Intersections of Jane Jacobs’ conditions for diversity and low-carbon urban systems: a look at four global cities

Countless cities are rapidly developing across the globe, pressing the need for clear urban planning and design recommendations geared towards sustainability. This article examines the intersections of Jane Jacobs’ four conditions for diversity with low-carbon and low-energy use urban systems in four cities around the world: Lyon (France), Chicago (United-States), Kolkata (India), and Singapore (Singapore). After reviewing Jacobs’ four conditions for diversity, we introduce the four cities and describe their historical development context. We then present a framework to study the cities along three dimensions: population and density, infrastructure development/use, and climate and landscape. These cities differ in many respects and their analysis is instructive for many other cities around the globe. Jacobs’ conditions are present in all of them, manifested in different ways and to varying degrees. Overall we find that the adoption of Jacobs' conditions seems to align well with concepts of low-carbon urban systems, with their focus on walkability, transit-oriented design, and more efficient land use (i.e., smaller unit sizes). Transportation sector emissions seems to demonstrate a stronger influence from the presence of Jacobs' conditions, while the link was less pronounced in the building sector. Kolkata, a low-income, developing world city, seems to possess many of Jacobs' conditions, while exhibiting low per capita emissions - maintaining both of these during its economic expansion will take careful consideration. Greenhouse gas mitigation, however, is inherently an in situ problem and the first task must therefore be to gain local knowledge of an area before developing strategies to lower its carbon footprint

Focused Ion Beam Fabrication

Contains summary of research program and reports on four research projects.Charles Stark Draper Laboratory (Contract DL-H-225270)Hughes Research LaboratoriesInternational Business Machines, Inc. (Contract 456614)Nippon Telegraph and Telephone, Inc.U.S. Navy - Office of Naval Research (Contract N00014-84-K-0073)U.S. Department of Defense (Contract MDA903-85-C-0215)Hitachi Central Research Laborator

Air-sea CO2 exchange in the equatorial Pacific

Author Posting. © American Geophysical Union, 2004. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research 109 (2004): C08S02, doi:10.1029/2003JC002256.GasEx-2001, a 15-day air-sea carbon dioxide (CO2) exchange study conducted in the equatorial Pacific, used a combination of ships, buoys, and drifters equipped with ocean and atmospheric sensors to assess variability and surface mechanisms controlling air-sea CO2 fluxes. Direct covariance and profile method air-sea CO2 fluxes were measured together with the surface ocean and marine boundary layer processes. The study took place in February 2001 near 125°W, 3°S in a region of high CO2. The diurnal variation in the air-sea CO2 difference was 2.5%, driven predominantly by temperature effects on surface solubility. The wind speed was 6.0 ± 1.3 m s−1, and the atmospheric boundary layer was unstable with conditions over the range −1 < z/L < 0. Diurnal heat fluxes generated daytime surface ocean stratification and subsequent large nighttime buoyancy fluxes. The average CO2 flux from the ocean to the atmosphere was determined to be 3.9 mol m−2 yr−1, with nighttime CO2 fluxes increasing by 40% over daytime values because of a strong nighttime increase in (vertical) convective velocities. The 15 days of air-sea flux measurements taken during GasEx-2001 demonstrate some of the systematic environmental trends of the eastern equatorial Pacific Ocean. The fact that other physical processes, in addition to wind, were observed to control the rate of CO2 transfer from the ocean to the atmosphere indicates that these processes need to be taken into account in local and global biogeochemical models. These local processes can vary on regional and global scales. The GasEx-2001 results show a weak wind dependence but a strong variability in processes governed by the diurnal heating cycle. This implies that any changes in the incident radiation, including atmospheric cloud dynamics, phytoplankton biomass, and surface ocean stratification may have significant feedbacks on the amount and variability of air-sea gas exchange. This is in sharp contrast with previous field studies of air-sea gas exchange, which showed that wind was the dominating forcing function. The results suggest that gas transfer parameterizations that rely solely on wind will be insufficient for regions with low to intermediate winds and strong insolation.This work was performed with the support of the National Science Foundation Grant OCE-9986724 and the NOAA Global Carbon Cycle Program Grants NA06GP048, NA17RJ1223, and NA87RJ0445 in the Office of Global Programs

The Liver Tumor Segmentation Benchmark (LiTS)

In this work, we report the set-up and results of the Liver Tumor Segmentation Benchmark (LITS) organized in conjunction with the IEEE International Symposium on Biomedical Imaging (ISBI) 2016 and International Conference On Medical Image Computing Computer Assisted Intervention (MICCAI) 2017. Twenty four valid state-of-the-art liver and liver tumor segmentation algorithms were applied to a set of 131 computed tomography (CT) volumes with different types of tumor contrast levels (hyper-/hypo-intense), abnormalities in tissues (metastasectomie) size and varying amount of lesions. The submitted algorithms have been tested on 70 undisclosed volumes. The dataset is created in collaboration with seven hospitals and research institutions and manually reviewed by independent three radiologists. We found that not a single algorithm performed best for liver and tumors. The best liver segmentation algorithm achieved a Dice score of 0.96(MICCAI) whereas for tumor segmentation the best algorithm evaluated at 0.67(ISBI) and 0.70(MICCAI). The LITS image data and manual annotations continue to be publicly available through an online evaluation system as an ongoing benchmarking resource.Comment: conferenc

Identification of a novel susceptibility locus at 13q34 and refinement of the 20p12.2 region as a multi-signal locus associated with bladder cancer risk in individuals of european ancestry

Candidate gene and genome-wide association studies (GWAS) have identified 15 independent genomic regions associated with bladder cancer risk. In search for additional susceptibility variants, we followed up on four promising single-nucleotide polymorphisms (SNPs) that had not achieved genome-wide significance in 6911 cases and 11 814 controls (rs6104690, rs4510656, rs5003154 and rs4907479, P &lt; 1 7 10(-6)), using additional data from existing GWAS datasets and targeted genotyping for studies that did not have GWAS data. In a combined analysis, which included data on up to 15 058 cases and 286 270 controls, two SNPs achieved genome-wide statistical significance: rs6104690 in a gene desert at 20p12.2 (P = 2.19 7 10(-11)) and rs4907479 within the MCF2L gene at 13q34 (P = 3.3 7 10(-10)). Imputation and fine-mapping analyses were performed in these two regions for a subset of 5551 bladder cancer cases and 10 242 controls. Analyses at the 13q34 region suggest a single signal marked by rs4907479. In contrast, we detected two signals in the 20p12.2 region-the first signal is marked by rs6104690, and the second signal is marked by two moderately correlated SNPs (r(2) = 0.53), rs6108803 and the previously reported rs62185668. The second 20p12.2 signal is more strongly associated with the risk of muscle-invasive (T2-T4 stage) compared with non-muscle-invasive (Ta, T1 stage) bladder cancer (case-case P 64 0.02 for both rs62185668 and rs6108803). Functional analyses are needed to explore the biological mechanisms underlying these novel genetic associations with risk for bladder cancer

Common Genetic Polymorphisms Influence Blood Biomarker Measurements in COPD

Implementing precision medicine for complex diseases such as chronic obstructive lung disease (COPD) will require extensive use of biomarkers and an in-depth understanding of how genetic, epigenetic, and environmental variations contribute to phenotypic diversity and disease progression. A meta-analysis from two large cohorts of current and former smokers with and without COPD [SPIROMICS (N = 750); COPDGene (N = 590)] was used to identify single nucleotide polymorphisms (SNPs) associated with measurement of 88 blood proteins (protein quantitative trait loci; pQTLs). PQTLs consistently replicated between the two cohorts. Features of pQTLs were compared to previously reported expression QTLs (eQTLs). Inference of causal relations of pQTL genotypes, biomarker measurements, and four clinical COPD phenotypes (airflow obstruction, emphysema, exacerbation history, and chronic bronchitis) were explored using conditional independence tests. We identified 527 highly significant (p 10% of measured variation in 13 protein biomarkers, with a single SNP (rs7041; p = 10−392) explaining 71%-75% of the measured variation in vitamin D binding protein (gene = GC). Some of these pQTLs [e.g., pQTLs for VDBP, sRAGE (gene = AGER), surfactant protein D (gene = SFTPD), and TNFRSF10C] have been previously associated with COPD phenotypes. Most pQTLs were local (cis), but distant (trans) pQTL SNPs in the ABO blood group locus were the top pQTL SNPs for five proteins. The inclusion of pQTL SNPs improved the clinical predictive value for the established association of sRAGE and emphysema, and the explanation of variance (R2) for emphysema improved from 0.3 to 0.4 when the pQTL SNP was included in the model along with clinical covariates. Causal modeling provided insight into specific pQTL-disease relationships for airflow obstruction and emphysema. In conclusion, given the frequency of highly significant local pQTLs, the large amount of variance potentially explained by pQTL, and the differences observed between pQTLs and eQTLs SNPs, we recommend that protein biomarker-disease association studies take into account the potential effect of common local SNPs and that pQTLs be integrated along with eQTLs to uncover disease mechanisms. Large-scale blood biomarker studies would also benefit from close attention to the ABO blood group