Abstract: In the grand narrative of mathematical physics, a profound gap separates microscopic particle dynam- ics and macroscopic continuum mechanics. Hilbert’s sixth problem aims to construct the axiomatic foundation of macroscopic physical laws starting from atomism; this is not only a pursuit of mathemat- ical rigor but also an ultimate inquiry into the essential laws of the physical world. This paper provides an in-depth analysis of two milestone works in this field: the rigorous derivation of fluid equations by Deng, Hani, and Ma [1] and the constructive decomposition of kinetic equations by Chang Liu and Kun Xu [2]. The former establishes the inevitability of macroscopic laws by rigorously proving long-time convergence from hard-sphere systems to fluid equations through the introduction of a "Molecular Cutting Algorithm." The latter constructs a unified equation system traversing the entire Knudsen spectrum by introducing physical constraints under finite parameters via a "Local Dynamical Horizon." In particular, the work by Liu and Xu provides intermediate equation sets from the BGK model to the Navier-Stokes equations that vary continuously with scale, creatively solving the immense challenge of "how to establish control equations at designated scales" in multi-scale engineering calculations. This paper systematically compares these two distinct but highly complementary research paradigms from four dimensions: the height of mathematical analysis, the depth of physical modeling, the breadth of computational methods, and the width of application prospects.

Abstract: Three-dimensional concrete printing (3DPC) enables the fabrication of complex artificial coral reef structures, yet the role of binder composition in controlling mechanical anisotropy, water absorption, and alkali leaching remains insufficiently understood. This study compares two regional formulations: Mix_Vn (Vietnam, 40% fly ash) and Mix_Cn (China, 30% fly ash + 20% ground granulated blast-furnace slag, GGBS). Compressive strength was evaluated in three orthogonal orientations, water absorption was measured in tap and seawater, and pH evolution was monitored under four immersion regimes. Mix_Cn exhibited higher and more isotropic strength, reduced water absorption, and slower alkali release compared with Mix_Vn. In particular, GGBS substitution improved pore connectivity and stabilized pH near 9.0 under renewed seawater, whereas Mix_Vn exceeded pH 10.5 within two days in static tap water. These findings provide the first comparative evidence that GGBS incorporation simultaneously mitigates anisotropy and durability concerns in 3DPC, making Mix_Cn the recommended formulation for marine ecological applications and contributing to low-carbon concrete construction through substantial Portland cement replacement by industrial by-products.

Abstract: Carbimazole is a widely used medication to treat Graves disease. Acquired aplastic anemia is a rare complication that happens in less than 0.01% of people. We had a 36-year-old woman. Who is on high-dose Carbimazole . who got high-grade fever; severe menorrhagia ; spontaneous epistaxis; and pancytopenia . Her bone marrow biopsy showed severe bone marrow failure with only 5% cellularity and trilineage hypoplasia. Other potential causes were rolled out. Immediate discontinuation of Carbimazole was done; and supportive care; including blood transfusions; broad-spectrum antibiotics; G-CSF; and eltrombopag; was started. The patient deteriorated during her hospital stay; developed neutropenic sepsis and acute respiratory failure from diffuse alveolar hemorrhage; which required intubation and pulse steroid therapy. She was stabilized and discharged; with a referral to a tertiary medical center for starting antithymocyte globulin (ATG) immunosuppressive therapy. This case serves as a stark reminder of how lethal thionamide-induced bone marrow failure can be; highlighting the vital need for immediate drug cessation; swift intensive care; and thorough patient education on early warning signs.

Abstract: This study introduces a reliable portfolio optimization framework that utilizes Mean-Variance (MV) Optimization together with Kullback-Leibler (KL) divergence under the AR-GJR-GARCH filtering process for capturing non-normality, volatility clustering, and model uncertainty in the returns of financial assets. The introduced Mean-Variance-KL (MV-KL) method incorporates the maximization of expected return, risk, and proximity to investor-specific target return distributions, while increasing the efficiency and robustness of the portfolio through portfolio diversification. The MV-KL portfolio is developed based on the returns from the African and worldwide financial assets using the AR-GJR-GARCH model to extract the conditional mean and volatility processes before constructing the optimal portfolios. The portfolio evaluation metrics used include residual return, residual volatility, Sharpe and Sortino ratios, as well as VaR and CVaR. The results indicate that although the classical MV approach generates the best stable risk-adjusted returns among the other methods. The proposed hybrid MV-KL method is more diversified and provides better downside risk management than the conventional portfolio techniques. The integration of KL divergence allows superior flexibility in adapting investor preferences and improves portfolio resilience under varying market conditions. These findings add to the increasing literature on robust portfolio optimization by providing an information-theoretic approach to dynamic asset allocation.

Abstract: We develop a geometric and operationally explicit construction of correspondence rules (Bopp operators) for s-parametrized Stratonovich–Weyl phase-space symbols associated with symmetric irreducible representations of SU(d). Our main result is an intertwining procedure showing that all s-ordered Bopp operators are generated from the Husimi rules by applying continuous powers of the intertwining operator Υλ(L²). This is illustrated with the cases of SU(2) and SU(3). We show that, unlike the SU(2) case where the rules reduce to first-order vector fields, higher-rank SU(d) systems exhibit genuine higher-order differential contributions. This approach avoids cumbersome group-theoretical calculations, gives a transparent geometric interpretation of the phase-space map, and extends and complements results beyond spin systems.

Abstract: In recent years, numerous incidents and accidents have occurred in PEMEX's national pipeline system in Mexico, resulting in adverse environmental impacts and fatalities. Using an intermediate methodology for quantitative and qualitative analysis, known as consequence analysis, the risk analysis was developed based on a news article dated November 26, 2018, regarding the incident on the LPG pipeline at kilometer 2.5 of Avenida 8 de Julio, in Tlajomulco de Zuñiga, Jalisco, Mexico, caused by an illegal tap. This is because, in this event, Petroleos Mexicanos withheld information, considering it likely to compromise the actions taken, and reported only the incident. This paper analyzes the incident using a consequence analysis methodology, demonstrating how, based on the limited information available, this approach enables the analysis and evaluation of potential events. This facilitates the design and implementation of preventative controls to avoid the crucial event: an explosion followed by a fire caused by a jet fire in the pipeline. The paper identifies appropriate protective barriers and mitigation actions following the onset of the incident, as well as the environmental effects of the resulting leak, using a consequence analysis methodology, with simulations of the unwanted event in the software PHAST^â and ALOHA^â.

Abstract: Nameless is a practice-based project at the meeting of art, physics, and philosophy, built from one question: what is the simplest thing that can exist, and what does it hold? Its starting point is the smallest unit of quantum information, a single qubit whose states form a sphere. The project follows that sphere as it rings, into its vibration patterns, its linked circles of symmetry, and a chain of further structure that physics already knows, all fixed by two assumptions with nothing left to adjust. We treat this physics as material for art rather than a truth we defend, rendering it as a slowly turning sphere of light, a vibrating cavity, and a voice that answers from inside the framework. Every step is marked as proven, matched, or assumed, and that honesty is treated as part of the art. The accompanying philosophy reads the world as one distinction observing itself, so that beauty becomes the transparency of the perceiver. Because the work was made with a large language model that also speaks within it, it asks how authorship is shared between people and machines, and proposes that science, the contemplative traditions, and art circle one recognition by three roads.

Abstract: Background and Objectives: The anatomical relationship between nasal cavity dimensions and the pharyngeal airway space (PAS) in simple snoring remains poorly defined. We investigated the association between nasal cavity dimensions and the PAS in adults with simple snoring using computed tomography (CT), focusing on anatomical correlations. Methods: This study included 83 adults with habitual snoring and nasal obstruction, with a confirmed apnea-hypopnea index (AHI) < 2. Polysomnography and CT were performed to measure nasal and pharyngeal airway dimensions. The minimum cross-sectional areas (mCSAs) of three nasal cavity segments and pharyngeal airway dimensions were measured using awake CT images. Multivariate regression analyses were performed to evaluate the association between the nasal and pharyngeal parameters. Results: The smallest nasal cavity mCSA was positively associated with PAS in the overall cohort (β = 0.369, P = 0.001), with a significant association observed in males (β = 0.499, P = 0.001), but not in females. Sex-related differences were also observed in the PAS dimensions, including anteroposterior length and pharyngeal depth. Conclusions: In individuals with simple snoring, smaller nasal cavity dimensions were associated with a narrower PAS on static CT imaging, particularly in males. These findings reflect the anatomical associations and should not be interpreted as evidence of functional airway collapse or disease progression.

Abstract: This study evaluated nano-iron sulfide (nFeS) as an iron source on the bioavailability, biocompatibility, and tolerance in broilers. Broilers were allocated to the five diets: an iron-deficient basal diet (ID), the basal diet with 80 mg Fe/kg as FeSO₄, or 20, 40, or 80 mg Fe/kg as nFeS. Results showed that nFeS treatments (40, 80 mg/kg) improved average daily gain and feed conversion rate compared to ID, showed comparable or even superior effects to FeSO₄ on growth performance during 1-21 days (p < 0.05). nFeS improved whole blood Hb content and PCV percentage at day 21, while increasing serum SOD and GSH-Px activities at day 42. nFeS (40, 80 mg/kg) had or tended to deposit higher iron content in liver, spleen, duodenum and serum than FeSO₄ groups. nFeS significantly increased breast meat lightness and redness compared with the ID (p < 0.05) and showed comparable effects on postmortem pH, drip loss, and shear force relative to FeSO₄. nFeS reshaped the microbial composition in the jejunum and cecum, particularly enriching the abundance of beneficial bacteria such as Lactobacillus in the jejunum. At the dose up to 400 mg/kg, nFeS revealed no negative effects in broilers. In conclusion, nFeS is an effective iron supplement with high bioavailability and comparability, and additional benefit in shaping intestinal microbiota.

Abstract: Understanding turbulent channel flow remains a central problem in fluid dynamics, particularly in relation to near-wall structures and scaling behavior. In this work, we investigate analytical solutions of turbulent channel flow using both the classical Navier-Stokes (NS) equations and the Alexeev hydrodynamic equations (AHE), derived from the Generalized Boltzmann Equation, which accounts for non-local effects and finite collision-time dynamics. Analytical solutions are obtained under the assumption that stationary states correspond to mean flow quantities. The AHE solutions are validated against numerical results and compared with NS predictions and experimental data from multiple studies spanning Reynolds numbers from 3×103 to 3.5×107. The AHE-based solutions show consistently improved agreement with experimental velocity profiles across this wide range, while the NS-based solutions exhibit systematic deviations. The analysis reveals a new similarity parameter associated with the boundary-layer thickness, providing additional structure to turbulent scaling. A reduced formulation for the transverse velocity component yields analytical solutions that are consistent with experimental observations of secondary flows. Furthermore, coupled numerical solutions for the streamwise and transverse velocities exhibit a family of kink-type structures, which are interpreted as representations of streamwise streaks. This provides a mechanistic link between transverse velocity dynamics and the formation of coherent near-wall structures. Overall, the results offer a unified framework for mean velocity profiles, secondary flows, and streak formation in turbulent channel flow, and suggest that non-local hydrodynamic effects play an important role in wall-bounded turbulence.

Abstract: Remote sensing is essential for mapping mangrove forest ecosystems, yet accuracy and spatial resolution remain constrained, particularly in Africa, where mangroves are fragmented, reference data and cloud-free images are scarce. The state-of-the-art of mangrove forest mapping relies on native-resolution, single-date imagery and machine learning. This study evaluates deep learning methods using aggregated multi-date satellite imagery to improve mangrove mapping and national-scale area estimation. Semantic segmentation and super-resolution techniques were applied to Sentinel‑2 (S2) and Sentinel‑1 (S1) images, with training data derived from field observations and high-resolution drone and satellite imagery. Coastal regions of Tanzania and Ghana were used as representative study areas for eastern and western Africa, respectively. Results show strong classification performance, with S2 imagery alone achieving an Intersection over Union (IoU) of 85.8%. Adding S1 provided modest gains (86.3%), while super-resolution significantly improved the accuracy (88.5%). The combined super-resolved S2 and S1 dataset yielded the highest performance (89.2%). Wall-to-wall mapping and statistically rigorous validation and area estimation produced accurate results with quantified uncertainty. Tanzania showed high consistency (F1 = 96%; 1207 km², 95% CI [1151.7, 1263]), while Ghana exhibited slightly higher uncertainty (F1 = 92%; 92.6 km², 95% CI [87.5, 97.7]). Integrating deep learning with multi-date, multi-sensor fusion and super-resolution enables accurate mangrove mapping and area estimation for improved coastal management and restoration.

Abstract: As cannabis usage persists within communities following its legalization across regions globally, the aftermath of consumption raises concerns for environmental and public health as cannabinoids and their metabolites are introduced into water systems. The exploration of novel metabolites has expanded knowledge on cannabis metabolism, but the impact of these metabolites when released through bodily excretions into the wastewater system remain limited. Cannabinoids within the human body can already pose adverse effects upon consumption; these impacts are further complicated with the successful detection of metabolite residues in both surface and tap waters. Cannabis has been used recreationally and pharmaceutically for their psychoactive properties, and the rate of usage and release is expected to increase as extension of legalization make cannabis more readily accessible. Cannabis metabolites within the water system are detected using liquid chromatography paired with mass spectrometry (LC-MS) due to its reliability and specificity. Cannabinoid analysis using LC-MS is cost effective and reduces risk of heat degradation from alternatives like gas chromatography-mass spectrometry (GC-MS). The detection of cannabinoids and their metabolites utilizing primarily LC-MS methodology for monitoring consumption trends and health impacts is crucial to understanding residues from cannabinoids tetrahydrocannabinol (THC), cannabinol (CBN), cannabidiol (CBD), cannabigerol (CBG), and cannabichromene (CBC).

Abstract: The recently proposed two-component Tsallis-Hagedorn Model with Transverse Flow (THMTF) function, which is the sum of thermodynamically consistent Tsallis function with embedded transverse flow and inverse power-law function (which is asymptotic of Hagedorn function at high p_T values), has described quite well simultaneously the experimental midrapidity p_T spectra of the charged pions and kaons, protons and antiprotons in the whole measured p_T range up to 20 GeV/c at all ten multiplicity classes in proton-proton collisions at sqrt(s)=7 and 13 TeV at the LHC. Dependencies of non-extensivity parameter, q, kinetic freeze-out temperature parameter, T₀, momentum scale parameter, P₀, and power-index n of the two-component THMTF function on <dN_ch/dη> in proton-proton collisions at sqrt(s)=7 and 13 TeV have been analyzed and interpreted. Analyzing <dN_ch/dη> dependencies of parameters T₀ and <β_T>, the border <dN_ch/dη> values of transition towards plateau region of kinetic freeze-out temperature (T₀) (and simultaneous emergence of transverse flow) and probable onset of deconfinement phase transition (towards QGP-like state) have been estimated to be <dN_ch/dη>≈ 7.6±0.9 and <dN_ch/dη>≈ 9.0±1.0 in proton-proton collisions at sqrt(s)= 7 and 13 TeV, respectively. These estimates made using THMTF function in present work have been above but close to the corresponding <dN_ch/dη> ≈6.1±0.3 and <dN_ch/dη> ≈7.1±0.2 estimates of possible onset of deconfinement phase transition in proton-proton collisions at sqrt(s)= 7 and 13 TeV, respectively, made in our earlier works using Hagedorn function with embedded transverse flow. Our estimates are consistent with and complement the corresponding early result ((dN_ch/dη) ≈ 6±1) of Campanini and Ferri for probable onset of deconfinement phase transition, obtained from analyses of the experimental <p_T> versus <dN_ch/dη> curves and extracted experimental EOSs, and squared speed of sound in proton-proton and proton-antiproton collisions in wide energy, sqrt(s)= 31-7000 GeV, interval. The mean number of partons participating in a scattering, n_α=5, has been estimated from extracted average value of power-index n in the analyzed proton-proton collisions. This suggests that g+q→meson+q and g+g→meson+g gluon fragmentation reactions are the main mechanisms for high p_T meson production in proton-proton collisions at the LHC. The obtained significant differences in <dN_ch/dη> dependencies of parameters q and n for pions and kaons, on the one hand, and for (anti)protons, on the other hand, can imply that pions and kaons demonstrate features of local thermalization in proton-proton collisions at the LHC with high enough multiplicity, whereas (anti)protons show significant deviations due to non-thermal production mechanisms. The Pearson coefficients of linear correlation have been calculated between various parameters of the two-component THMTF function in proton-proton collisions at sqrt(s)= 7 and 13 TeV and compared with those obtained recently in Xe+Xe and Pb+Pb collisions at the LHC.

Abstract:

Due to the superior thermal, mechanical and chemical properties of ceramics, metallized ceramics are widely used as circuit carriers and interconnect devices wherever standard polymer-based circuit boards come to their limits. 2D metallization represents the current state-of-the-art. The metallization of 3D shaped ceramics cannot be achieved with standard metallization techniques and is still a field of research. In this study laser induced direct metallization (LDM) is applied, where a pulsed laser is used to locally activate the surface of a Cr₂O₃ doped ZTA ceramic. Subsequently a selective electroless copper plating on the laser irradiated areas is performed. Laser power, pulse repetition frequency, pulse overlap and the amount of surpasses were varied systematically in order to determine the parametric sensitivity of the ablation and metallization behavior for pulsed infrared laser structuring. It was found that ablation is necessary for the metallization and the peak fluence is the governing factor for the ablation and metallization process. It was further shown, that the ablation can be well predicted with an accumulated fluence which includes the pulse overlap. 3D ceramic substrates were successfully metallized applying an optimized set of laser parameters.

Abstract: Trimethylamine N-oxide (TMAO), a gut microbiota-derived metabolite of dietary choline and L-carnitine, has emerged as a leading molecular mediator of the gut-heart-kidney axis in heart failure (HF). Evidence from 14 prospective cohort studies demonstrates consistent associations between elevated circulating TMAO and adverse outcomes including mortality, rehospitalization, and major adverse cardiovascular events. The prognostic independence of TMAO is attenuated after renal function adjustment, reflecting both obligate renal clearance and a bidirectional relationship with kidney injury. Critically, TMAO is not modulated by conventional neurohormonal guideline-directed medical therapy (GDMT), suggesting that gut microbiome dysbiosis represents a pathophysiological axis not reached by current HF treatment. The field has evolved through three conceptual eras: TMAO as a single prognostic biomarker, TMAO as a cardiorenal mediator, and most recently, TMAO as the anchor of a multi-metabolite gut-heart signature encompassing trimethyllysine, choline, crotonobetaine, and acetyl-L-carnitine. Beyond the TMAO pathway, emerging evidence for phenylacetylglutamine, short-chain fatty acids, and protein-bound uremic toxins as parallel gut-derived cardiovascular mediators supports a multidimensional metabolite profiling approach. Panel approaches consistently outperform single-marker TMAO. Ethnic and dietary heterogeneity complicate universal threshold application. Without human interventional data demonstrating that lowering TMAO improves cardiovascular outcomes, TMAO remains a prognostic risk marker rather than a validated clinical target. Clinical translation requires resolving the renal confounding problem, validating multi-metabolite panels across diverse populations, and conducting intervention trials targeting the gut-heart-kidney axis.

Abstract: Ulcerative colitis is characterized by relapsing-remitting phases and impaired intestinal barrier integrity. Creatine supplementation ameliorates colitis severity and intestinal barrier damage; however, the mechanisms underlying its protective effects remain poorly understood. We investigated whether creatine prevents inflammation and preserves epithelial architecture and the proper expression and localization of proteins involved in intestinal barrier integrity, with attention to sex-specific effects. Using a dextran sulfate sodium-induced chronic colitis model in male and female rats, we evaluated classical readouts together with novel structural and vascular parameters. In both sexes and during both disease phases, creatine attenuated clinical symptoms and colonic damage while preventing pro-inflammatory cytokine upregulation, epithelial mucin-2 depletion, mislocalization and dysregulated expression of ZO-1, claudin-5, E-cadherin, and β-catenin, as well as alterations in endothelial caveolin-1 and plasmalemma vesicle-associated protein-1. Furthermore, creatine preserved epithelial scutoid geometry. Overall, it benefited both sexes, with greater efficacy during the active phase and more pronounced effects in males. These findings identify anti-inflammatory action and preservation of epithelial and vascular barrier integrity as key mechanisms underlying creatine-mediated protection, sustaining key parameters at normal levels throughout the active and remission phases of colitis, promoting the recovery of gut homeostasis, and supporting creatine as a safe and accessible adjuvant therapy for ulcerative colitis.

Abstract: Task package partitioning is a key step in shipbuilding. Efficient and balanced task package partitioning is a top priority for modern shipyards. The partitioning scheme is one of the crucial issues in shipbuilding. However, the multidimensional features of intermediate products—the intrinsic basis on which task units should be grouped into packages—are often overlooked in existing methods, resulting in low intra-package cohesion, high inter-package coupling, and imbalanced load distribution. To address this problem, a multi-objective optimization model is established to optimize task package partitioning. First, a three-objective model is constructed to maximize cohesion, minimize coupling, and balance the workload. Second, phase-homogeneity hard constraints and man-hour bounds are introduced to ensure engineering feasibility. Finally, a hybrid Genetic Algorithm - Branch and Bound solution framework is designed, in which global search is performed by GA and local refinement is handled by B&B. A practical case of an Hull Construction Project of 11000 DWT Bulk Carrier is used to evaluate the performance of the proposed method. Satisfactory results are achieved with effective convergence, as cohesion is improved, coupling is reduced, and workload distribution is balanced, which provides robust support for engineering decision-making.

Abstract: Bangladesh built its modern economy on human labor: ready-made garments, a large freelancing workforce, and a mostly informal jobs base. Artificial intelligence and automation now target that routine, low-wage work. This paper asks how exposed the country is, and whether its policy response matches the threat. Using a qualitative secondary-data design, it applies the Acemoglu-Restrepo task-based model of automation to peer-reviewed studies, institutional reports, and field journalism, with each headline figure cross-validated across independent sources. A 2024 factory study records an average 30.58 percent workforce reduction where automation has arrived, concentrated in cutting and sweater lines. The displacement falls hardest on women, whose share of garment work fell from 85 percent in 1991 to 57 percent in 2023. A national AI policy exists only in draft, leaving a gap between a projected 5.38 million jobs at risk by 2041 and any enacted protection. The task-based lens explains why a labor-surplus economy with weak reinstatement capacity sits in the displacement zone, and why reskilling and industrial policy will decide the outcome.

Abstract:

Native Mexican turkeys (Meleagris gallopavo gallopavo) are an important genetic resource in family-based production systems exposed to marked regional and seasonal environmental variation. This study evaluated the effects of environmental gradients shape diet composition and hematological responses of native Mexican turkeys raised in family production systems. Fifty approximately six-month-old males were evaluated in a 5 × 2 factorial design including five physiographic regions and two seasons (rainy and dry). Crop content composition, estimated dietary nutrient composition, body weight, and hematological profile were analyzed using multivariate analysis of variance, principal component analysis (PCA), and multiple regression. Grains and energy-rich by-products predominated in the diet (58.2–76.2%), whereas the dry season increased dry plant fragments and crude fiber while reducing crude protein from 17.5 to 14.3% (p < 0.001). Body weight was greatest in the Neovolcanic Axis (5.20 kg) and lowest on the Coast (4.35 kg) (p < 0.001). Erythrocyte-related variables were higher in temperate, high-altitude regions, whereas leukocyte-related variables predominated in warmer regions (p < 0.05). PCA explained 71.3% of the total variation, identifying nutritional–productive and immunological–adaptive components. Physiographic region was the main determinant of diet composition and hematological responses, whereas the dry season intensified nutritional constraints and their effects on physiological adaptation.

Abstract: Rice leaf diseases pose a major threat to crop productivity and global food security. Therefore, rapid and accurate disease diagnosis is essential for effective crop management. Despite the advancements made by deep learning algorithms in automated disease detection, the majority of current deep learning-based models are built and evaluated on single-source datasets. Therefore, the generalization capability of these models is still questionable. In order to overcome this problem, this paper presents an interpretable deep learning approach for classifying diseases in rice leaves using ConvNeXt-Tiny and Grad-CAM. The proposed semantic class normalization technique is used to harmonize the heterogeneous data classes to form a seven-class classification system. The model performance was analyzed based on two available public datasets for rice leaf disease and a combination of both. After performing five individual runs, the average classification accuracies were calculated to be 99.13±0.37%, 95.28±0.63%, and 97.27±0.41% for Datasets 1, 2, and the combined dataset, respectively. The confusion matrix analysis indicated minor misclassification errors in the form of false positives for the disease classes which have similarities in appearance. The training and validation curves showed consistent learning with minimum overfitting. Moreover, Grad-CAM analysis confirmed the focus of the model on the disease-specific regions. These results collectively show that the combination of transfer learning, semantic class harmonization, and explainable AI is a stable platform to conduct automated rice disease detection. It is evident from these outcomes that reliable performance can be achieved even under heterogeneous imaging conditions. Consequently, there exists great potential for this approach in agricultural decision-support systems.