Integration of cad/ tool path data for 5-axis step-nc machining of free form / irrregular contoured surfaces

This research paper presents the work on feature recognition, tool path data generation and integration with STEP-NC (AP-238 format) for features having Free form / Irregular Contoured Surface(s) (FICS). Initially, the FICS features are modelled / imported in UG CAD package and a closeness index is generated. This is done by comparing the FICS features with basic B-Splines / Bezier curves / surfaces. Then blending functions are caculated by adopting convolution theorem. Based on the blending functions, contour offsett tool paths are generated and simulated for 5 axis milling environment. Finally, the tool path (CL) data is integrated with STEP-NC (AP-238) format. The tool path algorithm and STEP- NC data is tested with various industrial parts through an automated UFUNC plugin.

Secure Communications in Smart Grid: Networking and Protocols

The key attributes of a smarter power grid include: pervasive interconnection of smart devices; extensive data generation and collection; and rapid reaction to events across a widely dispersed physical infrastructure. Modern telecommunications technologies are being deployed across power systems to support these monitoring and control capabilities. To enable interoperability, several new communications protocols and standards have been developed over the past 10 to 20 years. These continue to be refined, even as new systems are rolled out.

This new hyper-connected communications infrastructure provides an environment rich in sub-systems and physical devices that are attractive to cyber-attackers. Indeed, as smarter grid operations become dependent on interconnectivity, the communications network itself becomes a target. Consequently, we examine cyber-attacks that specifically target communications, particularly state-of-the-art standards and protocols. We further explore approaches and technologies that aim to protect critical communications networks against intrusions, and to monitor for, and detect, intrusions that infiltrate Smart Grid systems.

Testing the Prebish-Singer hypothesis using second-generation panel data stationarity tests with a break

In this paper, we test the Prebish-Singer (PS) hypothesis, which states that real commodity prices decline in the long run, using two recent powerful panel data stationarity tests accounting for cross-sectional dependence and a structural break. We find that the hypothesis cannot be rejected for most commodities other than oil.

Connectivity Mapping for Candidate Therapeutics Identification Using Next Generation Sequencing RNA-Seq Data

The advent of next generation sequencing technologies (NGS) has expanded the area of genomic research, offering high coverage and increased sensitivity over older microarray platforms. Although the current cost of next generation sequencing is still exceeding that of microarray approaches, the rapid advances in NGS will likely make it the platform of choice for future research in differential gene expression. Connectivity mapping is a procedure for examining the connections among diseases, genes and drugs by differential gene expression initially based on microarray technology, with which a large collection of compound-induced reference gene expression profiles have been accumulated. In this work, we aim to test the feasibility of incorporating NGS RNA-Seq data into the current connectivity mapping framework by utilizing the microarray based reference profiles and the construction of a differentially expressed gene signature from a NGS dataset. This would allow for the establishment of connections between the NGS gene signature and those microarray reference profiles, alleviating the associated incurring cost of re-creating drug profiles with NGS technology. We examined the connectivity mapping approach on a publicly available NGS dataset with androgen stimulation of LNCaP cells in order to extract candidate compounds that could inhibit the proliferative phenotype of LNCaP cells and to elucidate their potential in a laboratory setting. In addition, we also analyzed an independent microarray dataset of similar experimental settings. We found a high level of concordance between the top compounds identified using the gene signatures from the two datasets. The nicotine derivative cotinine was returned as the top candidate among the overlapping compounds with potential to suppress this proliferative phenotype. Subsequent lab experiments validated this connectivity mapping hit, showing that cotinine inhibits cell proliferation in an androgen dependent manner. Thus the results in this study suggest a promising prospect of integrating NGS data with connectivity mapping. © 2013 McArt et al.

Efficiency assessment of electricity power generation on Ireland’s Single Electricity Market by Data Envelopment Analysis

The efficiency of generation plants is an important measure for evaluating the operating performance. The objective of this paper is to evaluate electricity power generation by conducting an All-Island-Generator-Efficiency-Study (AIGES) for the Republic of Ireland and Northern Ireland by utilising a Data Envelopment Analysis (DEA) approach. An operational performance efficiency index is defined and pursued for the year 2008. The economic activities of electricity generation units/plants examined in this paper are characterized by numerous input and output indicators. Constant returns to scale (CRS) and variable returns to scale (VRS) type DEA models are employed in the analysis. Also a slacks based analysis indicates the level of inefficiency for each variable examined. The findings from this study provide a general ranking and evaluation but also facilitate various interesting efficiency comparisons between generators by fuel type.

Modelling and Prediction of NOx Emission in a Coal-Fired Power Generation Plant

In this paper NOx emissions modelling for real-time operation and control of a 200 MWe coal-fired power generation plant is studied. Three model types are compared. For the first model the fundamentals governing the NOx formation mechanisms and a system identification technique are used to develop a grey-box model. Then a linear AutoRegressive model with eXogenous inputs (ARX) model and a non-linear ARX model (NARX) are built. Operation plant data is used for modelling and validation. Model cross-validation tests show that the developed grey-box model is able to consistently produce better overall long-term prediction performance than the other two models.

Effects of the novel (Pro(3))GIP antagonist and exendin(9-39)amide on GIP- and GLP-1-induced cyclic AMP generation, insulin secretion and postprandial insulin release in obese diabetic (ob/ob) mice: evidence that GIP is the major physiological incretin

AIMS/HYPOTHESIS: This study examined the biological effects of the GIP receptor antagonist, (Pro3)GIP and the GLP-1 receptor antagonist, exendin(9-39)amide.

METHODS: Cyclic AMP production was assessed in Chinese hamster lung fibroblasts transfected with human GIP or GLP-1 receptors, respectively. In vitro insulin release studies were assessed in BRIN-BD11 cells while in vivo insulinotropic and glycaemic responses were measured in obese diabetic ( ob/ ob) mice.

RESULTS: In GIP receptor-transfected fibroblasts, (Pro(3))GIP or exendin(9-39)amide inhibited GIP-stimulated cyclic AMP production with maximal inhibition of 70.0+/-3.5% and 73.5+/-3.2% at 10(-6) mol/l, respectively. In GLP-1 receptor-transfected fibroblasts, exendin(9-39)amide inhibited GLP-1-stimulated cyclic AMP production with maximal inhibition of 60+/-0.7% at 10(-6) mol/l, whereas (Pro(3))GIP had no effect. (Pro(3))GIP specifically inhibited GIP-stimulated insulin release (86%; p<0.001) from clonal BRIN-BD11 cells, but had no effect on GLP-1-stimulated insulin release. In contrast, exendin(9-39)amide inhibited both GIP and GLP-1-stimulated insulin release (57% and 44%, respectively; p<0.001). Administration of (Pro(3))GIP, exendin(9-39)amide or a combination of both peptides (25 nmol/kg body weight, i.p.) to fasted (ob/ob) mice decreased the plasma insulin responses by 42%, 54% and 49%, respectively (p<0.01 to p<0.001). The hyperinsulinaemia of non-fasted (ob/ob) mice was decreased by 19%, 27% and 18% (p<0.05 to p<0.01) by injection of (Pro3)GIP, exendin(9-39)amide or combined peptides but accompanying changes of plasma glucose were small.

CONCLUSIONS/INTERPRETATION: These data show that (Pro(3))GIP is a specific GIP receptor antagonist. Furthermore, feeding studies in one commonly used animal model of obesity and diabetes, (ob/ob) mice, suggest that GIP is the major physiological component of the enteroinsular axis, contributing approximately 80% to incretin-induced insulin release.

Development of complex classical force fields through force matching to ab initio data: Application to a room-temperature ionic liquid

Recent experimental neutron diffraction data and ab initio molecular dynamics simulation of the ionic liquid dimethylimidazolium chloride ([dmim]Cl) have provided a structural description of the system at the molecular level. However, partial radial distribution functions calculated from the latter, when compared to previous classical simulation results, highlight some limitations in the structural description offered by force fieldbased simulations. With the availability of ab initio data it is possible to improve the classical description of [dmim]Cl by using the force matching approach, and the strategy for fitting complex force fields in their original functional form is discussed. A self-consistent optimization method for the generation of classical potentials of general functional form is presented and applied, and a force field that better reproduces the observed first principles forces is obtained. When used in simulation, it predicts structural data which reproduces more faithfully that observed in the ab initio studies. Some possible refinements to the technique, its application, and the general suitability of common potential energy functions used within many ionic liquid force fields are discussed.

Enhanced cAMP generation and insulin-releasing potency of two novel Tyr(1)-modified enzyme-resistant forms of glucose-dependent insulinotropic polypeptide is associated with significant antihyperglycaemic activity in spontaneous obesity-diabetes

Glucose-dependent insulinotropic polypeptide (GIP) is an important incretin hormone, which potentiates glucose-induced insulin secretion. Antihyperglycaemic actions of GIP provide significant potential in Type 11 diabetes therapy. However, inactivation of GIP by the enzyme dipeptidyl peptidase IV (DPP IV) and its consequent short circulating half-life limit its therapeutic use. Therefore two novel Tyr(1)-Modified analogues of GIP, N-Fmoc-GIP (where Fmoc is 9-fluorenylmethoxycarbonyl) and N-palmitate-GIP, were synthesized and tested for metabolic stability and biological activity. Both GIP analogues were resistant to degradation by DPP IV and human plasma. In Chinese hamster lung (CHL) cells expressing the cloned human GIP receptor, both analogues exhibited a 2-fold increase in cAMP-generating potency compared with native GIP (EC50 values of 9.4, 10.0 and 18.2 nM respectively). Using clonal BRIN-BD11 cells, both analogues demonstrated strong insulinotropic activity compared with native GIP (P <0.01 to P <0.001). In obese diabetic (ob/ob) mice, administration of N-Fmoc-GIP or N-palmitate-GIP (25 nmol/kg) together with glucose (18 mmol/kg) significantly reduced the peak 15 min glucose excursion (1.4- and 1.5-fold respectively; P <0.05 to P <0.01) compared with glucose alone. The area under the curve (AUC) for glucose was significantly lower after administration of either analogue compared with glucose administered alone or in combination with native GIP (1.5-fold; P <0.05). This was associated with a significantly greater AUC for insulin (2.1-fold; P <0.001) for both analogues compared with native GIP. A similar pattern of in vivo responsiveness was evident in lean control mice. These data indicate that novel N-terminal Tyr(1) modification of GIP with an Fmoc or palmitate group confers resistance to degradation by DPP IV in plasma, which is reflected by increased in vitro potency and greater insulinotropic and antihyperglycaemic activities in an animal model of Type 11 diabetes mellitus.

Room Temperature, Electrochemical Generation of Ozone with 50% Current Efficiency in 0.5M Sulfuric Acid at Cell Voltages <3V.

The electrochemical generation of ozone by Ni/Sb-SnO2 anodes immersed in 0.5M H2SO4 was assessed in both flow and recycle systems using the same electrochemical cell. The anodes were found to exhibit current efficiencies of up to 50% for ozone generation under flow conditions at room temperature, with an optimum mole ratio in the precursor solutions of ca. 500:8:3 Sn:Sb:Ni and optimum cell voltage of 2.7V. A comparison of the data obtained under flow and recycle conditions suggests that the presence of ozone in the anolyte inhibits its formation. The minimum electrical energy cost achieved, of 18 kWh kg1 compares favorably with estimated costs for Cold Corona Discharge generally reported in the literature, especially when the very significant advantages of electrochemical ozone generation are taken into account.

Introduction to Domain-Driven Data Mining Special Section

In the last decade, data mining has emerged as one of the most dynamic and lively areas in information technology. Although many algorithms and techniques for data mining have been proposed, they either focus on domain independent techniques or on very specific domain problems. A general requirement in bridging the gap between academia and business is to cater to general domain-related issues surrounding real-life applications, such as constraints, organizational factors, domain expert knowledge, domain adaption, and operational knowledge. Unfortunately, these either have not been addressed, or have not been sufficiently addressed, in current data mining research and development.Domain-Driven Data Mining (D3M) aims to develop general principles, methodologies, and techniques for modeling and merging comprehensive domain-related factors and synthesized ubiquitous intelligence surrounding problem domains with the data mining process, and discovering knowledge to support business decision-making. This paper aims to report original, cutting-edge, and state-of-the-art progress in D3M. It covers theoretical and applied contributions aiming to: 1) propose next-generation data mining frameworks and processes for actionable knowledge discovery, 2) investigate effective (automated, human and machine-centered and/or human-machined-co-operated) principles and approaches for acquiring, representing, modelling, and engaging ubiquitous intelligence in real-world data mining, and 3) develop workable and operational systems balancing technical significance and applications concerns, and converting and delivering actionable knowledge into operational applications rules to seamlessly engage application processes and systems.

Low power field programmable gate array implementation of fast digital signal processing algorithms: characterisation and manipulation of data locality

Dynamic power consumption is very dependent on interconnect, so clever mapping of digital signal processing algorithms to parallelised realisations with data locality is vital. This is a particular problem for fast algorithm implementations where typically, designers will have sacrificed circuit structure for efficiency in software implementation. This study outlines an approach for reducing the dynamic power consumption of a class of fast algorithms by minimising the index space separation; this allows the generation of field programmable gate array (FPGA) implementations with reduced power consumption. It is shown how a 50% reduction in relative index space separation results in a measured power gain of 36 and 37% over a Cooley-Tukey Fast Fourier Transform (FFT)-based solution for both actual power measurements for a Xilinx Virtex-II FPGA implementation and circuit measurements for a Xilinx Virtex-5 implementation. The authors show the generality of the approach by applying it to a number of other fast algorithms namely the discrete cosine, the discrete Hartley and the Walsh-Hadamard transforms.

Monoenergetic Ion Beam Generation by Driving Ion Solitary Waves with Circularly Polarized Laser Light

Experimental data from the Trident Laser facility is presented showing quasimonoenergetic carbon ions from nm-scaled foil targets with an energy spread of as low as 15% at 35 MeV. These results and high resolution kinetic simulations show laser acceleration of quasimonoenergetic ion beams by the generation of ion solitons with circularly polarized laser pulses (500 fs, ¼ 1054 nm). The conversion ef?ciency into monoenergetic ions is increased by an order of magnitude compared with previous experimental results, representing an important step towards applications such as ion fast ignition.

Probing Ferroelectrics Using Optical Second Harmonic Generation

Nonlinear optics is an essential component of modern laser systems and optoelectronic devices. It has also emerged as an important tool in probing the electronic, vibrational, magnetic, and crystallographic structure of materials ranging from oxides and metals, to polymers and biological samples. This review focuses on the specific technique of optical second harmonic generation (SHG), and its application in probing ferroelectric complex oxide crystals and thin films. As the dominant SHG interaction mechanism exists only in materials that lack inversion symmetry, SHG is a sensitive probe of broken inversion symmetry, and thus also of bulk polar phenomena in materials. By performing in-situ SHG polarimetry experiments in different experimental conditions such as sample orientation, applied electric field, and temperature, one can probe ferroelectric hysteresis loops and phase transitions. Careful modeling of the polarimetry data allows for the determination of the point group symmetry of the crystal. In epitaxial thin films with a two-dimensional arrangement of well-defined domain orientations, one can extract information about intrinsic material properties such as nonlinear coefficients, as well as microstructural information such as the local statistics of the different domain variants being probed. This review presents several detailed examples of ferroelectric systems where such measurements and modeling are performed. The use of SHG microscopic imaging is discussed, and its ability to reveal domain structures and phases not normally visible with linear optics is illustrated.