Development of a 3D printer using scanning projection stereolithography

We have developed a system for the rapid fabrication of low cost 3D devices and systems in the laboratory with micro-scale features yet cm-scale objects. Our system is inspired by maskless lithography, where a digital micromirror device (DMD) is used to project patterns with resolution up to 10 µm onto a layer of photoresist. Large area objects can be fabricated by stitching projected images over a 5cm2 area. The addition of a z-stage allows multiple layers to be stacked to create 3D objects, removing the need for any developing or etching steps but at the same time leading to true 3D devices which are robust, configurable and scalable. We demonstrate the applications of the system by printing a range of micro-scale objects as well as a fully functioning microfluidic droplet device and test its integrity by pumping dye through the channels

Floral scent evolution in the genus jaborosa (Solanaceae): Influence of ecological and environmental factors

Floral scent is a key communication channel between plants and pollinators. However,the contributions of environment and phylogeny to floral scent composition remain poorly understood. In this study, we characterized interspecific variation of floral scent composition in the genus Jaborosa Juss. (Solanaceae) and, using an ecological niche modelling approach (ENM), we assessed the environmental variables that exerted the strongest influence on floral scent variation, taking into account pollination mode and phylogenetic relationships. Our results indicate that two major evolutionary themes have emerged: (i) a ?warm Lowland Subtropical nectar-rewarding clade? with large white hawkmoth pollinated flowers that emit fragrances dominated by oxygenated aromatic or sesquiterpenoid volatiles, and (ii) a ?cool-temperate brood-deceptive clade? of largely fly-pollinated species found at high altitudes (Andes) or latitudes (Patagonian Steppe) that emit foul odors including cresol, indole and sulfuric volatiles. The joint consideration of floral scent profiles, pollination mode, and geoclimatic context helped us to disentangle the factors that shaped floral scent evolution across ?pollinator climates? (geographic differences in pollinator abundance or preference). Our findings suggest that the ability of plants in the genus Jaborosa to colonize newly formed habitats during Andean orogeny was associated with striking transitions in flower scent composition that trigger specific odor-driven behaviors in nocturnal hawkmoths and saprophilous fly pollinators.Fil: More, Marcela. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto Multidisciplinario de Biología Vegetal. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas Físicas y Naturales. Instituto Multidisciplinario de Biología Vegetal; ArgentinaFil: Soteras, María Florencia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto Multidisciplinario de Biología Vegetal. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas Físicas y Naturales. Instituto Multidisciplinario de Biología Vegetal; ArgentinaFil: Ibañez, Ana Clara. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto Multidisciplinario de Biología Vegetal. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas Físicas y Naturales. Instituto Multidisciplinario de Biología Vegetal; ArgentinaFil: Dötterl, Stefan. Paris-lodron-university Of Salzburg; AustriaFil: Cocucci, Andrea Aristides. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto Multidisciplinario de Biología Vegetal. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas Físicas y Naturales. Instituto Multidisciplinario de Biología Vegetal; ArgentinaFil: Raguso, Robert A.. Cornell University, Dept. Of Neurobiology And Behavior; Estados Unido

International Manufacturing Networks Supply Strategy Design Aided by Simulation Tools: An Empirical Study in the Wind Sector

[ENG] In the last decades, many manufacturing companies are suffering a trend toward multisite location and greater fragmentation of theirs productive and logistic processes. This fact out lights that the open of boundaries in Eastern Europe and the irruptions of countries in the global trade economy, have forced to develop value added activities such as engineering, purchasing, manufacturing and assembly in different places, even in different countries

Simulation in development of skilled and competent operators

Modelling and Simulation helps industry to get information about how something will behave without actually testing it in real life in real industry scenario which will incur cost. One can compress the time frame, and study the behaviour of a scenario without engaging it. The use of this within engineering is well recognized. It became necessity or need in an industry. It plays various roles, from fulfilling the requirement in front end task up to furnishing the needed areas in back end task. In a petrochemical plant especially in Ethylene crackers, training operators to operate plant safely and consistent is a need. Highernumber in employees 'migration does play a role in a need of training simulator. When an operator with many years of experience left the company, he brings with himself a valuable portion of knowledge and data and training new personnel will incur money and time cost. The training of ethylene plant new operators now need to rely on senior operators experiences from different plant life cycle and will vary with different trainers. Need of simulation that can represent the real world scenario is a mandatory to give a valuable training experience and loss of billions dollars can be avoided

The Impact of Interest Rates on the Development of an Emerging Market: Empirical Evidence of Nigeria.

The study reveals that interest rate is always difficult to forecast. Interest rates will probably rise with the removal of public sector funds from the industry. The interest rate (MPR) is the rate at which banks borrow from Central Bank to cover their immediate cash shortfall. The higher the cost of such borrowing, the higher also will be the rate banks will advance credit to the real sector. However, in the long-term, with re-capitalization on banks, insurance companies’ e.g. could begin to exploit economies of scale to compete on pricing and improve their deposit mobilization capabilities, which could positively affect interest rates. The Central Bank of Nigeria (CBN) has not formulated a model that will reduce interest rate, inflation and stabilize the exchange rate. However, a time series analysis was adopted for 40 years (1970- 2010).The Error Correction Modelling (ECM) was adopted to reconcile fluctuations or changes both in the short and long run between the variables. The result shows that due to the ability to estimates the parameters of Error Correction Mechanism (ECM), which is generally consistent, sufficient, significant and negative. The non-zero coefficient of INTt and INFt in both ways, if statistically significant, will indicate a short-run causality from INTt to Gcft as well as INFt to GDPt. The paper recommends that pragmatic approach needs to be adopted to ensure that the lending rates are reduced to single digit in order to reduce production cost, high unemployment rate and encourage Foreign Direct Investment (FDI). The monetary policy rate (MPR) at 12% (CBN, 2013) is too high for a developing economy such as Nigeria because it will have a negative impact on the naira exchange rate. Monetary and fiscal policies remain necessary and sufficient conditions for attaining a realistic interest rate performance. Interest rate management in a depressionary economy needs regular fine-tuning of relevant instruments by the monetary authorities. Keywords: Interest rate, Capital formation, Inflation, Monetary and fiscal policy, Central bank

A deep learning framework based on Koopman operator for data-driven modeling of vehicle dynamics

Autonomous vehicles and driving technologies have received notable attention in the past decades. In autonomous driving systems, \textcolor{black}{the} information of vehicle dynamics is required in most cases for designing of motion planning and control algorithms. However, it is nontrivial for identifying a global model of vehicle dynamics due to the existence of strong non-linearity and uncertainty. Many efforts have resorted to machine learning techniques for building data-driven models, but it may suffer from interpretability and result in a complex nonlinear representation. In this paper, we propose a deep learning framework relying on an interpretable Koopman operator to build a data-driven predictor of the vehicle dynamics. The main idea is to use the Koopman operator for representing the nonlinear dynamics in a linear lifted feature space. The approach results in a global model that integrates the dynamics in both longitudinal and lateral directions. As the core contribution, we propose a deep learning-based extended dynamic mode decomposition (Deep EDMD) algorithm to learn a finite approximation of the Koopman operator. Different from other machine learning-based approaches, deep neural networks play the role of learning feature representations for EDMD in the framework of the Koopman operator. Simulation results in a high-fidelity CarSim environment are reported, which show the capability of the Deep EDMD approach in multi-step prediction of vehicle dynamics at a wide operating range. Also, the proposed approach outperforms the EDMD method, the multi-layer perception (MLP) method, and the Extreme Learning Machines-based EDMD (ELM-EDMD) method in terms of modeling performance. Finally, we design a linear MPC with Deep EDMD (DE-MPC) for realizing reference tracking and test the controller in the CarSim environment.Comment: 12 pages, 10 figures, 1 table, and 2 algorithm

Environmental Odour

Environmental odour is perceived as a major nuisance by rural as well as urban populations. The sources of odourous substances are manifold. In urban areas, these include restaurants, small manufacturing trades, and other sources, which might cause complaints. In the suburbs, wastewater treatment plants, landfill sites, and other infrastructures are the expected major odour sources. These problems are often caused be the accelerated growth of cities. In rural sites, livestock farming and the spreading of manure on the fields is blamed for severe odour annoyance. In fact, environmental odours are considered to be a common cause of public complaints by residents to local authorities, regional, or national environmental agencies. This Special Issue of Atmosphere will address the entire chain, from the quantification of odour sources, abatement methods, the dilution in the atmosphere, and the assessment of odour exposure for the assessment of annoyance. In particular, this Special Issue aims to encourage contributions dealing with field trials and dispersion modeling to assess the degree of annoyance and the quantitative success of abatement measures