Mendeley Data Showcase

The SpaPhish dataset is a Spanish-language email corpus created under the hypothesis that phishing detection in Spanish benefits from (i) native-language message content and (ii) explicit, human-validated psychological annotations that make social-engineering tactics measurable and interpretable. The data provides both the linguistic surface (email subject and body) and message-level technical indicators commonly associated with email abuse, enabling joint analysis of what the message says and how it is technically packaged. SpaPhish contains 1,463 hashed message records; 1,457 of them include a valid binary class label encoded as 000/001 (distribution: 001 = 780, 000 = 677). Each record includes: (a) a unique hash, (b) subject, body, and date when available (dates span 2014-06-07 to 2025-10-27 in the current file), and (c) extracted technical fields such as url_count (plus the URL list), hops_count, and attachment descriptors (attachments_count, types, and sizes). Notable corpus-level observations from the labeled subset are that 85.6% of messages contain at least one URL (url_count>0), attachments are present in 18.4% of messages (attachments_count>0), and hop counts are typically small (median hops_count = 3). A distinctive component of SpaPhish is its psychological layer: for each message, three independent annotators (_A, _B, _C) provide binary presence labels (000/001) for five persuasion principles reflected in the schema: authority, social_proof, liking/similarity deception, commitment/integrity/reciprocation, and distraction, along with free-text justifications (justif_*) documenting the rationale for each judgment. In addition, consolidated (non-suffixed) columns provide an aggregated label per principle intended for benchmarking and downstream modeling. To use the dataset correctly, consumers should treat the per-annotator labels as the primary evidence, use the consolidated labels as a convenience layer, and filter out the small fraction of records that contain non-binary placeholders in some annotation fields.

This dataset contains a high-quality and visually diverse collection of jackfruit (Artocarpus heterophyllus) leaf images captured from real agricultural fields in Savar and Rajbari, Bangladesh. It includes eight well-defined classes—Blight, Dried, Fungal_Spot, Healthy, Leaf_Miner, Pest_Damage, Senescence, and Young—covering major disease conditions and leaf growth stages.To increase data diversity and reduce class imbalance, various image augmentation techniques were applied consistently across all classes. These include horizontal flipping, rotation, zooming, random cropping, and brightness adjustment with random combinations per image.The dataset also provides a CSV metadata file with image names and labels details.It is suitable for machine learning and deep learning tasks such as disease detection, growth-stage classification, and intelligent crop health monitoring, supporting precision agriculture and sustainable jackfruit cultivation. Dataset Classes and Image Counts: Blight:1000 images Dried:1000 images Fungal_Spot:1000 images Healthy:1000 images Leaf_Miner:1000 images Pest_Damage:1000 images Senescence:1000 images Young:1000 images Total: 8,000 images Image Details: Original image resolution:3072 x 4096 Resized image resolution:512 x 512 Image format: JPG Color mode: RGB Collection device: Smartphone camera Location: Savar and Rajbari districts, Bangladesh

NOTE: The Dataset For TrOCR Is Available In HuggingFace NusaAksara https://huggingface.co/datasets/NusaAksara/NusaAksara/viewer/Image%20Transcription%20(OCR)/train?f%5Bscript%5D%5Bvalue%5D=%27jawa%27&views%5B%5D=image_transcription_ocr This data is a combination of data for TrOCR Text Transcription of Jawa Aksara from NusaAksara, and A collection data for YOLOv8 manually created and annotated from Robflow consisting of document images from NusaAksara Jawa Aksara Image Segmentation Dataset, and Single page images of historical documents from The British Public Library: Endangered Archives Program. Link To NusaAksara (OCR Transcription): https://huggingface.co/datasets/NusaAksara/NusaAksara/viewer/Image%20Transcription%20(OCR)/train?f%5Bscript%5D%5Bvalue%5D=%27jawa%27&row=4707&views%5B%5D=image_transcription_ocr Link To NusaAksara (OCR SEGMENTATION): https://huggingface.co/datasets/NusaAksara/NusaAksara/viewer/Image%20Segmentation/train?f%5Blanguage%5D%5Bvalue%5D=%27Jawa%27&views%5B%5D=image_segmentation Link EAP: https://eap.bl.uk/search

Original Immunoblot source images in the paper "ICAM1 mRNA entraps ILF2/ILF3 to inhibit transcription of EIF4E and global protein synthesis ". Cropped regions used in the published figure are indicated on the image.

This dataset documents Informal Recyclable Waste Aggregators (IRWAs) in Hanoi, Vietnam, with a specific focus on their spatial distribution, socio-demographic characteristics, and physical/architectural attributes, and with a distinction between urban and rural contexts. Data were collected through field surveys and on-site observations, where applicable. The dataset comprises 975 individual IRWA facilities, each represented as a single observation. A total of 14 variables are included, organized into four main categories: 1. Identification and spatial classification - ID_IRWA_Hanoi: Unique identifier for each IRWA facility - Classification: Urban or rural classification of the facility location, determined based on the official status of wards (urban) and communes (rural) as defined by the 2025 administrative reorganization of Hanoi under the two-tier local government structure. 2. Socio-demographic characteristics - Gender: Gender of the owner - Age: Age group of the owner - Hometown: Province or city of origin of the owner - Residence: Whether the owner lives on-site or elsewhere 3. Temporal characteristics - EstablishmentPeriod: Period during which the facility was established 4. Physical and architectural characteristics - Material_Tarpaulin: Use of tarpaulin in the structure - Material_Sheet_FibreCement: Use of sheet metal or fibre cement - Material_Brick: Presence of brick construction - Material_Beton: Presence of reinforced concrete - GroundArea: Approximate ground area category of the facility - Storage: Estimated storage surface area - Mezzanine: Presence or absence of a mezzanine level Values recorded as “N/A” indicate cases where the information could not be obtained through field surveys or on-site observations.

Dataset used in the empirical analysis.

Soil samples were collected from 90 sites around southwest alpine plateau of China

Expression of miRNAs in Diffuse axonal injury

Osteoporosis (OP) is a common metabolic bone disease marked by decreased bone density and impaired bone structure. Conventional therapeutic strategies for OP restricted due to their non-specific targeting and long-term toxicity. Leveraging the gut-bone axis, we developed an engineered bacterial extracellular vesicle (BEV) delivery system derived from probiotic Akkermansia muciniphila (AKK). These BEVs were engineered with a bone-targeting peptide (SDSSD) to generate BT-AKK-EVs. Through miRNA sequencing and functional experiments, we identified miR-21-5p as a pivotal effector molecule enriched within AKK-EVs. Mechanistically, BT-AKK-EVs delivered miR-21-5p to promoting osteogenic differentiation while simultaneously inhibiting osteoclastogenesis via activation of the PI3K-AKT signaling pathway. Systemic administration of BT-AKK-EVs in ovariectomized mice resulted in their robust accumulation in bone tissues, significantly alleviating bone loss. This study establishes engineered probiotic BEVs as a safe and efficient platform for targeted bone therapy and elucidates a concrete molecular mechanism of gut-bone communication through vesicle-packaged miRNA, offering a transformative strategy for treating metabolic bone disorders.

Data, code, and rendme files for Economic Modelling