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The significance of university-industry collaboration becomes even more pronounced within the pharmaceutical R&D context. Such collaborations provide a platform to address potential challenges by offering access to cutting-edge research, specialized facilities, and expertise. Collaborative models, such as multi-university partnerships and university-industry contract research, have emerged as viable methods to support innovation in the pharmaceutical industry. Such collaborations have facilitated universities in accessing invaluable resources from their industrial counterparts, while industries have benefited from enhanced technological capabilities and foundational scientific knowledge. This symbiotic relationship not only benefits the primary stakeholders but also has broader societal implications, as it accelerates the transfer of scientific results to the market. This research adopts a broad definition of pharmaceutical university-industry R&D collaboration. The primary objective is to gain insights to answer the overarching question: How to manage innovation in pharmaceutical university-industry R&D practices? To answer this, the present research employs both quantitative (Chapters 2 and 3) and qualitative (Chapters 4 and 5) methodologies, with a multi-level analysis encompassing landscape- (Chapter 2), collaboration- (Chapter 3), university- (Chapter 4), and company (Chapter 5) perspectives. Based on the landscape perspective, Chapter 2 uses a bibliometric approach to analyze historical and emerging topics in the pharmaceutical UIC R&D context. The study identifies a rise in related publications, emphasizing the research’s importance. The comprehensive review categorizes publications into three levels that are industrial and organizational innovation strategy, -structure, and -culture. The chapter advocates for broader engagement by academic and commercial entities, emphasizing the potential of R&D alliances in the pharmaceutical industry, where university-industry collaborations are particularly promising. Chapter 3, using Neglected Tropical Diseases as the focal point, delves into whether the type of PPPs influences the initiation and duration of NTD-related clinical trials. The research identifies various collaborative types, among which NGO- and public sector-led collaborations are the major subtypes. Key determinants shaping these collaborations encompass scientific, logistical, political, and financial aspects. The chapter emphasizes the pivotal role companies play in combating NTDs, either independently or within public-private partnerships. The identified characteristics and determinants provide suggestions for practitioners to further optimize R&D strategies. Chapter 4 delves into the micro-foundations of dynamic capabilities within the university technology transfer process, drawing from empirical cases of the Industry Alliance Office and the Demonstrator Lab. For sensing capabilities, this chapter underscores the importance of timely identification of opportunities through internal competencies and external partnerships. On the seizing front, the research highlights the critical role of universities in aligning with industrial entities to maximize detected opportunities, emphasizing resource co-allocation and collaborative business models. Reconfiguring capabilities are important for universities to position themselves as central orchestrators within the broader of university-industry ecosystem. It is also important for partnering companies and academic entrepreneurs to employ dynamic capabilities with the aim of academic entrepreneurship. Chapter 5 delves into the micro-foundations of dynamic capabilities essential for academic entrepreneurship within the university-industry ecosystem. It emphasizes that sensing capabilities empower them to strategically allocate resources and address potential challenges. The chapter also underscores the significance of seizing capabilities in facilitating knowledge integration and partnership management. To ensure sustained innovation, it is important for high-tech enterprises to develop reconfiguring capabilities. To further research pharmaceutical UIC R&D innovation management, Chapter 6 then puts forward various recommendations to different stakeholders including universities, research institutes, startup companies, and regulatory agencies. Chapter 6 also adds some of the limitations of Chapters 2-5, based on which the present research hopes to provide some suggestions for future research.

What role do scents and olfaction play in heritage practices? What are the values connected to historical smells and olfactory practices? The Odeuropa project, in collaboration with cultural heritage institutes and communities, has compiled a list of value statements related to olfactory heritage. These statements can be used by heritage professionals to capture the significance of scents as part of cultural heritage, or to support heritage communities to recognize the role of smell in heritage practices. They can also support GLAMs to capture the added value of working with smells in a heritage context. The value statements can be integrated in questionnaires and interviews.

This resource presents an overview of intangible cultural heritage practices in which smells plays or can play a significant role. The list is compiled to support cultural heritage policy makers to identify the significance of olfactory heritage and help heritage communities to acknowledge the value of olfaction in heritage practices. The information is compiled by the Odeuropa project in collaboration with the Dutch Centre for Intangible Cultural Heritage (DICH), the Smell of Heritage group of University College London and the KNAW Meertens Institute.

This is a dataset on 460,452 individuals employed by the Dutch East India Company (Verenigde Oost-Indische Compagnie, VOC) in the seventeenth and especially the eighteenth centuries, developed from 774,200 muster records in the ‘VOC-opvarenden’ collection. The original data has been enhanced through the disambiguation of individual records, the standardization of 44,152 unique place names, and the addition of wage details and rank structure. This collection includes the original ‘VOC-opvarenden’ dataset (comprising three files), enriched files (totaling nine), integrated external data, and Jupyter notebooks documenting the transformation from original to enriched datasets. The accompanying data paper provides an in-depth overview of the original dataset, the enhancement process, and potential applications. Additionally, it features appendices serving as codebooks, offering concise descriptions of each variable present in the enriched data files. Enabling research into career patterns, network structures, and migration trends, this resource is of significant value to the study of early modern history, social and economic history, and sociology.

These slides were presented at the HS Academy workshop titled "Working Group on Research Infrastructures and Heritage Science Career Paths," organized jointly by the IPERION HS and E-RIHS projects. The presentation was held in Bologna on January 25, 2024.

This dataset contains 206 spatially explicit environmental variables, also termed covariates, at 25m resolution that cover the entire Netherlands (national scale). The raster data are comprised of covariates related to the soil-forming factors (climate, organism/land use/land cover, relief/topography, parent material/geology) for the purpose of using them for digital soil mapping. However, since the covariates cover a wide range of environmental variables, they can potentially be used for spatial modelling in the Netherlands also outside the field of soil science. All covariates can also be found from the original source, but the potential strength and practicality of this dataset lies in the broad range of readily available, collected, prepared and harmonized raster data.The metadata of all the covariates in this dataset can be found in the "00_covariates_metadata.csv" file, including information about the names, category, value types, specific value types, type of geospatial data, file type, whether its static or dynamic, temporal coverage, date/version, resolution (all 25m), origin, source, access/license, description, processing steps and comments. The dataset includes 3 different types of files:GeoTIFF (.tif): the covariates as raster data at 25m resolution in the EPSG:28992 (Amersfoort / RD New) spatial projectionText (.txt): README files for each covariate with additional metadata information (filename ending in "_readme.txt")Tabular data (.csv): Classification and re-classification table for categorical covariates (filename ending in "_reclassify.csv")Note that the reclassification tables contain potential ways to reclassify the data provided, but can be altered by the user. Reclassification may be useful for categorical covariates with a large number of classes/categories. Note that covariates with CC BY-ND 4.0 licenses, covariates that are not open data or for which the license was unknown are not shared in this dataset.More information about these covariates can be found in the associated scientific paper "BIS-4D: Mapping soil properties and their uncertainties at 25m resolution in the Netherlands" (Helfenstein et al., 2024, under review). Different ways of pre-processing and preparing the covariates for subsequent modelling can be found in R scripts 20-25 in the associated code repository on GitLab. This includes assembling and preparing covariates using GDAL ("20_cov_prep_gdal.R"), computing digital elevation model (DEM) derivatives using SAGA GIS ("21_cov_dem_deriv_saga.R"), deriving spectral indices from RGBNIR bands of Sentinel 2 images ("22_cov_sensing_deriv.R"), preparing categorical covariates using GDAL ("23_cov_cat_recl_gdal.R"), deriving dynamic covariates ("24_cov_dyn_prep_gdal.R") and exploratory analysis of the covariates ("25_cov_expl_analysis_clorpt.Rmd", "25_cov_expl_analysis_cont_cat.Rmd").

Presentation "Bringing Realistic Stratigraphy into Evolutionary Biology through Age-Depth Modeling" held at the "Stratigraphy in Modern Geoscience: methodologies, applications and future relevance" meeting London, 23rd of January 2024) organized by The Geological Society. Abstract text: The stratigraphic record allows observation of fossil evolution over longer time scales than are accessible to direct human observation. However, direct dating of fossils in deep time is impossible, making it necessary to estimate their age from indirect methods. The age inference is complicated by stratigraphic effects such as changing sedimentation rates and hiatuses. Age-depth models assign chronological ages to stratigraphic positions, thus establishing a temporal framework for the fossils they contain, but are themselves dependent on stratigraphic architectures. A robust understanding of these architectures is fundamental for establishing realistic, accurate age-depth models, and reconstructing evolutionary change from the fossil record. We present a novel mathematical framework for age-depth modeling implemented in the R software. It includes two non-parametric methods to estimate age-depth models from complex stratigraphic data and to quantify the associated geochronological uncertainties. In contrast to other age-depth modeling frameworks, it allows to directly transform complex data structures and mathematical objects such as phylogenetic trees and time series from the time domain to the stratigraphic domain and vice versa. As examples of the developed framework, we 1. construct age-depth models for Devonian strata in the La Thure section, Belgium, using sedimentation rates constrained by cyclostratigraphic methods. 2. use measurements of extraterrestrial 3He from ODP site 960 (Maud Rise, Weddell Sea) to construct age-depth models for the Paleocene–Eocene thermal maximum. 3. examine the preservation of phylogenetic relationships along the onshore-offshore gradient in a carbonate platform simulated in the CarboKitten model. The presented framework simplifies the interface between stratigraphy and other domains of science, making it easier for communities outside of sedimentology to understand and use stratigraphic information in inter-disciplinary approaches. It demonstrates that a modern, model-driven understanding of stratigraphy is highly relevant to all disciplines drawing information from geohistorical records.

Seventeenth- and eighteenth-century artist biographers documented the mobility of early modern Netherlandish artists. Yet, research into the movements of Dutch and Flemish artists still fails to capture the full significance of this essential aspect of the artistic profession. This article presents a novel approach to artist mobility, by applying Michael Baxandall's interpretation of the artwork as “a solution to a problem” to a selection of artworks by Northern artists in late-sixteenth- and seventeenth-century Naples. By analyzing itinerant artists’ abilities to solve the challenges they faced as foreigners in the Spanish Viceroyalty, this study offers new insights into their creativity. INTRECCI d'arte, No. 12 (2023): Storie dell'arte dai mondi iberici: materiali, problemi, geografie