Funder Network: Evaluating the Pilot Knowledge-Sharing Website

In 2011, the Association of Charitable Foundations (ACF), New Philanthropy Capital (NPC), and the City Bridge Trust ran a six-month pilot project to improve learning and knowledge-sharing among funders. This report presents an evaluation

Abstract Urbanism

One of the first computational models of cities was Thomas Schelling’s “Models of Segregation” in this, and related papers of around the same period (1969-71), he attempted to provide a logical model for understanding the dynamics of racial segregation in north American cities and laid much of the groundwork for what later became agent-based modeling.1 Such work is expressed contemporarily for instance in the work of J.M. Epstein and others in the area of computational social modeling.2 Although Models of Segregation did not at first use a computer, it sets up some of the basic characteristics of the field. We use this work as a starting point to think about the relationship between urban morphologies and the politics of models on the one hand and the way in which, with the increasing and multiform kinds of merger between computational systems, models, and city forms, what it means to live in a model

An Evolutionary Method for the Minimum Toll Booth Problem: the Methodology

This paper considers the minimum toll booth problem (MINTB) for determining a tolling strategy in a transportation network that requires the least number of toll locations, and simultaneously causes the most efficient use of the network. The paper develops a methodology for using the genetic algorithm to solve MINTB and presents the algorithm GAMINTB. The proposed method is tested and validated through a computational study with six example networks. Additional numerical test discovers some interesting properties for the proposed method, and provides guidelines for further application of the GAMINTB

Temperature dependent absorption cross-sections of HNO3 and N2O5

Absorption cross-sections for HNO3 and N2O5 have been measured in the wavelength region 220-450 nm, using a dual beam diode array spectrometer with a spectral resolution of 0.3 nm. The results for both compounds are in good agreement with recommended values at room temperature. However, the cross-sections of both HNO3 and N2O5 show a marked reduction with decreasing temperature in the range 295-233 K. The calculated photolysis rate of HNO3 at the low temperatures and high solar zenith angles characteristic of the polar winter and spring is significantly lower than previously estimated

Heterogeneity in Surface Sensing Suggests a Division of Labor in Pseudomonas aeruginosa Populations

The second messenger signaling molecule cyclic diguanylate monophosphate (c-di-GMP) drives the transition between planktonic and biofilm growth in many bacterial species. Pseudomonas aeruginosa has two surface sensing systems that produce c-di-GMP in response to surface adherence. Current thinking in the field is that once cells attach to a surface, they uniformly respond by producing c-di-GMP. Here, we describe how the Wsp system generates heterogeneity in surface sensing, resulting in two physiologically distinct subpopulations of cells. One subpopulation has elevated c-di-GMP and produces biofilm matrix, serving as the founders of initial microcolonies. The other subpopulation has low c-di-GMP and engages in surface motility, allowing for exploration of the surface. We also show that this heterogeneity strongly correlates to surface behavior for descendent cells. Together, our results suggest that after surface attachment, P. aeruginosa engages in a division of labor that persists across generations, accelerating early biofilm formation and surface exploration

A Transfer Learning-Based Framework for Classifying Lymph Node Metastasis in Prostate Cancer Patients

Background: Prostate cancer is the second most common new cancer diagnosis in the United States. It is usually slow-growing, and when it is low-grade and confined to the prostate gland, it can be treated either conservatively (through active surveillance) or with surgery. However, if the cancer has spread beyond the prostate, such as to the lymph nodes, then that indicates a more aggressive cancer, and surgery may not be adequate. Methods: The challenge is that it is often difficult for radiologists reading prostate-specific imaging such as magnetic resonance images (MRIs) to differentiate malignant lymph nodes from non-malignant ones. An emerging field is the development of artificial intelligence (AI) models, including machine learning and deep learning, for medical imaging to assist in diagnostic tasks. Earlier research focused on implementing texture algorithms to extract imaging features used in classification models. More recently, researchers began studying the use of deep learning for both stand-alone feature extraction and end-to-end classification tasks. In order to tackle the challenges inherent in small datasets, this study was designed as a scalable hybrid framework utilizing pre-trained ResNet-18, a deep learning model, to extract features that were subsequently fed into a machine learning classifier to automatically identify malignant lymph nodes in patients with prostate cancer. For comparison, two texture algorithms were implemented, namely the gray-level co-occurrence matrix (GLCM) and Gabor. Results: Using an institutional prostate lymph node dataset (42 positives, 84 negatives), the proposed framework achieved an accuracy of 76.19%, a sensitivity of 79.76%, and a specificity of 69.05%. Using GLCM features, the classification achieved an accuracy of 61.90%, a sensitivity of 74.07%, and a specificity of 42.86%. Using Gabor features, the classification achieved an accuracy of 65.08%, a sensitivity of 73.47%, and a specificity of 52.50%. Conclusions: Our results demonstrate that a hybrid approach, i.e., using a pre-trainined deep learning model for feature extraction, followed by a machine learning classifier, is a viable solution. This hybrid approach is especially useful in medical-imaging-based applications with small datasets.This work was supported by the Mayo Clinic Center for Individualized Medicine.Mayo Clinic Center for Individualized Medicin

Microplastic burden in invasive signal crayfish (Pacifastacus leniusculus) increases along a stream urbanization gradient

Microplastics are a globally pervasive pollutant with the potential to directly impact species and accumulate in ecosystems. However, there remains a relative paucity of research addressing their accumulation in freshwater ecosystems and a near absence of work in crayfish, despite their high ecological and economic importance. This study investigated the presence of microplastics in the invasive signal crayfish Pacifastacus leniusculus along a stream urbanization gradient. The results demonstrate a ubiquitous presence of microplastics in crayfish digestive tracts at all sites and provide the first evidence of microplastic accumulation in tail tissue. Evidence of a positive linear trend was demonstrated between microplastic concentration in crayfish and upstream urban area size in generalized linear models. Evidence for a positive effect of the upstream urban area and a negative effect of crayfish length on microplastic concentrations in crayfish was demonstrated in multiple generalized linear regression models. Our results extend the current understanding of microplastics presence in freshwater ecosystems and demonstrate their presence in crayfish in the wild for the first time

Timing and Nature of the Deepening of the Tasmanian Gateway

Tectonic changes that produced a deep Tasmanian Gateway between Australia and Antarctica are widely invoked as the major mechanism for Antarctic cryosphere growth and Antarctic Circumpolar Current (ACC) development during the Eocene/Oligocene (E/O) transition (∼34–33 Ma). Ocean Drilling Program (ODP) Leg 189 recovered near-continuous marine sedimentary records across the E/O transition interval at four sites around Tasmania. These records are largely barren of calcareous microfossils but contain a rich record of siliceous- and organic-walled marine microfossils. In this study we integrate micropaleontological, sedimentological, geochemical, and paleomagnetic data from Site 1172 (East Tasman Plateau) to identify four distinct phases (A–D) in the E/O Tasmanian Gateway deepening that are correlative among ODP Leg 189 sites. Phase A, prior to ∼35.5 Ma: minor initial deepening characterized by a shallow marine prodeltaic setting with initial condensation episodes. Phase B, ∼35.5–33.5 Ma: increased deepening marked by the onset of major glauconitic deposition and inception of energetic bottom-water currents. Phase C, ∼33.5–30.2 Ma: further deepening to bathyal depths, with episodic erosion by increasingly energetic bottom-water currents. Phase D, \u3c30.2 Ma: establishment of stable, open-ocean, warm-temperate, oligotrophic settings characterized by siliceous-carbonate ooze deposition. Our combined evidence indicates that this early Oligocene Tasmanian Gateway deepening initially produced an eastward flow of relatively warm surface waters from the Australo-Antarctic Gulf into the southwestern Pacific Ocean. This “proto-Leeuwin” current fundamentally differs from previous regional reconstructions of eastward flowing cool water (e.g., a “proto-ACC”) during the early Oligocene and thereby represents an important new constraint for reconstructing regional- to global-scale dynamics for this major global change event