Sites Unseen: Uncovering Hidden Hazards in American Cities, by Scott Frickel and James R. Elliott. New York, NY: Russell Sage Foundation, ISBN 9780871544285; 154 pp. $29.95 paperback

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/149744/1/cico12408.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/149744/2/cico12408_am.pd

Guillermo Jajamovich 2018: Puerto Madero in Motion [Puerto Madero en Movimiento]. Buenos Aires: Teseo

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/153761/1/ijur12886.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/153761/2/ijur12886_am.pd

Arlene Dávila (2012): Culture Works: Space, Value, and Mobility Across the Neoliberal Americas

For "lo urbano" issue

Failed power domination on graphs

Let G be a simple graph with vertex set V and edge set E, and let S ⊆ V . The sets Pi (S), i ≥ 0, of vertices monitored by S at the i th step are given by P0(S) = N[S] and Pi+1(S) = Pi (S) {w : {w} = N[v]\Pi (S) for some v ∈ Pi (S)}. If there exists j such that Pj (S) = V , then S is called a power dominating set, PDS, of G. Otherwise, S is a failed power dominating set, FPDS. The power domination number of a simple graph G, denoted γp(G) gives the minimum number of measurement devices known as phasor measurement units (PMUs) required to observe a power network represented by G, and is the minimum cardinality of any PDS of G. The failed power domination number of G, ¯γp(G), is the maximum cardinality of any FPDS of G, and represents the maximum number of PMUs that could be placed on a given power network represented by G, but fail to observe the full network. As a consequence, ¯γp(G)+1 gives the minimum number of PMUs necessary to successfully observe the full network no matter where they are placed. We prove that ¯γp(G) is NP-hard to compute, determine graphs in which every vertex is a PDS, and compare ¯γp(G) to similar parameters

Mass Action Kinetic Model of Apoptosis by TRAIL-Functionalized Leukocytes

Background: Metastasis through the bloodstream contributes to poor prognosis in many types of cancer. A unique approach to target and kill colon, prostate, and other epithelial-type cancer cells in the blood has been recently developed that uses circulating leukocytes to present the cancer-specific, liposome-bound Tumor Necrosis Factor (TNF)-related apoptosis inducing ligand (TRAIL) on their surface along with E − selectin adhesion receptors. This approach, demonstrated both in vitro with human blood and in mice, mimics the cytotoxic activity of natural killer cells. The resulting liposomal TRAIL-coated leukocytes hold promise as an effective means to neutralize circulating tumor cells that enter the bloodstream with the potential to form new metastases.Methods: The computational biology study reported here examines the mechanism of this effective signal delivery, by considering the kinetics of the coupled reaction cascade, from TRAIL binding death receptor to eventual apoptosis. In this study, a collision of bound TRAIL with circulating tumor cells (CTCs) is considered and compared to a prolonged exposure of CTCs to soluble TRAIL. An existing computational model of soluble TRAIL treatment was modified to represent the kinetics from a diffusion-limited 3D reference frame into a 2D collision frame with advection and adhesion to mimic the E − selectin and membrane bound TRAIL treatment. Thus, the current model recreates the new approach of targeting cancer cells within the blood. The model was found to faithfully reproduce representative observations from experiments of liposomal TRAIL treatment under shear.Results: The model predicts apoptosis of CTCs within 2 h when treated with membrane bound TRAIL, while apoptosis in CTCs treated with soluble TRAIL proceeds much more slowly over the course of 10 h, consistent with previous experiments. Given the clearance rate of soluble TRAIL in vivo, this model predicts that the soluble TRAIL method would be rendered ineffective, as found in previous experiments.Conclusion: This study therefore indicates that the kinetics of the coupled reaction cascade of liposomal E − selectin and membrane bound TRAIL colliding with CTCs can explain why this new approach to target and kill cancer cells in blood is much more effective than its soluble counterpart

Prova Nacional dos Residentes e Especializandos em Radiologia e Diagnóstico por Imagem no Brasil: instrumento de avaliação da qualificação do futuro radiologista

PURPOSE: This is a study of performance based on an In-training Examination for Radiology and Diagnostic Imaging targeting residents (R) and specialization trainees (ST) in Radiology. The radiological training may differ between R and ST in some centers. The authors present their experience and thoughts regarding the first three years of application of the In-training Examination administered by The Brazilian College of Radiology. METHODS: Three hundred and eight-six tests were analyzed in 1999, 715 in 2000, and 731 in 2001. The yearly tests consisted of multiple-choice answers, some with interpretation of digital images, and were divided into 9 specialties: neurology, thorax, physics, pediatrics, digestive system, urinary system, musculoskeletal system, mammography, and gynecology-obstetrics. Each specialty was analyzed separately. The tests were given simultaneously in 12 Brazilian cities. The subspecialty scores of examinees at different stages of training were compared (1st, 2nd, and 3rd year residents and specialization trainees), by the Kruskal-Wallis test (P;0.05). Generally, in 2000 and 2001, R achieved higher scores than ST (POBJETIVO: Estudo comparativo entre o desempenho dos residentes e especializandos em radiologia por meio da Prova Nacional dos Residentes e Especializandos em Radiologia e Diagnóstico por Imagem (PNRERADI), durante os três primeiros anos de sua aplicação. O ensino nos centros de formação em radiodiagnóstico pode diferir entre residentes e especializandos. MÉTODOS: Foram analisadas 386 provas em 1999, 715 em 2000 e 731 em 2001. As provas foram divididas em nove subespecialidades: neurologia, tórax, digestivo, física, pediatria, urinário, músculo-esquelético, mamografia e ginecologia-obstetrícia, cada uma delas avaliada separadamente, constando de testes de múltipla escolha, algumas com interpretação de imagens digitalizadas. As provas foram aplicadas simultaneamente em 12 cidades distribuídas no território nacional. As subespecialidades foram comparadas nos diversos níveis (residentes e especializandos de 1º, 2º e 3º anos) através do teste não-paramétrico de Kruskal-Wallis (