a sealing effect, it is best to replace the drilling fluid entirely and fill the annulus with cement slurry throughout the cementing process. A significant driving power and high stability at the interface between the cement slurry and drilling fluid are often necessary for achieving a high displacement efficiency. It is important that a comprehensive theoretical characterization is established on the thickness and location of drilling fluid retention and the conditions to prevent the formation of drilling fluid retention. In this study, firstly, the characteristics of annulus fluid shear stress distribution are analyzed by establishing the differential equation of shear stress distribution. Subsequently, the calculation model of the drilling fluid retention layer’s thickness is constructed. Subsequently, the impact of cement slurry and drilling fluid properties, eccentricity of the casing, and additional variables on the annular wall’s drilling fluid retention thickness are scrutinized. The quantitative conditions for preventing drilling fluid retention are also analyzed (i.e., Equation (23)). Based on the newly developed model, a case study is conducted to show the significance of the new model. This offers a theoretical foundation for enhancing cement injection displacement efficiency and cementing performance optimization. Full article

Traditionally, non-aureus staphylococci and mammaliicocci (NASM) were not considered significant players in bovine mastitis. This study investigated the involvement of NASM (Staphylococcus hominis and Staphylococcus chromogenes) and lactic acid bacteria (LAB) strains (Weissella paramesenteroides) through bovine neutrophil responses. Bovine neutrophils displayed minimal apoptosis upon NASM and LAB challenge. Neutrophils expressed high TLR2 after challenge, but TLR6 expression varied and remained low in NASM pathogen recognition. Bovine neutrophils effectively engulfed and killed LAB, but their activity was significantly impaired against NASM. This was evident in S. chromogenes, where reduced TLR6 recognition and a weakened phagocytic response likely contributed to a lower bactericidal effect. Regardless of the bacteria encountered, intracellular ROS production remained high. S. chromogenes-challenged neutrophils displayed upregulation in genes for pathogen recognition (TLRs), ROS production, and both pro- and anti-apoptotic pathways. This response mirrored that of Weissella. except for CASP9 and BCL2, suggesting these bacteria have divergent roles in triggering cell death. Our findings suggest that S. chromogenes manipulates bovine neutrophil defenses through coordinated changes in functional responses and gene expression, while LAB strains have a weaker influence on apoptosis. Full article

This study focuses on optimizing chlorophyll extraction techniques, in which leaf discs are cut from places on the leaf blade to enhance chlorophyll concentration in sesame (Sesamum indicum L.) leaves. Thirty sesame genotypes, categorized into light green (LG), middle green (MG), and deep green (DG) pigment groups based on leaf coloration, were selected from a larger pool of field-grown accessions. The investigation involved determining optimal Soil Plant Analysis Development (SPAD) value index measurements, quantifying pigment concentrations, exploring extraction solvents, and selecting suitable leaf disk positions. Significant variations in chlorophyll content were observed across genotypes, greenness categories, and leaf disk positions. The categorization of genotypes into DG, MG, and LG groups revealed a correlation between leaf appearance and chlorophyll content. The study highlighted a consistent relationship between carotenoids and chlorophyll, indicating their role in adaptation to warm environments. An examination of leaf disk positions revealed a significant chlorophyll gradient along the leaf blade, emphasizing the need for standardized protocols. Chlorophyll extraction experiments identified DMSO and 96% ethanol, particularly in those incubated for 10 min at 85 °C, as effective choices. This recommendation considers factors like cost-effectiveness, time efficiency, safety, and environmental regulations, ensuring consistent and simplified extraction processes. For higher chlorophyll extraction, focusing on leaf tips and the 75% localization along the sesame leaf blade is suggested, as this consistently yields increased chlorophyll content. Furthermore, our examination revealed significant anatomical variations in the internal structure of the mesophyll tissue leaves between deep green and light green sesame plants, primarily linked to chloroplast density and pigment-producing structures. Our findings, therefore, provide insightful knowledge of chlorophyll gradients and encourage the use of standardized protocols that enable researchers to refine their experimental designs for precise and comparable chlorophyll measurements. The recommended solvent choices ensure reliable outcomes in plant physiology, ecology, and environmental studies. Full article

Soil moisture strongly interferes with the spectra of soil organic matter (SOM) in the near-infrared region, which reduces the correlation between organic matter and spectra and decreases accuracy in the prediction of SOM. In this study, we explored the feasibility of two types of spectral indices, two- and three-band mixed (SI) and three-band spectral indices (SI3), and two water removal algorithms, direct standardization (DS) and external parameter orthogonalization (EPO), to estimate SOM in wet soils using a total of 192 soil samples at six water content gradients. The estimation accuracies of spectral indices combined with water removal algorithms were better than those of full spectral data combined with water removal algorithms: the prediction accuracies of SI-EPO (R² = 0.735, RMSEp = 3.4102 g/kg) were higher than those of EPO (R² = 0.63, RMSEp = 4.1021 g/kg), and those of SI-DS (R² = 0.70, RMSEp = 3.7085 g/kg) were higher than those of DS (R² = 0.61, RMSEp = 4.2806 g/kg); SI3-EPO (R² = 0.752, RMSEp = 3.1344 g/kg) was better than SI-EPO; both EPO and DS effectively mitigated the influence of soil moisture, with EPO demonstrating superior performance in small-sample prediction scenarios. This study introduces a novel approach to counteract the impact of soil moisture on SOM estimation. Full article

Graph anomaly detection aims to identify unusual patterns or structures in graph-structured data. Most existing research focuses on anomalous nodes in ordinary graphs with pairwise relationships. However, complex real-world systems often involve relationships that go beyond pairwise relationships, and insufficient attention is paid to hypergraph anomaly detection, especially anomalous hyperedge detection. Some existing methods for researching hypergraphs involve transforming hypergraphs into ordinary graphs for learning, which can result in poor detection performance due to the loss of high-order information. We propose a new method for Anomalous Hyperedge Detection on Symmetric Line Expansion (AHD-SLE). The SLE of a hypergraph is an ordinary graph with pairwise relationships and can be backmapped to the hypergraph, so the SLE is able to preserve the higher-order information of the hypergraph. The AHD-SLE first maps the hypergraph to the SLE; then, the information is aggregated by Graph Convolutional Networks (GCNs) in the SLE. After that, the hyperedge embedding representation is obtained through a backmapping operation. Finally, an anomaly function is designed to detect anomalous hyperedges using the hyperedge embedding representation. Experiments on five different types of real hypergraph datasets show that AHD-SLE outperforms the baseline algorithm in terms of Area Under the receiver operating characteristic Curve(AUC) and Recall metrics. Full article

Motivated by the open problems on the global dynamics of the generalized four-dimensional Lorenz-like system, this paper deals with the existence of globally exponentially attracting sets and heteroclinic orbits by constructing a series of Lyapunov functions. Specifically, not only is a family of mathematical expressions of globally exponentially attracting sets derived, but the existence of a pair of orbits heteroclinic to $S_0$ and $S_{\pm }$ is also proven with the aid of a Lyapunov function and the definitions of both the $\alpha$-limit set and $\omega$-limit set. Moreover, numerical examples are used to justify the theoretical analysis. Since the obtained results improve and complement the existing ones, they may provide support in chaos control, chaos synchronization, the Hausdorff and Lyapunov dimensions of strange attractors, etc. Full article