Approximate Expressions to Evaluate the Performance in Butene-1 Purification Units

1 INTRODUCTIONSelective hydrogenatioll of small amounts of butynes and butadiene is industrially employedfor obtaining high purity butene-l used as co-monomer in the production of linear low-densitypolyethyene.For this purpose,the content of vinylacetylene.butyne-l and 1,3-butadiene presentin the process stream should be reduced to a few tens of ppm.     

Particle loss: An initial investigation into size effects and stress-dilatancy

Drained triaxial tests have been performed to explore the effect of particle loss on shearing behaviour and critical states in granular mixtures. The mixtures comprise Leighton Buzzard sand (d₅₀ = 0.8 mm), to which was added 15% by mass of salt particles of different nominal sizes: 0.063 mm, 0.25 mm and 0.5 mm. Shearing behaviours before and after particle loss (by dissolution) were compared. A good fit is observed between the test data and a stress-dilatancy relationship for the post-dissolution tests, highlighting the ability of the stress-dilatancy analysis as a means to interpret the effects of particle loss on shearing. It was noted that critical state strength parameter M is determined by the post-dissolution grading regardless of size of removed particle. However, the duration of contractant volumetric strain increased with the larger removed particles (0.25 mm & 0.5 mm) even when initial specific volumes were virtually identical. It is suggested that a loose volumetric state is reached if the sand particle network is initially disrupted by the amount and/or size of salt particles, which following dissolution results in structural or fabric phenomena that are not reflected in scalar volumetric measures such as specific volume.     

BETaaS: A Platform for Development and Execution of Machine-to-Machine Applications in the Internet of Things

Wireless Personal Communications - The integration of everyday objects into the Internet represents the foundation of the forthcoming Internet of Things (IoT). Smart objects will be the building...     

A time Petri net-based method for embedded hard real-time software synthesis

Over the last few years, embedded software synthesis has drawn much attention. However, few works deal with software synthesis for hard real-time systems considering arbitrary inter-tasks precedence and exclusion relations. Code generation for meeting all timing and resource constraints is not a trivial task. Thus, this research area has several open issues, mainly related to generation of predictable-guaranteed scheduled code. The method proposed in this paper starts from a high-level specification, and automatically translates such specification into a time Petri net model; this model is adopted for finding a feasible static schedule meeting all constraints. If found, the approach generates a scheduled code, based on the found feasible schedule. Therefore, the user just enter the specification and receives, as result, the scheduled code. Thus, all intermediary phases are hidden from the users.     

Survey and comparison of message authentication solutions on wireless sensor networks

Security is an important concern in any modern network. This also applies to Wireless Sensor Networks (WSNs), especially those used in applications that monitor sensitive information (e.g., health care applications). However, the highly constrained nature of sensors imposes a difficult challenge: their reduced availability of memory, processing power and energy hinders the deployment of many modern cryptographic algorithms considered secure. For this reason, the choice of the most memory-, processing- and energy-efficient security solutions is of vital importance in WSNs. To date, a number of extensive analyses comparing different encryption algorithms and key management schemes have been developed, while very little attention has been given to message authentication solutions. In this paper, aiming to close this gap, we identify cipher-based Message Authentication Codes (MACs) and Authenticated Encryption with Associated Data (AEAD) schemes suitable for WSNs and then evaluate their features and performance on a real platform (TelosB). As a result of this analysis, we identify the recommended choices depending on the characteristics of the target network and available hardware.     

Suspended Silicon Microphotodiodes for Electrochemical and Biological Applications

Local electric stimulation of tissues and cells has gained importance as therapeutic alternative in the treatment of many diseases. These alternatives aim to deliver a less invasively stimuli in liquid media, making imperative the development of versatile micro‐ and nanoscale solutions for wireless actuation. Here, a simple microfabrication process to produce suspended silicon microphotodiodes that can be activated by visible light to generate local photocurrents in their surrounding medium is presented. Electrical characterization using electrical probes confirms their diode behavior. To demonstrate their electrochemical performance, an indirect test is implemented in solution through photoelectrochemical reactions controlled by a white‐LED lamp. Furthermore, their effects on biological systems are observed in vitro using mouse primary neurons in which the suspended microphotodiodes are activated periodically with white‐LED lamp, bringing out observable morphological changes in neuronal processes. The results demonstrate a simplified and cost‐effective wireless tool for photovoltaic current generation in liquid media at the microscale.     

Direct Determination of Trace Elements in Meat Samples via High-Resolution Graphite Furnace Atomic Absorption Spectrometry

This work presents a direct and straightforward approach for the determination of trace elements in fish muscle, oyster, and bovine liver via direct solid sample analysis (SS) using high-resolution continuum source graphite furnace atomic absorption spectrometry (HR-CS GF AAS). The preliminary studies revealed the presence of spectral interferences at the analytical line of Ni at 231.096 nm, which could be corrected subtracting the spectrum of SiO and PO from the sample spectra using least-squares background correction. Moreover, all meat samples were proven homogeneous according to the homogeneity factor (H _e) (all values were <10 mg^½). Pyrolysis (Tp) and atomization (Ta) temperatures were studied and optimized as 800 °C (Tp) and 2500 °C (Ta) for Mn, 700 °C (Tp) and 2600 °C (Ta) for Ni, and 600 °C (Tp) and 2500 °C (Ta) for Rb. Calibration against aqueous standards was proven feasible for Mn determination, whereas Ni and Rb required calibration against solid standards for their quantification. The detection limits achieved were demonstrated adequate for application to food analysis (0.005 μg g^?1 for Mn, 0.002 μg g^?1 for Ni, and 0.1 μg g^?1 for Rb). The developed method was successfully applied for the elemental analysis of fish muscle, oyster, and bovine liver and three certified reference materials, demonstrating good agreement with the certified values and with the reference technique at a 95 % statistical confidence level.     

Enhanced spherulite growth rates of isotactic polypropylene in incompatible blends

Isothermal radial growth rates (G) of isotactic polypropylene (iPP) spherulites in immiscible blends with a polyethylene based ionomer (1) partially neutralized with Zn⁺², (2) completely acidified, and (3) completely esterified have been determined at crystallization temperatures between 118 and 124°C by time-lapse photomicroscopy. In these blends iPP spherulites grow with increased G as compared to that of pure iPP. This behavior is attributed to increases in the rate of transport, due to limited miscibility induced by mechanical mixing. However, subtle differences in the melting behavior suggest that changes in Spherulite morphology may also be a contributing factor.     

Automatic routine tuning to represent landform attributes on multicore and multi-GPU systems

Auto-tuning techniques have been used in the design of routines in recent years. The goal is to develop routines which automatically adapt to the conditions of the computational system in such a way that efficient executions are obtained independently of the end-user experience. This paper aims to explore programming routines that can be automatically adapted to the computational system conditions, making possible to use auto-tuning to represent landform attributes on multicores and multi-GPU systems using high- performance computing techniques for efficient solution of two-dimensional polynomial regression models that allow large problem instances to be addressed.