Design improvements on rotary valve particle feeders used for obtaining suspended airflows

The back repulsion of low density particles, sticking of particles in feeder valve and interlocking and cohesive archs of particles in feeder hopper have been widely observed problems of a conventional rotary valve feeder used for feeding of granular particles into an airflow line. In this study, these problems of the rotary valve feeders were isolated by means of novel modifications to its conventional design. Results of the modifications showed that the modified feeder can be sensitively used to feed granular particles with mass feeding rates ranging between 5±0.15 and 85±0.85 g/s without encountering problems experienced with conventional rotary valves.     

Effect of high hydrostatic pressure on physicochemical and biochemical properties of milk

Interest in high hydrostatic pressure (HHP) applications on milk and dairy products has recently increased as HHP offers a new technology for food preservation to the food industry. Although HHP-induced microbial destruction, rennet or acid coagulation of milk and increase in cheese yield has been reported, the actual effect of HHP application on milk constituents still remains to be unexplained. Therefore, we have analyzed the effect of HHP on physicochemical and biochemical properties such as turbidity, pH and especially protein micelle surface hydrophobicity of milk proteins. To serve for this purpose, milk samples with different fat contents were pressurized from 110 to 440 MPa at 25 °C for 10 and 20 min. Turbidity decreased with pressure increase and there was a slight change in pH. In order to measure the extent of exposure of hydrophobic groups of proteins to HHP, the method described by Bonomi et al. [1], based on use of a fluorescent probe, was utilized. In the light of the results obtained, it can be concluded that HHP has an effect on non-covalent interactions and especially hydrophobic bonds in milk. As the pressure is increased from 110 to 440 MPa, the micelles possibly decompose into sub-micelles and the embedded hydrophobic areas inside these micelles re-position in such a way that they can readily interfere with the fluorescent marker, ANS. These results may lead to practical applications of HHP treatment in the dairy industry to produce microbiologically safe, minimally processed products with high nutritional and sensory quality and novel texture.     

PHASE EQUILIBRIUM FOR TERNARY LIQUID SYSTEMS OF WATER CARBOXYLIC ACID CHLORINATED HYDROCARBON: THERMODYNAMIC MODELING THROUGH SERLAS

Liquid-liquid equilibrium data of the solubility (binodal) curves and tie-line end compositions are presented for mixtures of [water (1) + formic acid, or acetic acid, or propanoic acid (2) + chlorobenzene, or 1,2-dichloroethane (3)] at T = 293.2 K and P = 101.3 ± 0.7 kPa. A log-basis approach, SERLAS (solvation energy relation for liquid-associated system), has been proposed to estimate the properties and liquid-liquid equilibrium (LLE) of associated systems containing proton-donating and -accepting and polar components capable of a physical interaction through hydrogen bonding or dipole-dipole interaction. The tie lines were also correlated using the UNIFAC-original model. The reliability of the models has been analyzed against the LLE data with respect to the distribution coefficient and separation factor. The proposed model appears to be an improvement in data fit for the ternary systems, yielding a mean relative error of 10.1% for all the systems considered.     

Fabrication of chitosan/polyvinyl alcohol/amine modified carbon nanotube composite films for rapid chromate removal

Composite adsorbent films with amine and hydroxyl functionalities were synthesized from chitosan (CS), polyvinyl alcohol (PVA), and amine-modified carbon nanotubes (a-MWCNT) by solvent casting method. Weight proportions of CS to PVA and weight percent of a-MWCNT were optimized to achieve highest chromate removal capacity. Structural characteristics of the composites were investigated using scanning electron microscopy, Fourier transform infrared spectroscopy, Raman spectroscopy, and thermal gravimetric analysis. Accordingly, incorporation of a-MWCNT to CS/PVA structure resulted in the generation of nanochannels, which enhanced adsorption capacity. Moreover, the composite comprising 0.4% wt. a-MWCNT provided over 99% of Cr (VI) removal from 50 mg L⁻¹ Cr (VI) solution within five minutes of contact time. Redlich–Peterson and Radke–Prausnitz isotherm models provided the highest conformity to adsorption data. Maximum chromate sorption capacity of CS/PVA/a-MWCNT composite film was determined as 134.2 mg g⁻¹ being 172% higher than that of CS/PVA. Regeneration was best achieved in 1.0 M NaOH and the composite was shown to retain at least 70% of its original capacity after five consecutive adsorption–desorption cycles.     

An on-chip cell culturing and combinatorial drug screening system

A low-cost, convenient and precise drug combination screening microfluidic platform is developed, in which cell culture chambers designed with micropillars integrate with three laminar flow diffusion channels. This platform has several distinct features, including minimum shear stress on cells, biocompatibility, optimum concentration distribution and automatic combinatorial gradient generation, which can potentially speed up the discovery of an effective drug combination for cancer ablations. The presented device can generate two-drug combination gradients at the optimum flow rate of 90 μL/h and can be applied to identify the optimal combination of two clinically relevant chemotherapy drugs. For demonstration, paclitaxel at 0.77 × 10^?3 mg/mL and cisplatin at 0.23 × 10^?4 mg/mL were studied against lung cancer cells (A549). This microfluidic device has the potential to provide a precise and robust screening for anticancer combinational drugs practiced in clinics.     

Converting numerical classification into text classification

Consider a supervised learning problem in which examples contain both numerical- and text-valued features. To use traditional feature-vector-based learning methods, one could treat the presence or absence of a word as a Boolean feature and use these binary-valued features together with the numerical features. However, the use of a text-classification system on this is a bit more problematic—in the most straight-forward approach each number would be considered a distinct token and treated as a word. This paper presents an alternative approach for the use of text classification methods for supervised learning problems with numerical-valued features in which the numerical features are converted into bag-of-words features, thereby making them directly usable by text classification methods. We show that even on purely numerical-valued data the results of text classification on the derived text-like representation outperforms the more naive numbers-as-tokens representation and, more importantly, is competitive with mature numerical classification methods such as C4.5, Ripper, and SVM. We further show that on mixed-mode data adding numerical features using our approach can improve performance over not adding those features.     

Strategic effort allocation in online innovation tournaments

Online innovation tournaments, such as those hosted by crowdsourcing platforms (e.g., Kaggle), have been widely adopted by firms to evolve creative solutions to various problems. Solvers compete in these tournaments to earn rewards. In such competitive environments, it is imperative that solvers provide creative solutions with minimum effort. This article explores the factors that influence the solvers’ effort allocation decisions in a dynamic tournament setting. Specifically, comprehensive time variant data of teams that participated in crowdsourcing competitions on Kaggle were analyzed to gain insight into how solvers continually formulate strategies in light of performance feedback obtained through interim ranking. The results suggest that solvers strategically allocate their efforts throughout the contest to dynamically optimize their payoffs through balancing the probability of winning and the cost of expending effort. In particular, solvers tend to increase their efforts toward the end of tournaments or when they get closer to winning positions. Furthermore, our findings indicate that a last-minute surge in effort is more prevalent among high-skill solvers than in those with lower skill levels. In addition to providing insights that may help solvers develop strategies to improve their performance, the study has implications for the design of online crowdsourcing platforms, particularly in terms of incentivizing solvers to put forth their best effort.     

Magnetically controlled shape-memory effects of hybrid nanocomposites from oligo(ω-pentadecalactone) and covalently integrated magnetite nanoparticles

The covalent integration of inorganic nanoparticles in polymer matrices has gained significance for improving the structural properties of polymer-based materials. Here we report on the performance of poly(ω-pentadecalactone) networks with magnetite nanoparticles as netpoints in their magnetically-controlled shape-memory capability. Hybrid nanocomposites with magnetite nanoparticle content ranging from 5 to 11 wt% were prepared by reacting two types of oligo(ω-pentadecalactone) (OPDL) based precursors with terminal hydroxy groups, a three arm OPDL (³AOPDL, M_n = 6000 g mol⁻¹) and an OPDL (M_n = 3300 g mol⁻¹) coated magnetite nanoparticle (∅ = 10 nm), with a diisocyanate. Homogenous hybrid nanocomposites were obtained independent from the weight content of the OPDL decorated nanoparticles in the samples. At 100 °C (T > T_m-OPDL) the covalent integration of the nanoparticles increased the mechanical strength with increasing weight content whereby the elasticity remained almost constant. In magnetically-controlled one-way dual-shape experiments the shape fixity decreased from 95% to 90% but the shape recovery increased slightly from 95% to 97% when the nanoparticle content was increased. In magnetically-controlled reversible dual-shape experiments the nanoparticles had a restraining effect and the maximum shape-change of 65% for hybrid nanocomposites with 5 wt% magnetite nanoparticles was reduced to 36% when the particle content was increased to 11 wt%. These results show that the performance of hybrid nanocomposites can be tailored by nanoparticle content, however in terms of their applicability either mechanical strength or actuation capability should be focussed in the material selection.     

Modeling of Thermal Performance of a Cooling Tower Using an Artificial Neural Network

Abstract

In the present study, the ability of an artificial neural network model to evaluate the thermal performance of a cooling tower, which used in the heating, ventilating, and air conditioning industries to reject heat to the atmosphere, is examined. The network is trained with the following experimental values: the ratio of the water mass flow rate to air mass flow rate, the inlet water temperature, and the outlet water temperature, and the inlet air wet-bulb temperature are selected as input variables, while the output is the coefficient of performance. It is concluded that a well-trained neural network provides fast, accurate, and consistent results, making it an easy-to use tool for preliminary engineering studies.     

Determination of the energy savings and the optimum insulation thickness in the four different insulated exterior walls

The optimum insulation thickness of the external wall for four cities from four climate zones of Turkey, energy savings over a lifetime of 10 years and payback periods are calculated for the five different energy types and four different insulation materials applied externally on walls. Extruded polystyrene, expanded polystyrene, nil siding and rock wool as wall insulation material are selected. In this study, the net energy cost savings are calculated using the P₁–P₂ method. The results show that energy cost savings vary between 4.2 $/m² and 9.5 $/m² depending on the city and insulation materials. The highest payback period value with 2.25 years in Mersin found by using natural gas as an energy source for heating, while the lowest value is reached by using LPG as an energy source in Bitlis.