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The Lemon Leaf Disease Dataset is a comprehensive collection of 1,238 high-quality images of lemon tree leaves, systematically gathered from Munshi Bazar in Kamalganj Upazila, Moulvibazar District, Bangladesh, between July 3 and July 7, 2025. This dataset consists of eight distinct classes: Bacterial_Canker (216 images), Bacterial_Spot (241 images), Citrus_Leafminer (42 images), Curl_Virus (128 images), Deficiency_Leaf (100 images), Dry_Leaf (129 images), Healthy_Leaf (267 images), and Leaf_Spot (115 images), capturing various healthy and diseased conditions of lemon leaves. The images were captured using a Realme 6i smartphone in natural lighting conditions, ensuring high resolution and clarity. The original images, taken in JPG format at a resolution of 4000 × 3000 pixels, were later resized to 640 × 480 pixels at 72 dpi to standardize the dataset. Although the dataset does not include annotations, it serves as a valuable resource for researchers and machine learning practitioners working on plant disease detection and classification. This dataset is particularly relevant for applications in precision agriculture and automated plant pathology, where early diagnosis and leaf health monitoring can significantly improve crop management strategies.

This dataset “Lake_DOS_data” contains the original data of all the figures in the submitted article “Comparative Analysis of Dissolved Organic Sulfur (DOS) Molecular Signatures in Three Large Freshwater Lakes with Contrasting Hydrological Connectivity to the Changjiang River” .

the data of the SSCE article . Please use matlab2021b to use the data and code.

This data is raw data about "Phosphorylation of Hemocyanin at S293 Activates p38 MAPK Signaling to Induce Antimicrobial Peptides in Penaeus vannamei"

Main R code (GLMM analyses) and data for the project: "Altruistic punishment in action: movement vigor in neuroeconomic choice"

The data published here are solar wind parameters, geomagnetic indices, TEC data and Model data (TIE-GCM, CTIP, PPEEFM) . These data have been used to study geomagnetic storm of April 23-24, 2023.

The dataset contains Python scripts connected with estimation of Lyapunov Exponents with use of Automatic Differentiation. They show that: a) Automatic Differentiation (AD) can be successfully applied in Lyapunov Exponents (LEs) estmination; b) AD approach is slighlty less accurate then the one based on the variational equation; c) AD approach is less efficient then the one based on the variational equation for small systems, but more effective for large ones.

This is testdata use to benchmark and validate our Edit-o-Matic genome editing software.

The strength of additively manufactured ceramics may depend on the orientation of the direction in which tensile stresses act during testing with respect to the building direction (z). This may be due to ─ specific properties of the interfaces between the deposited layers ─ aliasing effects on surfaces ─ others In order to address this characteristic behaviour together with other aspects relevant to ceramics and the additive manufacturing process, we aim at: ─ providing a test piece geometry with dimensions relevant to a specific ceramic AM method that can be manufactured in different orientations with respect to the building direction z. ─ providing 30+ individual test pieces for a statistical strength analysis produced in a time-efficient single print job ─ providing test pieces with prospective tensile loaded faces that are neither the faces attached to the building platform during manufacturing nor the last printed layer ─ providing test pieces with prospective tensile loaded faces that are not in contact with kiln furniture during thermal processing A test specimen suitable for strength testing of additively manufactured ceramics is presented. A specimen consists of 48 test pieces in the form of carefully designed constant-moment cantilever beams which are attached to a baseplate. The baseplate is formed by two connected solid plates with a specified angle (ꞵ) in between. By variation of this angle, different orientations of the cantilever axis (prospective tension-loaded face) with respect to the building direction of the AM process can be achieved. *.stl files for specimens with three different orientations/configurations are provided. Strength testing is performed by loading each cantilever at a pre-defined loading point (A) to failure. A description of the testing method as well as a detailed error analysis is provided in https://doi.org/10.1016/j.oceram.2023.100410 An example of how this specimen can be used to evaluate the strength of LCM ceramics can be found in https://doi.org/10.1016/j.oceram.2024.100557

In this study, we demonstrate that the addition of Als5pFP promotes biomass accumulation in C. albicans biofilms under standard laboratory conditions, including in complex media and at temperatures compatible with clinical biofilm assays. Using advanced image analysis of microscopy images, we show that Als5p peptide induces a distinct morphological effect on biofilms: a sharpening of microcolony structures, characterized by the concentration of fungal cells into denser aggregates and the reduction of cells in intermediate spaces. These observations suggest a potential role for amyloid-like fibrils formed by Als5p peptide in influencing the spatial organization of C. albicans biofilms. Our findings contribute to the understanding of the architectural development of C. albicans biofilms and provide a foundation for future research aimed at targeting amyloid structures within fungal biofilms. Furthermore, the results may support the design of biofilm-targeting antifungal agents and the development of biosensors for monitoring amyloid formation during infection.