An Integrated View of Data: Application of Knowledge Modeling to Data Management

Data management has become an important challenge. Good data management requires an effective approach to collecting, storing, and accessing data across the enterprise. In this paper, a knowledge modeling approach to data management is introduced with an emphasis on data requirements analysis. A knowledge model can provide a high-level view of organizational data by specifying the structure and relationships of the knowledge contents used in business processes. The proposed knowledge modeling approach is business process oriented and decision oriented. The description of the knowledge contents in the model is based on ontological specification. The model is comprised of five elements: work product, work unit, producer, stage, and modeling language. The elements of the model and the modeling process are elaborated. The proposed modeling approach is applied to the vessel chartering process in a shipping company to demonstrate its application in real-world practices

Modeling and Analysis of Plasmonic Terahertz Wave Detector Based on Field Effect Transistor

Department of Electrical EngineeringI propose accurate analysis and novel model of the nonresonant plasmonic terahertz (THz) wave detector based on the silicon (Si) field effect transistor (FET) with a technology computer-aided design (TCAD) platform and SPICE simulation. By introducing a quasi-plasma two-dimensional electron gas (2DEG) in the channel of the FET, the physical behavior of the plasma wave has been modeled with the TCAD platform. For accurate analysis of the modulation and propagation of the channel electron density as the plasma wave, I have characterized the quasi-plasma 2DEG model with two key parameters, such as quasi-plasma 2DEG length (lQP) and density (NQP). The lQP and NQP is defined exactly as extracting the average point of the electron density by using the normalization method. Through the quasi-plasma 2DEG modeling, I investigate the performance enhancement of the plasmonic terahertz wave detector based on Si FET according to scaling down the gate oxide thickness (tox), which is a significant parameter of FET-based plasmonic terahertz detector for the channel electron density modulation. By scaling down tox, the responsivity (Rv) and noise equivalent power (NEP), which are the important performance metrics of the THz wave detector, have been enhanced. In addition, I report the new NQS compact model for MOSFET-based THz wave detector using SPICE simulation. Because the FETs are intensively considered for THz detector due to their performance and applicability, it is essential to describe the physical behaviors of FET in the THz regime with non-quasi-static (NQS) analysis. However, most of the NQS MOSFET models (e.g., Elmore model) have the complexity of the formulation and fail to describe the device physics for the accurate analysis of fast switching and high-frequency operation. In this work, I have proposed novel NQS compact model of MOSFET, which is applicable for transient simulation of the plasmonic THz detectors. The new SPICE NQS model has been verified by comparing with TCAD device simulation as reference of the complete numerical NQS simulation. For simulation of MOSFET-based plasmonic THz detector with SPICE, I demonstrate the model validity by extracting the photoresponse simulation as the function of the gate voltage at 0.2 THz with the peak point in the sub-threshold region. The proposed novel methodologies will provide the advanced physical analysis and efficient structural design for developing the nonresonant plasmonic terahertz detectors operating in THz regime.ope

Reactivity of fly ashes milled in different milling devices

The effect of two different milling devices, namely attrition mill versus vibration mill, on the reactivity of fly ash was studied. High calcium fly ash from 4th Thermal power station of Ulaanbaatar (Mongolia) was used for the experiments. The raw and processed samples were characterized by XRD, SEM, Particle size distribution, BET, Blaine surface area and density measurements. The efficiency of 1 hour milling was evaluated with the Blaine surface area set to be more than 5000 cm2/g. The physical and chemical properties of the attrition milled fly ash changed not much compared to the vibration milled samples. For example the d50 particle size became reduced from 29 μm to 6 μm by attrition milling and in vibration milled fly ash it was reduced to 7 μm. The density increased from 2.44 g/cm3 of raw fly ash to 2.84 g/cm3 and 2.79 g/cm3 in attrition and vibration milled samples, respectively. Mechanical milling revealed not only a particle size reduction but also the formation of a denser microstructure. As a result the vibration milled fly ash showed a weaker interaction with the alkaline solution (8 M NaOH used here) compared to the attrition milled fly ash. Consequently, compressive strength of the binder prepared using the attrition milled fly ash was higher, 61 MPa, while for vibration milled fly ash it was 49 MPa. For comparison unmilled fly ash, it was 21 MPa

Controlled release of human growth hormone fused with a human hybrid Fc fragment through a nanoporous polymer membrane

Nanotechnology has been applied to the development of more effective and compatible drug delivery systems for therapeutic proteins. Human growth hormone (hGH) was fused with a hybrid Fc fragment containing partial Fc domains of human IgD and IgG(4) to produce a long-acting fusion protein. The fusion protein, hGH-hyFc, resulted in the increase of the hydrodynamic diameter (ca. 11 nm) compared with the diameter (ca. 5 nm) of the recombinant hGH. A diblock copolymer membrane with nanopores (average diameter of 14.3 nm) exhibited a constant release rate of hGH-hyFc. The hGH-hyFc protein released in a controlled manner for one month was found to trigger the phosphorylation of Janus kinase 2 (JAK2) in human B lymphocyte and to exhibit an almost identical circular dichroism spectrum to that of the original hGH-hyFc, suggesting that the released fusion protein should maintain the functional and structural integrity of hGH. Thus, the nanoporous release device could be a potential delivery system for the long-term controlled release of therapeutic proteins fused with the hybrid Fc fragment.X111313sciescopu

Palladium Catalysts for Dehydrogenation of Ammonia Borane with Preferential B−H Activation

Cationic Pd(II) complexes catalyzed the dehydrogenation of ammonia borane in the most efficient manner with the release of 2.0 equiv of H_2 in less than 60 s at 25 °C. Most of the hydrogen atoms were obtained from the boron atom of the ammonia borane. The first step of the dehydrogenation reaction was elaborated using density functional theory calculations

Dihydrotestosterone-Inducible IL-6 Inhibits Elongation of Human Hair Shafts by Suppressing Matrix Cell Proliferation and Promotes Regression of Hair Follicles in Mice

Autocrine and paracrine factors are produced by balding dermal papilla (DP) cells following dihydrotestosterone (DHT)-driven alterations and are believed to be key factors involved in male pattern baldness. Herein we report that the IL-6 is upregulated in balding DP cells compared with non-balding DP cells. IL-6 was upregulated 3hours after 10–100nM DHT treatment, and ELISA showed that IL-6 was secreted from balding DP cells in response to DHT. IL-6 receptor (IL-6R) and glycoprotein 130 (gp130) were expressed in follicular keratinocytes, including matrix cells. Recombinant human IL-6 (rhIL-6) inhibited hair shaft elongation and suppressed proliferation of matrix cells in cultured human hair follicles. Moreover, rhIL-6 injection into the hypodermis of mice during anagen caused premature onset of catagen. Taken together, our data strongly suggest that DHT-inducible IL-6 inhibits hair growth as a paracrine mediator from the DP

Adaptive laboratory evolution of a genome-reduced Escherichia coli.

Synthetic biology aims to design and construct bacterial genomes harboring the minimum number of genes required for self-replicable life. However, the genome-reduced bacteria often show impaired growth under laboratory conditions that cannot be understood based on the removed genes. The unexpected phenotypes highlight our limited understanding of bacterial genomes. Here, we deploy adaptive laboratory evolution (ALE) to re-optimize growth performance of a genome-reduced strain. The basis for suboptimal growth is the imbalanced metabolism that is rewired during ALE. The metabolic rewiring is globally orchestrated by mutations in rpoD altering promoter binding of RNA polymerase. Lastly, the evolved strain has no translational buffering capacity, enabling effective translation of abundant mRNAs. Multi-omic analysis of the evolved strain reveals transcriptome- and translatome-wide remodeling that orchestrate metabolism and growth. These results reveal that failure of prediction may not be associated with understanding individual genes, but rather from insufficient understanding of the strain's systems biology