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I provide novel empirical evidence grounded in an original theoretical framework to explain why colocation matters for the rate, direction, and quality of scientific collaboration. To address endogeneity concerns due to selection into colocation and matching, I exploit the constraints imposed on the spatial allocation of labs on the Jussieu campus of Paris by the removal of asbestos from its buildings. Consistent with search costs constituting a major friction to collaboration, colocation increases the likelihood of joint research by 3.5 times, an effect that is mostly driven by lab pairs that face higher search costs ex ante. Furthermore, separation does not negatively affect collaboration between previously colocated labs. However, while colocated labs grow increasingly similar in topics and literature cited, separated ones embark on less correlated research trajectories. Research outcomes, instead, seem to be mostly influenced by how distance affects execution costs: after colocation, labs are more likely to pursue both lower-quality projects (a selection effect) and high-quality projects (an effort effect). Opposite effects on quality are observed after separation. Whereas search costs affect which scientists are likely to collaborate together, execution costs shape the quality of their output. The online appendix is available at https://doi.org/10.1287/mnsc.2017.2798 . This paper was accepted by Ashish Arora, entrepreneurship and innovation.

We develop a simple theoretical framework for thinking about how geographic frictions, and in particular travel costs, shape scientists’ collaboration decisions and the types of projects that are developed locally versus over distance. We then take advantage of a quasi-experiment—the introduction of new routes by a low-cost airline—to test the predictions of the theory. Results show that travel costs constitute an important friction to collaboration: after a low-cost airline enters, the number of collaborations increases between 0.3 and 1.1 times, a result that is robust to multiple falsification tests and causal in nature. The reduction in geographic frictions is particularly beneficial for high-quality scientists that are otherwise embedded in worse local environments. Consistent with the theory, lower travel costs also endogenously change the types of projects scientists engage in at different levels of distance. After the shock, we observe an increase in higher-quality and novel projects, as well as projects that take advantage of complementary knowledge and skills between subfields, and that rely on specialized equipment. We test the generalizability of our findings from chemistry to a broader data set of scientific publications and to a different field where specialized equipment is less likely to be relevant, mathematics. Last, we discuss implications for the formation of collaborative research and development teams over distance. This paper was accepted by Toby Stuart, entrepreneurship and innovation.

Research Summary The flow of knowledge is closely linked to proximity. While extensive works show that long‐term geographic proximity affects work behavior, little is known about the effect of short‐term colocation, such as conferences. Using participant data at Gordon Research Conferences, we estimate difference‐in‐differences and instrumental variable models, which show that attendees who have no prior within‐conference collaborations are more likely to collaborate with other attendees, and that the researchers who have worked previously with other attendees are more likely to continue their collaborations. We also find that researchers who are junior, are located closer to the conference venue, and have established prior ties to the conference draw more collaborative benefits from temporary colocation across organizations. Thus, going to a conference alters the creation of collaborations. Managerial Summary Managers face important decisions with long‐term strategic ramifications regarding where to locate offices, plants, and R&D centers, as well as how to lay out workspaces inside the firm to enhance knowledge spillover and collaboration. Permanent proximity, however, may be difficult and sometimes impossible to attain. One potential way of overcoming the distance disadvantage in knowledge spillover and tie formation is through temporary colocation events that bring together individuals from distant locations in an environment of temporary proximity. We find that individuals who attend temporary colocation events across organizational boundaries are more likely to collaborate with one another subsequently. Hence, managers of firms should pledge substantial funds for employees to participate in these events so as to impact the subsequent direction of R&D activities.

This study proposes a novel contextualized colocation analysis to examine spatial crime patterns within their social contexts. The sample includes all reported MCI crime incidents (i.e., assault, break and enter, robbery, auto theft, and theft over incidents) in the city of Toronto between 2014 and 2019 (n = 178,892). Following a stepwise clustering feature selection, we begin our analysis by regionalizing the city based on the relevant social context indicators through a ward-like hierarchical spatial clustering algorithm. Then, we use a modified colocation miner algorithm with a novel Validity Score (VS) to select significant citywide and regional crime colocation patterns. The results indicate that eating establishments, commercial parking lots, and retail food stores are the most frequent urban facilities in citywide and regional crime colocation patterns. We also note several peculiar crime colocation patterns across disadvantaged neighborhoods. Additionally, the proposed analysis selects the patterns that explain an average of 11% more crime events through the use of VS. Our study offers an alternative method for colocation analysis by effectively identifying crime-specific citywide and regional crime colocation patterns. It also prioritizes the identified colocation patterns by ranking them based on their significance.

The recent literature on the nature of persistence features a handful of imaginative cases in which an object seems to colocate with itself. So far, discussion of these cases has focused primarily on how they defy the standard endurantist approaches to the problem of temporary intrinsics. But in this article, I set that issue aside and argue that cases of apparent self-colocation also pose another problem for the endurantist. While the perdurantist seems to have a fairly straightforward account of self-colocation, the endurantist has a hard time saying exactly what it would be for an object to be self-colocated. After introducing this problem and explaining how the perdurantist can circumvent it with little difficulty, I discuss a number of tempting endurantist solutions that ultimately fail. Then I suggest an endurantist solution which I think is more promising, but which requires the endurantist to deny that apparent cases of self-colocation are genuine cases of self-colocation.

From July 2019 to January 2021, six models of PM2.5 air sensors were operated at seven air quality monitoring sites across the U.S. in Arizona, Colorado, Delaware, Georgia, North Carolina, Oklahoma, and Wisconsin. Common PM sensor data issues were identified, including repeat zero measurements, false high outliers, baseline shift, varied relationships between the sensor and monitor, and relative humidity (RH) influences. While these issues are often easy to identify during colocation, they are more challenging to identify or correct during deployment since it is hard to differentiate between real pollution events and sensor malfunctions. Air sensors may exhibit wildly different performances even if they have the same or similar internal components. Commonly used RH corrections may still have variable bias by hour of the day and seasonally. Most sensors show promise in achieving the U.S. Environmental Protection Agency (EPA) performance targets, and the findings here can be used to improve their performance and reliability further. This evaluation generated a robust dataset of colocated air sensor and monitor data, and by making it publicly available along with the results presented in this paper, we hope the dataset will be an asset to the air sensor community in understanding sensor performance and validating new methods.

Computational metagenomics has revolutionized our understanding of the human microbiome, enabling the characterization of microbial diversity, the prediction of functional capabilities, and the identification of associations with human health outcomes. This review provides a concise yet comprehensive overview of state-of-the-art computational approaches in metagenomics, alongside widely used methods and tools employed in amplicon-based metagenomics. It is intended as an introductory resource for new researchers, outlining key methodologies, challenges, and future directions in the field. We discuss recent advances in bioinformatics pipelines, machine learning (ML) models, and integrative frameworks that are transforming our understanding of the microbiome’s role in health and disease. By addressing current limitations and proposing innovative solutions, this review aims to outline a roadmap for future research and clinical translation in computational metagenomics.

In this article, we introduce a new hybrid block collocation method (NHBCM) using polynomial approximation for solving two-dimensional elliptic partial differential equations (PDEs). The theoretical analysis demonstrates that the NHBCM achieves fifth-order accuracy, highlighting its robustness in stability and convergence. We validate the effectiveness of the NHBCM through a series of test problems, showcasing its practical applications. The comparison results indicate that the NHBCM provides significantly more efficient solutions for both linear and nonlinear elliptic model PDEs than other numerical methods used for comparison, thereby validating the superior performance of the NHBCM.

Abstract This paper considers what function-if any-colocation of bodies may have in the Stoic theory of blending (κρᾶσις), by examining (1) whether colocation is part of the definition of what blending is; and (2) whether colocation is posited by the Stoics as a requirement necessary for the definition to be satisfied. I reconstruct the standard, Chrysippean definition of blending, and I show that the answer to (1) is 'no'; further, I argue that the evidence gives no reason to affirm (2). Thus, it appears that colocation does not have a central function in the Stoic theory of blending.

Background There is a sharp contradiction between the supply and demand of medical resources in the provincial capitals of China. Understanding the spatial patterns of medical resources and identifying their spatial association and heterogeneity is a prerequisite to ensuring that limited resources are allocated fairly and optimally, which, along with improvements to urban residents’ quality of life, is a key aim of healthy city planning. However, the existing studies on medical resources pattern mainly focus on their spatial distribution and evolution characteristics, and lack the analyses of the spatial co-location between medical resources from the global and local perspectives. It is worth noting that the research on the spatial relationship between medical resources is an important way to realize the spatial equity and operation efficiency of urban medical resources. Methods Localized colocation quotient (LCLQ) analysis has been used successfully to measure directional spatial associations and heterogeneity between categorical point data. Using point of interest (POI) data and the LCLQ method, this paper presents the first analysis of spatial patterns and directional spatial associations between six medical resources across Wuhan city. Results (1) Pharmacies, clinics and community hospitals show “multicentre + multicircle”, “centre + axis + dot” and “banded” distribution characteristics, respectively, but specialized hospitals and general hospitals present “single core” and “double core” modes. (2) Overall, medical resources show agglomeration characteristics. The degrees of spatial agglomeration of the five medical resources, are ranked from high to low as follows: pharmacy, clinic, community hospital, special hospital, general hospital and 3A hospital. (3) Although pharmacies, clinics, and community hospitals of basic medical resources are interdependent, specialized hospitals, general hospitals and 3A hospitals of professional medical resources are also interdependent; furthermore, basic medical resources and professional medical resources are mutually exclusive. Conclusions Government and urban planners should pay great attention to the spatial distribution characteristics and association intensity of medical resources when formulating relevant policies. The findings of this study contribute to health equity and health policy discussions around basic medical services and professional medical services.