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Repository dei dati relativi alle pubblicazioni dell'UO2 (Ospedale San Raffaele) inerenti al progetto PNRR-MAD-2022-12375859 "Inflammation and depression: a multidisciplinary approach to dissect pathogenetic mechanisms in the onset, comorbidity, and treatment response".

**Dataset Description** This dataset contains parallel Bangla and English sentence pairs collected and processed for language translation and linguistic research. The Bangla corpus includes sentences written in both **Cholito Bangla** (colloquial form) and **Sadhu Bangla** (classical/formal form), extracted from Bangla literary sources. Each sentence is labeled according to its linguistic style and paired with an English translation. The dataset consists of the following fields: * **sentence**: The sentence text (Bangla or English, depending on the dataset version). * **label**: Linguistic style label (`cholito` or `sadhu`). * **source**: Source category of the text (`Book`). Data preprocessing included sentence segmentation using Bangla punctuation markers, removal of noisy OCR artifacts, duplicate elimination, and dataset validation. The English version was generated through machine translation and aligned with the original Bangla sentences. The dataset is intended for research and development in: * Machine Translation (Bangla–English) * Natural Language Processing (NLP) * Text Classification * Style Transfer * Bangla Linguistic Analysis * Large Language Model (LLM) Training and Evaluation The dataset was randomly shuffled and split into training and testing subsets using a 70:30 ratio while preserving sentence alignment between the Bangla and English versions.

The public analysis panel (Compustat raw fields stripped, firm IDs anonymized), the derived exposure files, a data dictionary, the replication code (re-pathed to run from the package), the figures, a README, and a manifest. No licensed fields leaked. Now the data dictionary, README, and manifest.

This dataset supports a bibliometric systematic literature review (SLR) of peer-reviewed research on port waste management and port reception facilities (PRFs) published between 2000 and 2025. It provides the bibliographic corpus, the reference list, and the per-article thematic classification used in the study, so that the descriptive bibliometrics, the keyword co-occurrence analysis, and the thematic synthesis can be independently verified and reproduced.

Replication package for the paper "Branches Without Intermediation: The Regional Economic Effects of Public Participation Banks in Türkiye" (submitted to Borsa İstanbul Review). The paper estimates, with a heterogeneity-robust staggered difference-in-differences design (Callaway and Sant'Anna, 2021), the effect of the provincial rollout of Türkiye's three state-owned participation (Islamic) banks, Ziraat Katılım (2015), Vakıf Katılım (2016), and Emlak Katılım (2019), on provincial real GDP per capita and on a range of financial and real-economy outcomes. The headline result is a precise null on real GDP per capita, with a mechanism ("branches without intermediation") that accounts for it. This package contains two hand-collected datasets that are its original contribution: (1) the province-level branch rollout of the three public participation banks, parsed from 23 bank annual reports; and (2) the three banks' annual balance sheets (financing, funds collected, securities). These are combined with a province-quarter banking panel built from the BDDK FinTürk system and with public macroeconomic, demographic, satellite, firm-registry, employment, and election series to form the constructed province-year and province-quarter estimation panels. The complete Python and R code reproducing every number, table, and figure is included. All reported results, tables, and figures reproduce from the committed processed panel (data/processed/panel_did.csv); the raw third-party inputs are not required. Third-party series (BDDK FinTürk, TÜİK, VIIRS nighttime lights, TOBB, SGK, YSK) are publicly available from their original providers and documented in the README. The original bank annual-report PDFs are not redistributed for copyright reasons; the README states where to obtain them. Data are released under CC BY 4.0 and code under the MIT License. See README.md for a full file manifest, variable dictionaries, software requirements, the run order, and a script-to-table/figure map.

This is supplementary material for an RCT comparing between 3 day and 7 day wear protocol for aligners

This dataset contains genomic and experimental data of Bacillus cereus BT-C2.4 isolated from aquaculture water in Ben Tre province, Vietnam. The dataset includes genome assembly file (.fasta) and experimental amoxicillin degradation data obtained by HPLC. Residual antibiotic concentrations and degradation efficiency (%) were measured over time, showing complete degradation within 24 hours. These data support studies on antimicrobial resistance, antibiotic biodegradation, and environmental microbiology in aquaculture systems.

This dataset contains the complete data and analytical outputs used in the study of sediment source fingerprinting in the Alvand karst catchment, western Iran. Three Excel files are provided, representing the geochemical oxides, weathering indices, and combined tracer datasets. Each file includes the raw geochemical data, calculated weathering indices (where applicable), conservative tracer testing, Kruskal–Wallis screening, stepwise discriminant function analysis (DFA), final composite fingerprint selection, Modified MixSIR Bayesian source apportionment results, and virtual mixture validation outputs. These datasets provide full transparency and reproducibility of the tracer selection, source discrimination, and sediment source contribution analyses presented in the manuscript.

Experimental Evidence using cRCT on Resource Constraints in Community-Based Mangrove Restoration

Published in March 2023, Poesie dalla Macchina Pensante represents one of the earliest—and arguably the first—Italian books of illustrated poetry created with a new-generation generative AI system. Developed through a collaboration between Gabriele Moschin, Andrea Filippi, ChatGPT, and DALL·E, the project combines AI-generated poems with AI-generated images, documenting a pivotal moment in the emergence of computational creativity. Rather than concealing the limitations of early generative models, the book embraces their unexpected associations, semantic shifts, and imaginative anomalies as poetic material. Today, it can be read both as an artistic experiment and as a historical document of the first wave of generative AI, anticipating subsequent debates on authorship, creativity, and human–machine collaboration.