Enhanced neointimal growth in cultured rabbit aorta following in vivo balloon angioplasty

We have used in vivo balloon catheterization in combination with in vitro organ culture to develop a model system for vascular neointima formation. A Fogarty balloon catheter was used to deendothelialize and rupture the internal elastic lamina of aortae in adult rabbits. After three d of recovery, aortae were harvested, divided into segments, and placed into organ culture. We obtained a daily index of cell proliferation in cultured vessels using [3H]thymidine incorporation into DNA. Also, segments were collected and processed for routine histology or immunohistochemistry. Aortic segments that had undergone ballooning 3 d before harvest and then cultured exhibited diffuse neointimal growth after several d in vitro, whereas those from sham-operated (nonballooned) rabbits showed generally only a single endothelial cell layer that is characteristic of normal intima. Aortae that were harvested, balloon-damaged in vitro, and then cultured exhibited no neointimal growth. The neointima that developed in cultured segments from in vivo ballooned rabbits was primarily of smooth muscle cell origin as determined by positive immunostaining for alpha-smooth muscle actin. The intima:media thickness ratios were significantly higher in aortic segments from ballooned rabbits at harvest and after 4 or 7 d in culture compared with those from nonballooned rabbits. Also, the [3H]thymidine index was higher in the in vivo ballooned aorta compared to non-ballooned or in vitro ballooned vessel. We conclude that ballooning in vivo followed by exposure to blood-borne elements produces an enhanced proliferative response in cultured vessels that is distinct from other in vitro models of neointimal growth.     

Analysis of fly ash heavy metal content and disposal in three thermal power plants in India

The study investigates the heavy metal content of fly ash and bottom ash from three major power plants in North India, using flame atomic absorption spectrometry. It also studies the prevalent disposal methods used at these sites. The ashes were analysed for the presence of Cr, Mn, Pb, Zn, Cu, Ni and Co and detectable levels of all were found in both fly ash and bottom ash. The concentrations of Cr and Zn were highest while Co concentration was less. The wet disposal method is used in two of the power plants (site 1 and site 3). Neither of the sites uses ash pond lining in the construction of the ash ponds, hence leaching of the heavy metals is possible. Site 2 has adopted 100% dry disposal system which allows better utilization but incurs additional costs. Better management practices, increased utilization and proper disposal practices need to be undertaken to minimize the adverse environmental impact.     

Structural drivers controlling sulfur solubility in alkali aluminoborosilicate glasses

If the direct feed approach to vitrify the Hanford's tank waste is implemented, the low activity waste (LAW) will comprise higher concentrations of alkali/alkaline-earth sulfates than expected under the previously proposed vitrification scheme. To ensure a minimal impact of higher sulfate concentrations on the downstream operations and overall cost of vitrification, advanced glass formulations with enhanced sulfate loadings (solubility) are needed. While, the current sulfate solubility predictive models have been successful in designing LAW glasses with sulfate loadings <2 wt.%, it will be difficult for them to design glass compositions with enhanced loadings due to our limited understanding of the fundamental science governing these processes. In this pursuit, this article unearths the underlying compositional and structural drivers controlling the sulfate solubility in model LAW glasses. It has been shown that the preferentially removes non-framework cations from the modifier sites in the silicate network, thus, leading to the polymerization in the glass network via the formation of ring-structured borosilicate units. Furthermore, though the sulfate solubility slightly decreases with increasing Li⁺/Na⁺ in the glasses, the prefers to be charge compensated by Na⁺, as it is easier for to break Na–O bonds instead of Li–O bonds.     

Effect of austenitization on austempering of copper alloyed ductile iron

A ductile iron containing 0.6% copper as the main alloying element was austempered at a fixed austempering temperature of 330 °C for a fixed austempering time of 60 min after austenitization at 850 °C for different austenitization periods of 60, 90, and 120 min. The austempering process was repeated after changing austenitization temperature to 900 °C. The effect of austenitization temperature and time was studied on the carbon content and its distribution in the austenite after austenitization. The effect of austenitization parameters was also studied on austempered microstructure, structural parameters like volume fraction of austenite, X _γ , carbon content C _γ , and X _γ C _γ , and bainitic ferrite needle size, d _α after austempering. The average carbon content of austenite increases linearly with austenitization time and reaches a saturation level. Higher austenitization temperature results in higher carbon content of austenite. As regards the austempered structure, the lowering austenitization temperature causes significant refinement and more uniform distribution of austempered structure, and a decrease in the volume fraction of retained austenite.     

The influence of nickel and copper on the austempering of ductile iron

In the present investigation, the effect of alloying elements on the austempering process, austempered microstructure, and structural parameters of two austempered ductile irons (ADI) containing 0.6% Cu and 0.6% Cu/1.0% Ni as the main alloying elements was investigated. The optical metallography and x-ray diffraction were used to study the changes in the austempered structure. The effect of alloying additions on the austempering kinetics was studied using the Avrami equation. Significantly more upper bainite was observed in the austempered Cu-Ni alloyed ADI than in Cu alloyed ADI. The volume fraction of retained austenite (X _γ), the carbon level in the retained austenite (C _γ), and the product X _γ C _γ in an austempered structure of Cu-alloyed ADI are higher than in Cu-Ni-alloyed ADI. The austempering Kinetics is slowed down by the addition of Ni.     

Template-based program verification and program synthesis

Program verification is the task of automatically generating proofs for a program’s compliance with a given specification. Program synthesis is the task of automatically generating a program that meets a given specification. Both program verification and program synthesis can be viewed as search problems, for proofs and programs, respectively. For these search problems, we present approaches based on user-provided insights in the form of templates. Templates are hints about the syntactic forms of the invariants and programs, and help guide the search for solutions. We show how to reduce the template-based search problem to satisfiability solving, which permits the use of off-the-shelf solvers to efficiently explore the search space. Template-based approaches have allowed us to verify and synthesize programs outside the abilities of previous verifiers and synthesizers. Our approach can verify and synthesize difficult algorithmic textbook programs (e.g., sorting and dynamic programming-based algorithms) and difficult arithmetic programs.     

Pedestrian Detection and Tracking Using Deformable Part Models and Kalman Filtering

Abstract： Pedestrian detection techniques are important and challenging especially for complex real world scenes. They can be used for ensuring pedestrian safety, ADASs （advance driver assistance systems） and safety surveillance systems. In this paper, we propose a novel approach for multi-person tracking-by-detection using deformable part models in Kalman filtering framework. The Kalman filter is used to keep track of each person and a unique label is assigned to each tracked individual. Based on this approach, people can enter and leave the scene randomly. We test and demonstrate our results on Caltech Pedestrian benchmark, which is two orders of magnitude larger than any other existing datasets and consists of pedestrians varying widely in appearance, pose and scale. Complex situations such as people occluded by each other are handled gracefully and individual persons can be tracked correctly after a group of people split. Experiments confirm the real-time performance and robustness of our system, working in complex scenes. Our tracking model gives a tracking accuracy of 72.8% and a tracking precision of 82.3%. We can further reduce false positives by 2.8%, using Kalman filtering.     

Automated analysis of images in documents for intelligent document search

Authors use images to present a wide variety of important information in documents. For example, two-dimensional (2-D) plots display important data in scientific publications. Often, end-users seek to extract this data and convert it into a machine-processible form so that the data can be analyzed automatically or compared with other existing data. Existing document data extraction tools are semi-automatic and require users to provide metadata and interactively extract the data. In this paper, we describe a system that extracts data from documents fully automatically, completely eliminating the need for human intervention. The system uses a supervised learning-based algorithm to classify figures in digital documents into five classes: photographs, 2-D plots, 3-D plots, diagrams, and others. Then, an integrated algorithm is used to extract numerical data from data points and lines in the 2-D plot images along with the axes and their labels, the data symbols in the figure’s legend and their associated labels. We demonstrate that the proposed system and its component algorithms are effective via an empirical evaluation. Our data extraction system has the potential to be a vital component in high volume digital libraries.     

Supply chain risk mitigation competency: an individual-level knowledge-based perspective

Supply chain managers are responsible for making decisions regarding supply chain risk in order to mitigate the impact of supply chain disruptions. This study develops and tests a theoretical model that leverages the individual-level knowledge-based view perspective to understand the process through which risk mitigation orientation of the supply chain manager contributes to his/her absorptive capacity. A supply chain manager’s absorptive capacity, in turn, enhances his/her ability to effectively mitigate supply chain risk. Study findings demonstrate that supply chain managers with high-risk mitigation orientation have greater level of absorptive capacity which enhances their risk mitigation competency. This study represents the first development and testing of a model that examines individual-level knowledge management factors that affect supply chain risk mitigation competency. This research emphasises the importance of the individual supply chain manager in managing risk and illustrates how theoretical perspectives from the knowledge management, supply chain risk and organisational behaviour literature can be fruitfully adopted to explain behaviour in the field of supply chain risk management.