THE TECHNOLOGY FORECASTING OF NEW MATERIALS: THE EXAMPLE OF NANOSIZED CERAMIC POWDERS

New materials have been recognized as significant drivers for corporate growth and profitability in today’s fast changing environments. The nanosized ceramic powders played important parts in new materials field nowadays. However, little has been done in discussing the technology forecasting for the new materials development. Accordingly, this study applied the growth curve method to investigate the technology performances of nanosized ceramic powders. We adopted the bibliometric analysis through EI database and trademark office (USPTO) database to gain the useful data for this work. The effort resulted in nanosized ceramic powders were all in the initial growth periods of technological life cycles. The technology performances of nanosized ceramic powders through the EI and USPTO databases were similar and verified by each other. And there were parts of substitutions between traditional and nanosized ceramic powders. The bibliometric analysis was proposed as the simple and efficient tools to link the science and technology activities, and to obtain quantitative and historical data for helping researchers in technology forecasting, especially in rare historical data available fields, such as the new materials fields.new materials, bibliometric analysis, technology forecasting.

Distributed Training Large-Scale Deep Architectures

Scale of data and scale of computation infrastructures together enable the current deep learning renaissance. However, training large-scale deep architectures demands both algorithmic improvement and careful system configuration. In this paper, we focus on employing the system approach to speed up large-scale training. Via lessons learned from our routine benchmarking effort, we first identify bottlenecks and overheads that hinter data parallelism. We then devise guidelines that help practitioners to configure an effective system and fine-tune parameters to achieve desired speedup. Specifically, we develop a procedure for setting minibatch size and choosing computation algorithms. We also derive lemmas for determining the quantity of key components such as the number of GPUs and parameter servers. Experiments and examples show that these guidelines help effectively speed up large-scale deep learning training

Electricity demand-side management for an energy efficient future in China : technology options and policy priorities

Thesis (Ph. D.)--Massachusetts Institute of Technology, Engineering Systems Division, 2005.Includes bibliographical references (p. 278-289).The main objective of this research is to identify robust technology and policy options which achieve substantial reductions in electricity demand in China's Shandong Province. This research utilizes a scenario-based approach to identify sensible and feasible energy efficiency and load reduction strategies. The research consists of technical analyses through the development of an hourly load simulation model to study the time and temperature sensitive impacts on electricity demand growth by different demand-side management (DSM) scenarios and a policy analysis to formulate policy priorities based on the socio-economic and environmental realities in China. This bottom-up comprehensive study helps inform decision-making given the technological, consumption and socio-economic conditions in large-scale electricity grid systems of Shandong and China, thus preferred DSM strategies are identified, and sensible policy recommendations are made with respect to Shandong province and China as a whole. This study developed a computer-based modeling tool for peak-load based electric demand analysis and long-term projections.(cont.) The model simulates disaggregated hourly electric loads by end-user types with temperature-sensitive load simulation capability, which takes into account time use patterns, life-style and behavioral factors, distributed consumption behaviors of electricity users, appliances and equipment utilization patterns, environmental factors, and industrial structural and operational parameters. The simulation and scenario based research methodology provides a comparative basis, and dynamic insights to electricity demand in areas when limited generation and consumption information is available, which is especially appropriate for electricity sector studies in developing countries. The research showed that demand side management strategies could result in significant reduction in the peak loads as well as the total electricity consumption in Shandong.(cont.) The results of the technical analysis concluded that (1) temperature sensitive load makes up the fastest growing demand within the entire consumption profile; (2) implementation of building energy efficiency strategies demonstrates the largest energy saving potential; (3) implementation of appliances standards, has limited effects on energy saving; (4) load management strategies to induce changes in consumption behaviors also shows great potential, however, they are difficult to estimate; and (5) urbanization policies also have a strong impact on electricity consumption. The recommended DSM policy priorities are based on the energy-saving potentials of the DSM strategies, which are listed in priority order: (1) improvement of building technology, (2) management of new installation first (3) management of temperature sensitive loads, (4) implementation of behavioral and load management strategies, (5) better management of urbanization policies (6) promotion of aggressive industrial motor substitution measures & industrial structural changes, and (6) improvement of appliance efficiency.(cont.) This research also formulated integrated DSM policy recommendations to the Chinese government that are centered by the development of coordinated DSM policy framework, and that are based upon the current technological, managerial and institutional capacities of Chinese industry and governmental agencies. The details include moving away from the traditional utility centered IRP/DSM framework, developing a robust energy efficiency services industry, setting correct DSM priorities and implementing them, developing and upgrading the domestic energy efficiency product industry, and engaging end-user participation. The thesis recognized the barriers and difficulties in the policy implementation and stressed the importance of continuous adaptation and institutional learning in the implementation process.by Chia-Chin Cheng.Ph.D

Susceptibility of Human Embryonic Stem Cell-Derived Neural Cells to Japanese Encephalitis Virus Infection

Pluripotent human embryonic stem cells (hESCs) can be efficiently directed to become immature neuroepithelial precursor cells (NPCs) and functional mature neural cells, including neurotransmitter-secreting neurons and glial cells. Investigating the susceptibility of these hESCs-derived neural cells to neurotrophic viruses, such as Japanese encephalitis virus (JEV), provides insight into the viral cell tropism in the infected human brain. We demonstrate that hESC-derived NPCs are highly vulnerable to JEV infection at a low multiplicity of infection (MOI). In addition, glial fibrillary acid protein (GFAP)-expressing glial cells are also susceptible to JEV infection. In contrast, only a few mature neurons were infected at MOI 10 or higher on the third day post-infection. In addition, functional neurotransmitter-secreting neurons are also resistant to JEV infection at high MOI. Moreover, we discover that vimentin intermediate filament, reported as a putative neurovirulent JEV receptor, is highly expressed in NPCs and glial cells, but not mature neurons. These results indicate that the expression of vimentin in neural cells correlates to the cell tropism of JEV. Finally, we further demonstrate that membranous vimentin is necessary for the susceptibility of hESC-derived NPCs to JEV infection

Pin1 positively affects tumorigenesis of esophageal squamous cell carcinoma and correlates with poor survival of patients

BACKGROUND: Pin1 promotes oncogenesis by regulating multiple oncogenic signaling. In this study, we investigated the involvement of Pin1 in tumor progression and in the prognosis of human esophageal squamous cell carcinoma (ESCC). RESULTS: We observed that proliferation, clonogenicity and tumorigenesis of CE81T cells were inhibited by Pin1 knockdown. We next analyzed Pin1 expression in clinical ESCC specimens. When compared to the corresponding non-tumor part, Pin1 protein and mRNA levels in tumor part were higher in 84% and 62% patients, respectively. By immunohistochemistry, we identified that high Pin1 expression was associated with higher primary tumor stage (p = 0.035), higher overall cancer stage (p = 0.047) and poor overall survival (p < 0.001). Furthermore, the association between expression of Pin1 and levels of β-catenin and cyclin D in cell line and clinical specimens was evaluated. β-catenin and cyclin D1 were decreased in CE81T cells with Pin1 knockdown. Cyclin D1 level correlated with Pin1 expression in clinical ESCC specimens. CONCLUSIONS: Pin1 upregulation was associated with advanced stage and poor prognosis of ESCC. Pin1 knockdown inhibited aggressiveness of ESCC cells. β-catenin and cyclin D1 were positively regulated by Pin1. These results indicated that targeting Pin1 pathway could represent a potential modality for treating ESCC

Root Coverage Procedure With Connective Tissue Graft Harvested From a Distal Wedge: A Case Report

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/141955/1/cap0134.pd