Automated Reconstruction of Neuronal Morphology Based on Local Geometrical and Global Structural Models

Digital reconstruction of neurons from microscope images is an important and challenging problem in neuroscience. In this paper, we propose a model-based method to tackle this problem. We first formulate a model structure, then develop an algorithm for computing it by carefully taking into account morphological characteristics of neurons, as well as the image properties under typical imaging protocols. The method has been tested on the data sets used in the DIADEM competition and produced promising results for four out of the five data sets

Increased waterborne blaNDM-1 resistance gene abundances associated with seasonal human pilgrimages to the Upper Ganges River

Antibiotic resistance (AR) is often rooted in inappropriate antibiotic use, but poor water quality and inadequate sanitation exacerbate the problem, especially in emerging countries. An example is increasing multi-AR due to mobile carbapenemases, such as NDM-1 protein (coded by blaNDM-1 genes), which can produce extreme drug-resistant phenotypes. In 2010, NDM-1 positive isolates and blaNDM-1 genes were detected in surface waters across Delhi and have since been detected across the urban world. However, little is known about blaNDM-1 levels in more pristine locations, such as the headwaters of the Upper Ganges River. This area is of particular interest because it receives massive numbers of visitors during seasonal pilgrimages in May/June, including visitors from urban India. Here we quantified blaNDM-1 abundances, other AR genes (ARG) and coliform bacteria in sediments and water column samples from seven sites in the Rishikesh-Haridwar region of the Upper Ganges and five sites on the Yamuna River in Delhi to contrast blaNDM-1 levels and water quality conditions between season and region. Water quality in the Yamuna was very poor (e.g., anoxia at all sites), and blaNDM-1 abundances were high across sites in water (5.4 ± 0.4 log(blaNDM-1·mL-1); 95% confidence interval) and sediment (6.3 ± 0.7 log(blaNDM-1·mg-1)) samples from both seasons. In contrast, water column blaNDM-1 abundances were very low across all sites (2.1 ± 0.6 log(blaNDM-1·mL-1)) in February in the Upper Ganges and water quality was good (e.g., near saturation oxygen). However, per capita blaNDM-1 levels were 20 times greater in June in the Ganges water column relative to February and blaNDM-1 levels significantly correlated with fecal coliform levels (r=0.61; p=0.007). Given waste management infrastructure is limited in Rishikesh-Haridwar; data imply blaNDM-1 levels are higher in visitor's wastes than local residents, which results in seasonally higher blaNDM-1 levels in the river. Pilgrimage areas without adequate waste treatment are possible "hot spots" for AR transmission, and waste treatment must be improved to reduce broader AR dissemination via exposed returning visitors

Climate change effects on agriculture: Economic responses to biophysical shocks

Agricultural production is sensitive to weather and thus directly affected by climate change. Plausible estimates of these climate change impacts require combined use of climate, crop, and economic models. Results from previous studies vary substantially due to differences in models, scenarios, and data. This paper is part of a collective effort to systematically integrate these three types of models. We focus on the economic component of the assessment, investigating how nine global economic models of agriculture represent endogenous responses to seven standardized climate change scenarios produced by two climate and five crop models. These responses include adjustments in yields, area, consumption, and international trade. We apply biophysical shocks derived from the Intergovernmental Panel on Climate Change's representative concentration pathway with end-of-century radiative forcing of 8.5 W/m2. The mean biophysical yield effect with no incremental CO2 fertilization is a 17% reduction globally by 2050 relative to a scenario with unchanging climate. Endogenous economic responses reduce yield loss to 11%, increase area of major crops by 11%, and reduce consumption by 3%. Agricultural production, cropland area, trade, and prices show the greatest degree of variability in response to climate change, and consumption the lowest. The sources of these differences include model structure and specification; in particular, model assumptions about ease of land use conversion, intensification, and trade. This study identifies where models disagree on the relative responses to climate shocks and highlights research activities needed to improve the representation of agricultural adaptation responses to climate change

Changing perspectives on the internationalization of R&D and innovation by multinational enterprises: a review of the literature

Internationalization of R&D and innovation by Multinational Enterprises (MNEs) has undergone a gradual and comprehensive change in perspective over the past 50 years. From sporadic works in the late 1950s and in the 1960s, it became a systematically analysed topic in the 1970s, starting with pioneering reports and “foundation texts”. Our review unfolds the theoretical and empirical evolution of the literature from dyadic interpretations of centralization versus decentralization of R&D by MNEs to more comprehensive frameworks, wherein established MNEs from Advanced Economies still play a pivotal role, but new players and places also emerge in the global generation and diffusion of knowledge. Hence views of R&D internationalization increasingly rely on concepts, ideas and methods from IB and other related disciplines such as industrial organization, international economics and economic geography. Two main findings are highlighted. First, scholarly research pays an increasing attention to the network-like characteristics of international R&D activities. Second, different streams of literature have emphasized the role of location- specific factors in R&D internationalization. The increasing emphasis on these aspects has created new research opportunities in some key areas, including inter alia: cross-border knowledge sourcing strategies, changes in the geography of R&D and innovation, and the international fragmentation of production and R&D activities

Investigation on the Mechanical Properties of Powder Metallurgy-Manufactured AA7178/ZrSiO4 Nanocomposites

The versatility of metal matrix composites (MMCs) makes them a promising material for various industrial applications. The current study used a ball milling to mechanically AA7178 powder and strengthened with zirconium silicate (ZrSiO4) nanoparticles. In addition, the AA7178 matrix was ball-milled to distribute the ZrSiO4 nanoparticles throughout the material. The AA7178 reinforced with ZrSiO4 nanoparticles was compacted and consolidated using two distinct powder metallurgy (PM) sequences: double pressing, double sintering, and hot pressing. In tests measuring microhardness, compression strength, and elongational break, the new nanocomposites surpassed the AA7178. The adequate interfacial bonding and even distribution of ZrSiO4 nanoparticles throughout the AA7178 matrix were essential to the strengthening mechanism. With the use of hot pressing, the mechanical characteristics of the nanocomposites were enhanced. As reinforcement concentration increased beyond 2.5% by weight, mechanical properties drastically degraded due to ZrSiO4 nanoparticles clumping and unequal distribution. Improved mechanical parts attain through the uniform distribution of ZrSiO4 nanoparticles in the AA7178 and the maintenance of their mechanical properties