Technological and sensorial properties of liquid nitrogen ice cream enriched with protein from brewing waste (trub)

Debittered trub (brewing waste) is an important source of protein source (70.26%). Trub and whey protein were used for 5% protein enrichment of ice cream frozen by liquid nitrogen. Three formulations were elaborated: ice cream standard (ICS), ice cream with whey protein (ICW) and ice cream with trub (ICT). Chemical composition, rheological properties, texture, overrun, melting rate, scanning electron microscopy and a sensorial test were performed. Results showed that ICT presented a higher viscosity, obtained on the upward curve up to 6.76 Pa s⁻¹, consistency index (22.96 (Pa s⁻¹)ⁿ), hysteresis area (140.40 mPa s⁻¹) and hardness (31113.33 g) but a lower melting rate (0.38 g min⁻¹), overrun (13.92%) and sensorial acceptability than the other formulations. The addition of trub debittered for protein enrichment improved ice cream properties and demonstrated that it could be used as a food ingredient.     

In-tube condensation of mixture of R134a and ester oil: empirical correlations

This paper presents a comparative study of the condensation heat transfer coefficients in a smooth tube when operating with pure refrigerant R134a and its mixture with lubricant Castrol “icematic sw”. The lubricant is synthetic polyol ester based oil commonly used in lubricating the compressors. Two concentrations of R134a-oil mixtures of 2% and 5% oil (by mass) were analysed for a range of saturation temperatures of refrigerant R134a between 35 °C and 45 °C. The mass flow rate of the refrigerant and the mixtures was carefully maintained at 1 g/s, with a vapour quality varying between 1.0 and 0. The effects of vapour quality, flow rate, saturation temperature and temperature difference between saturation and tube wall on the heat transfer coefficient are investigated by analysing the experimental data. The experimental results were then compared with predictions from earlier models [Int J Heat Mass Transfer (1979), 185; 6th Int Heat Transfer Congress 3 (1974) 309; Int J Refrig 18 (1995) 524; Trans ASME 120 (1998) 193]. Finally two new empirical models were developed to predict the two-phase condensation heat transfer coefficient for pure refrigerant R134a and a mixture of refrigerant R134a with Castrol “icematic sw”.     

Fabrication of an optically driven pH gradient generator based on self-assembled proton pumps

Optically manipulating the local pH of a target solution in a microchannel, or reservoir, provides a mechanism for activating and controlling a variety of biological and chemical processes on Lab-on-a-Chip (LOC) devices and micro-total analysis systems (μ-TAS). A microscale pH gradient generator that exploits the light-activated molecular proton pumps found in the purple membranes (PM) of bacteriorhodopsin is described in this paper. The photo-electro-chemical transducer is an ultrathin layer (~13?nm) of oriented PM patches self-assembled on an Au-coated porous substrate. A biotin labeling and streptavidin molecular recognition technique is used to ensure that the extracellular side of all PM patches is attached to the porous substrate enabling unidirectional and efficient transport of ions across the transducer surface. The photo-induced proton pumps generate a flow of ions that produce a measurable change in pH between the separated solutions. The self-assembly procedure is experimentally quantified based on the capacitance characteristics of the bR membranes. The investigation confirms that the transducer is covered with the bR proton pumps at a mass density of 2.33?ng/cm². Experimental tests also show that the proposed transducer can repeatedly generate pH gradients as high as 0.42 and absolute voltage differences as high as 25?mV when illuminated by an 18?mW, 568?nm light source. Furthermore, the ΔpH is observed to be nonlinear with respect to light intensity and exposure time. The ΔpH of the target solution is sufficient to cause a phenolphthalein indicator dye to change color or an ionic hydrogel micro-valve to expand.     

Dynamic modulus of rubber by impact and rebound measurements

When rubber is deformed an energy input is involved which is released in part when the rubber returns to its original shape. The part which is not returned as mechanical energy is dissipated as heat. The “rebound resilience” is defined as the ratio of the energy returned to the energy applied for deformation by an indentation due to a single impact. In this experiment, a pendulum mass and a test piece, as long as they are in contact, may be considered an oscillating system having one degree of freedom in which the rubber is a Voigt model. The correlation between rebound resilience and loss angle of the rubber may thus be derived. The measurement of the contact time between pendulum indentor tip and rubber surface, in addition to the rebound resilience, allows calculation of deformation, speed and acceleration of the damped sinusoidal motion. The penetration of the spherical indentor under a constant force depends on Young's modulus. Scott found an empirical relationship among force applied, depth of indentation, radius of the indentor tip and the modulus. This relationship has been recently improved by Stiehler and coworkers, The Stiehler formula has been used here for evaluating the storage modulus of rubber vulcanizates by using the maximum force transmitted by the impacting mass and the indentation depth of the test piece at the same time.     

The effectiveness of Light Rail transit in achieving regional CO<Subscript>2</Subscript> emissions targets is linked to building energy use: insights from system dynamics modeling

Cities worldwide face the challenges of accommodating a growing population, while reducing emissions to meet climate mitigation targets. Public transit investments are often proposed as a way to curb emissions while maintaining healthy urban economies. However, cities face a system-level challenge in that transportation systems have cascading effects on land use and economic development. Understanding how an improved public transit system could affect urban growth and emissions requires a system-level view of a city, to anticipate side effects that could run counter to policy goals. To address this knowledge gap, we conducted a case study on the rapidly growing Research Triangle, North Carolina (USA) region, which has proposed to build a Light Railway by 2026 along a heavily used transportation corridor between the cities of Durham and Chapel Hill. At the same time, Durham County has set a goal of lowering greenhouse gas emissions by 30% from a 2005 baseline by 2030. In collaboration with local stakeholders, we developed a system dynamics model to simulate how Light Rail transit and concurrent policies could help or hinder these sustainable growth goals. The Durham–Orange Light Rail Project (D–O LRP) model simulates urban–regional dynamics between 2000 and 2040, including feedbacks from energy spending on economic growth and from land scarcity on development. Counter to expectations, model scenarios that included Light Rail had as much as 5% higher regional energy use and CO₂ emissions than business-as-usual (BAU) by 2040 despite many residents choosing to use public transit instead of private vehicles. This was largely due to an assumption that Light Rail increases demand for commercial development in the station areas, creating new jobs and attracting new residents. If regional solar capacity grew to 640 MW, this would offset the emissions growth, mostly from new buildings, that is indirectly due to Light Rail. National trends in building and automobile energy efficiency, as well as federal emissions regulation under the Clean Power Plan, would also allow significant progress toward the 2030 Durham emissions reduction goal. By simulating the magnitude of technology and policy effects, the D–O LRP model can enable policy makers to make strategic choices about regional growth.     

FT-NIR spectroscopy for the quality characterization of apricots (Prunus armeniaca L.)

Abstract: The nondestructive assessment of apricot fruit quality (Bora cultivar) was carried out by means of FT-NIR reflectance spectroscopy in the wavenumber range 12000 to 4000 cm⁻¹. Samples were harvested at four different ripening stages and scanned by a fiber optical probe immediately after harvesting and after a storage of 3 d (2 d at 4 °C and 1 d at 18 °C); the flesh firmness (FF), the soluble solids content (SSC), the acidity (A), and the titratable acidity (malic and citric acids) were then measured by destructive methods. Soft independent modeling of class analogy (SIMCA) analysis was used to classify spectra according to the ripening stage and the storage: partial least squares regression (PLS) models to predict FF, SSC, A, and the titratable acidity were also set-up for both just harvested and stored apricots. Spectral pretreatments and wavenumber selections were conducted on the basis of explorative principal component analysis (PCA). Apricot spectra were correctly classified in the right class with a mean classification rate of 87% (range: 80% to 100%). Test set validations of PLS models showed R² values up to 0.620, 0.863, 0.842, and 0.369 for FF, SSC, A, and the titratable acidity, respectively. The best models were obtained for the SSC and A and are suitable for rough screening; a lower power prediction emerged for the other maturity indices and the relative predictive models are not recommended. Practical Application : The results of the study could be used as a tool for the assessment of the ripening stage during the harvest and the quality during the postharvest storage of apricot fruits.     

Potent,Metabolically Stable 2‐Alkyl‐8‐(2H‐1,2,3‐triazol‐2‐yl)‐9H‐adenines as Adenosine A2A Receptor Ligands

Inhibition of adenosine A_2A receptors has been shown to elicit a therapeutic response in preclinical animal models of Parkinson’s disease (PD). We previously identified the triazolo‐9H‐purine, ST1535, as a potent A_2AR antagonist. Studies revealed that ST1535 is extensively hydroxylated at the ω‐1 position of the butyl side chain. Here, we describe the synthesis and evaluation of derivatives in which the ω‐1 position has been substituted (F, Me, OH) in order to block metabolism. The stability of the compounds was evaluated in human liver microsomes (HLM), and the affinity for A_2AR was determined. Two compounds, (2‐(3,3‐dimethylbutyl)‐9‐methyl‐8‐(2H‐1,2,3‐triazol‐2‐yl)‐9H‐purin‐6‐amine ( 3 b ) and 4‐(6‐amino‐9‐methyl‐8‐(2H‐1,2,3‐triazol‐2‐yl)‐9H‐purin‐2‐yl)‐2‐methylbutan‐2‐ol ( 3 c ), exhibited good affinity against A_2AR (K_i=0.4 nM and 2 nM , respectively) and high in vitro metabolic stability (89.5 % and 95.3 % recovery, respectively, after incubation with HLM for two hours).     

Climate policy impacts on the competitiveness of energy-intensive manufacturing sectors

This study examines the impacts of energy price changes resulting from different carbon-pricing policies on the competitiveness of selected US energy-intensive industries. It further examines possible industry responses, and identifies and provides a preliminary evaluation of potential opportunities to mitigate these impacts. The industry sectors investigated – steel, aluminum, chemicals and paper – are among the largest industrial users of fossil fuels in the US economy. The results of this examination show that climate policies that put a price on carbon could have substantial impacts on the competitiveness of US energy-intensive manufacturing sectors over the next two decades, if climate regulations are applied only in the United States, and no action is taken to invest in advanced low- and no-carbon technologies. The extent of these impacts will vary across industries, depending on their energy intensities, the mix of energy sources they rely on and how energy is used in production activities (heat and power, feedstock). Of relevance is also the speed and rigor with which industries adopt new technologies and retire (or replace) old ones. Other factors affecting these impacts include an industry's vulnerability to foreign imports and its ability to pass through cost increases to its customers in the face of international market competition.     

Multivariable predictive control of a pressurized tank using neural networks

The behavior of a multivariable predictive control scheme based on neural networks applied to a model of a nonlinear multivariable real process, consisting of a pressurized tank is investigated in this paper. The neural scheme consists of three neural networks; the first is meant for the identification of plant parameters (identifier), the second one is for the prediction of future control errors (predictor) and the third one, based on the two previous, compute the control input to be applied to the plant (controller). The weights of the neural networks are updated on-line, using standard and dynamic backpropagation. The model of the nonlinear process is driven to an operation point and it is then controlled with the proposed neural control scheme, analyzing the maximum range over the neural control works properly.     

A field orientation scheme for current-fed induction motor drivesbased on the torque angle closed-loop control

A novel field orientation scheme for current-fed induction motor drives is presented. The scheme is based on the closed-loop control of the torque angle and has the merits of being simple in implementation and insensitive to rotor resistance variations. The limits of previous field orientation schemes are reviewed. The torque angle control scheme is then formulated, and its application to induction motor (IM) drives fed by either current source inverters or current-controlled PWM inverters is illustrated. As an example, a current source inverter induction motor drive incorporating the scheme is designed, and its performance, which has been tested by simulation, is given