https://hdl.handle.net/10259/5684 Wed, 10 Jun 2026 18:13:04 GMT 2026-06-10T18:13:04Z https://hdl.handle.net/10259/11728 Dataset of the project “Use of by-products from blackberry and blueberry: charaterization, effect on health and development of safer and healthier meat products (FUNCBERRY)” Melero Gil, Beatriz; Ortega Heras, Miriam; Rovira Carballido, Jordi; Muñiz Rodríguez, Pilar; Rivero Pérez, Maria Dolores; Cavia Saiz, Mónica; Gerardi, Gisela; Gómez Bastida, Inmaculada The data set contained the raw data of the project “Use of by-products from blackberry and blueberry: charaterization, effect on health and development of safer and healthier meat products” (FUNCBERRY). Mon, 25 May 2026 00:00:00 GMT https://hdl.handle.net/10259/11728 2026-05-25T00:00:00Z https://hdl.handle.net/10259/11708 Dataset of the work “Physical-Chemical and Microbiological Characterisation of Blueberry By-products (Vaccinium myrtillus, L.) as Potential Food Ingredients” Ortega Heras, Miriam; González San José, Mª Luisa; Hortigüela Delgado, Ruth; Fernández Varona, Ángela; Rodríguez, Verónica; Melero Gil, Beatriz The dataset contained the raw data from the study entitled 'Physical-chemical and microbiological characterisation of three powdered products obtained from blueberry pomace: skins and seeds'. The analysed parameters included proximate composition, mineral content, total phenolic content, total anthocyanin content, antioxidant activity (ABTS), and individual anthocyanins and phenolic compounds. The microorganisms studied were aerobic mesophilic bacteria, Enterobacteriaceae, lactic acid bacteria, Bacillus spp. and Clostridium spp. The data also included the results of a heat treatment at 90 °C for 30, 60, 90 and 120 minutes. Mon, 25 May 2026 00:00:00 GMT https://hdl.handle.net/10259/11708 2026-05-25T00:00:00Z https://hdl.handle.net/10259/11686 DAYPSCI v1: An Event-Based Dataset of Fault Injection Scenarios in PLC-Controlled Industrial Cyber-Physical Systems Martín Fraile, Juan Vicente; Basurto Hornillos, Nuño; Sierra García, Jesús Enrique; Herrero Cosío, Álvaro The dataset contains time-series data collected from an industrial cyber-physical system (CPS) based on a PLC-controlled part marking station using Siemens S7-1200 and S7-1500 devices. Data acquisition follows an event-based logging approach, where changes in system variables are recorded together with their associated duration (Δt), enabling precise temporal characterization while reducing redundancy. In addition to temporal information, the dataset explicitly represents scan-level execution by incorporating identifiers of PLC scan cycles (scan_id) and the relative order of events within each scan (event_order). This allows accurate representation of multiple events occurring within the same control cycle and preserves the logical execution order of the system. The dataset includes both normal operation and fault conditions generated through controlled fault injection, specifically targeting sensors and actuators (e.g., solenoid valves). Ground truth labels are derived from the experimental configuration provided to the control system and embedded during data acquisition, ensuring consistency between system behavior and annotation. Data are organized into independent experimental batches, each corresponding to a specific operating condition. Each batch includes processed event-based data (CSV), raw network traffic captures in PCAPNG format, including industrial PROFINET communication traffic, and supporting documentation, enabling traceability and reproducibility. The dataset is designed to support the development, training, and evaluation of machine learning models for anomaly detection, fault classification, and industrial cybersecurity applications, while also enabling detailed temporal and logical analysis of discrete-event industrial processes. Tue, 19 May 2026 00:00:00 GMT https://hdl.handle.net/10259/11686 2026-05-19T00:00:00Z https://hdl.handle.net/10259/11498 Images_dataset_NF-UNSW-NB15-v3_1d_to_2d Villar Val, Álvaro; Martínez Fuentes, Virginia; Granados López, Diego; Arroyo Puente, Ángel; Herrero Cosío, Álvaro This dataset represents a higher-dimensional extension of the NF-UNSW-NB15 v3 dataset [Luay et al., 2025; Luay et al., 2025], in which the correlations among variables are explicitly considered and used to organize them spatially as pixels. Sun, 22 Mar 2026 00:00:00 GMT https://hdl.handle.net/10259/11498 2026-03-22T00:00:00Z