Inline method of droplet and particle size distribution analysis in dilute disperse systems

In the present article a measurement method of particle size distributions (PSD) in industrial installations which use a dispersed phase of low concentration (like spray dryers or spray scrubbers) is introduced. A new type of inline-measurement system has been developed and designed to work in spray drying conditions. A standard digital camera is used to record shadows of flowing particles inside the spray drying chamber. Collected images were analyzed by a newly developed software which recognizes particles only in the focus area and eliminates several types of artifacts. The constructed prototype of the PSD inline-analyzer was installed and used to monitor large laboratory scale spray dryer. All data collected by the designed system during the spray drying experiments were compared with data measured with an offline reference system to show accuracy of the new measurement technique.     

CFD modelling of moisture evaporation in an industrial dispersed system

A methodology is presented here for the mathematical modelling of moisture evaporation in a dispersed system in an industrial tower. An empirical model using characteristic drying curves was applied to calculate moisture evaporation from a droplet and particle. A simple method was developed to calculate the agglomeration process of the dispersed phase in the drying towers, using transient functions between the initial and final particle size distributions, at the nozzle and in the final product. The developed model and simulation results were validated on the basis of industrial spray tower experiments. High instability of the airflow due to the geometry of the dryer and the construction of the air inlets was observed. The general methodology applied within this CFD model is universal, and can be applied to the scaling-up of installations for dewatering in dispersed systems in order to determine configurations of feeding systems and control the product quality and safety of the process.     

The VFO-Driven Motion Planning and Feedback Control in Polygonal Worlds for a Unicycle with Bounded Curvature of Motion

Integrated motion planning and control for the purposes of maneuvering mobile robots under state- and input constraints is a problem of vital practical importance in applications of mobile robots such as autonomous transportation. Those constraints arise naturally in practice due to specifics of robot mechanical construction and the presence of obstacles in motion environment. In contrast to approaches focusing on feedback control design under the assumption of given reference motion or motion planning with neglection of subsequent feedback motion execution, we adopt a controller-driven motion planning paradigm, which has recently gained attention of many researchers. It postulates design of motion planning algorithms dedicated to specific feedback control policies, which compute a sequence of feedback control subtasks instead of classically planned open-loop controls or parametric paths. In this spirit, we propose a motion planning algorithm driven by the VFO (Vector Field Orientation) control law for the waypoint-following task. Presented analysis of the VFO control law reveals its beneficial properties, which are subsequently utilized to solve a generally nonlinear and non-convex optimal motion planning problem by formulating it as a mixed-integer linear program (MILP). The solution proposed in this paper yields a waypoint sequence, which is designed for execution by application of the VFO control law to drive a robot to a prescribed final configuration under an input constraint imposed by bounded curvature of robot motion and state constraints resulting from a convex decomposition of task space. Satisfaction of these constraints is guaranteed analytically and exactly, i.e., without utilization of numerical approximations. Moreover, for a given discrete set of possible waypoint orientations, the proposed algorithm computes plans optimal w.r.t. given cost functional, which can be any convex linear combination of quantities such as robot path length, curvature of robot motion, distance to imposed state constraints, etc. Furthermore, the planning algorithm exploits the possibility of both forward or backward movement of the robot to allow maneuvering in demanding environments. Generated waypoint sequences are a compact representation of a motion plan, which can be immediately executed with the VFO controller without any additional post-processing. Validity of the proposed approach has been confirmed by simulation studies and experimental motion execution with a laboratory-scale mobile robot.     

Learning Detail Transfer based on Geometric Features

The visual richness of computer graphics applications is frequently limited by the difficulty of obtaining high‐quality, detailed 3D models. This paper proposes a method for realistically transferring details (specifically, displacement maps) from existing high‐quality 3D models to simple shapes that may be created with easy‐to‐learn modeling tools. Our key insight is to use metric learning to find a combination of geometric features that successfully predicts detail‐map similarities on the source mesh; we use the learned feature combination to drive the detail transfer. The latter uses a variant of multi‐resolution non‐parametric texture synthesis, augmented by a high‐frequency detail transfer step in texture space. We demonstrate that our technique can successfully transfer details among a variety of shapes including furniture and clothing.     

DelayDroid: an instrumented approach to reducing tail-time energy of Android apps

Mobile devices with 3G/4G networking often waste energy in the so-called “tail time” during which the radio is kept on even though no communication is occurring. Prior work has proposed policies to reduce this energy waste by batching network requests. However, this work is challenging to apply in practice due to a lack of mechanisms. In response, we have developed DelayDroid, a framework that allows a developer to add the needed policy to existing, unmodified Android applications (apps) with no human effort as well as no SDK/OS changes. This allows such prior work (as well as our own policies) to be readily deployed and evaluated. The DelayDroid compile-time uses static analysis and bytecode refactoring to identify method calls that send network requests and modify such calls to detour them to the DelayDroid run-time. The run-time then applies a policy to batch them, avoiding the tail time energy waste. DelayDroid also includes a cross-app communication mechanism that supports policies that optimize across multiple apps running together, and we propose a policy that does so. We evaluated the correctness and universality of the DelayDroid mechanisms on 14 popular Android apps chosen from the Google App Store. To evaluate our proposed policy, we studied three DelayDroid-enabled apps (weather forecasting, email client, and news client) running together, finding that the DelayDroid mechanisms combined with our policy can reduce 3G/4G tail time energy waste by 36%.     

Quantitative determination of the iodine values of unsaturated plant oils using infrared and Raman spectroscopy methods

Thirteen edible oils: sunflower, avocado, hemp, high-linolenic flax, low-linolenic flax, safflower, walnut, roasted sesame, rice, corn, rapeseed, pumpkin seed, and hazel were studied in this work. Their fatty acid composition, iodine, acidic, peroxide, and saponification values were determined. Infrared and Raman spectra of the oils were recorded in the range 400–3200 cm^?1. The integral intensities of the bands at about 1655 and 2852 cm^?1 corresponding to ν(C=C) and ν(CH₂) vibrations were evaluated and used to construct a relationship between the spectroscopic data and the iodine value. The following linear dependencies were obtained: I_ν(C=C)/I_ν(CH2) = 7.449 × 10^?4 × iodine value – 0.0339 and I_ν(C=C)/I_ν(CH2) = 9.299 × 10^?4 × iodine value – 0.023 for the infrared and Raman spectra with a correlation coefficient 0.988 and 0.976, respectively. These calibration lines can be used to determine the iodine value for oils with unknown unsaturation level, and may be applied for margarines and other fatty materials.     

Reproducible comet assay of amorphous silica nanoparticles detects no genotoxicity

Genotoxicity of commercial colloidal and laboratory-synthesized silica nanoparticles was tested using the single cell gel electrophoresis or Comet assay. By using a carefully developed protocol and careful characterization of the nanoparticle dispersions, Comet assays were performed on 3T3-L1 fibroblasts with 3, 6, and 24 h incubations and 4 or 40 microg/ml of silica nanoparticles. No significant genotoxicity was observed for the nanoparticles tested under the conditions described, and results were independently validated in two separate laboratories, showing that in vitro toxicity testing can be quantitatively reproducible.     

Energy-efficient Rate Adaptation MAC Protocol for Ad Hoc Wireless Networks

In this paper, two novel energy-efficient rate adaptation schemes are presented. The proposed protocols use the Distributed Power Control (DPC) algorithm to predict the channel state and determine the necessary transmission power which optimizes the energy consumption. The first proposed rate adaptation scheme heuristically alters the modulation rate to balance the energy-efficiency and the required throughput which is estimated with queue fill ratio. Moreover, the back-off scheme is incorporated to mitigate congestion and reduce packet losses due to buffer overflows thus minimizing energy consumption. Consequently, the nodes will conserve energy when the traffic is low, offer higher throughput when needed and save energy during congestion by limiting transmission rates. The second rate adaptation scheme employs dynamic programming (DP) principle to analytically select modulation rate and a burst size to be used during transmission. The proposed quadratic cost-function minimizes the energy consumption while alleviating network congestions and buffer overflows. The proposed DP solution renders a Riccati equation ultimately providing an optimal rate selection. The simulation results indicate that an increase in throughput by 96% and energy-efficiency by 131% is observed when compared to other available protocols, for example Receiver Based AutoRate (RBAR).

RAPD with microsatellite as a tool for differentiation of Candida genus yeasts isolated in brewing

Fifteen wild yeast strains were isolated in two factories of a lager brewing company in Poland. Their identification with API 32C system showed mainly the presence of Candida sake species (7/15). To differentiate the isolates, randomly amplified polymorphic DNA (RAPD) with (GTG)(5), (GAC)(5), (GACA)(4) microsatellite primers and M13 core sequence (5'-GAG GGT GGC GGT TCT-3') were chosen. The results of patterns similarity are presented as dendrograms for each RAPD analysis and for overall patterns. On the overall patterns, all isolates identified as C. sake, except Strain No. 1, were regrouped in one cluster. Collection strain C. sake CBS 617 was similar in 46% to the cluster with six isolates (Strain Nos. 3, 6, 8, 11, 13, 14). The second reference strain C. sake CBS 159 and the Strain No. 1 were regrouped with other Candida species (collection strains) showing, respectively, only 20% and 42% of similarity to other C. sake strains. The similarity based on the overall dendrogram between isolate Nos. 3, 6, 8, 11, 13, 14 and C. sake CBS 617 was 49%. Between those strains and other Candida, the similarity was only 37%.