The effects of ethanol–unleaded gasoline blends on engine performance and exhaust emissions in a spark-ignition engine

Alcohols have been used as a fuel for engines since 19th century. Among the various alcohols, ethanol is known as the most suited renewable, bio-based and ecofriendly fuel for spark-ignition (SI) engines. The most attractive properties of ethanol as an SI engine fuel are that it can be produced from renewable energy sources such as sugar, cane, cassava, many types of waste biomass materials, corn and barley. In addition, ethanol has higher evaporation heat, octane number and flammability temperature therefore it has positive influence on engine performance and reduces exhaust emissions. In this study, the effects of unleaded gasoline (E0) and unleaded gasoline–ethanol blends (E50 and E85) on engine performance and pollutant emissions were investigated experimentally in a single cylinder four-stroke spark-ignition engine at two compression ratios (10:1 and 11:1). The engine speed was changed from 1500 to 5000 rpm at wide open throttle (WOT). The results of the engine test showed that ethanol addition to unleaded gasoline increase the engine torque, power and fuel consumption and reduce carbon monoxide (CO), nitrogen oxides (NO_x) and hydrocarbon (HC) emissions. It was also found that ethanol–gasoline blends allow increasing compression ratio (CR) without knock occurrence.     

A new facial expression recognition based on curvelet transform and online sequential extreme learning machine initialized with spherical clustering

In this paper, a novel algorithm is proposed for facial expression recognition by integrating curvelet transform and online sequential extreme learning machine (OSELM) with radial basis function (RBF) hidden node having optimal network architecture. In the proposed algorithm, the curvelet transform is firstly applied to each region of the face image divided into local regions instead of whole face image to reduce the curvelet coefficients too huge to classify. Feature set is then generated by calculating the entropy, the standard deviation and the mean of curvelet coefficients of each region. Finally, spherical clustering (SC) method is employed to the feature set to automatically determine the optimal hidden node number and RBF hidden node parameters of OSELM by aim of increasing classification accuracy and reducing the required time to select the hidden node number. So, the learning machine is called as OSELM-SC. It is constructed two groups of experiments: The aim of the first one is to evaluate the classification performance of OSELM-SC on the benchmark datasets, i.e., image segment, satellite image and DNA. The second one is to test the performance of the proposed facial expression recognition algorithm on the Japanese Female Facial Expression database and the Cohn-Kanade database. The obtained experimental results are compared against the state-of-the-art methods. The results demonstrate that the proposed algorithm can produce effective facial expression features and exhibit good recognition accuracy and robustness.     

In vitro cadmium removal from human serum by Cibacron Blue F3GA–thionein‐complex conjugated affinity membranes

A new membrane affinity biosorbent carrying thionein has been developed for selective removal of cadmium ions from human serum. Microporous poly(2‐hydroxyethyl methacrylate) (pHEMA) membranes were prepared by photopolymerization of HEMA. The pseudo dye ligand Cibacron Blue F3GA (CB) was covalently immobilized on the pHEMA membranes. Then, the cysteine‐rich metallopeptide thionein was conjugated onto the CB‐immobilized membrane. The maximum amounts of CB immobilized and thionein conjugated on the membranes were 1.07 µmol cm⁻² and 0.92 µmol cm⁻², respectively. The hydrophilic pHEMA membrane had a swelling ratio of 58% (w/w) with a contact angle of 45.8 °. CB‐immobilized and CB‐immobilized–thionein‐conjugated membranes were used in the Cd(II) removal studies. Cd(II) ion adsorption appeared to reach equilibrium within 30 min and to follow a typical Langmuir adsorption isotherm. The maximum capacity (q _m) of the CB‐immobilized membranes was 0.203 (µmol Cd(II)) cm⁻² membrane and increased to 1.48 (µmol Cd(II)) cm⁻² upon CB–thionein‐complex conjugation. The pHEMA membranes retained their cadmium adsorption capacity even after 10 cycles of repeated use. © 2000 Society of Chemical Industry     

Bacterial Foraging Optimization Algorithm for assembly line balancing

Assembly line balancing is the problem of assigning tasks to workstations by optimizing a performance measure while satisfying precedence relations between tasks and cycle time restrictions. Many exact, heuristic and metaheuristic approaches have been proposed for solving simple straight and U-shaped assembly line balancing problems. In this study, a relatively new optimization algorithm, Bacterial Foraging Optimization Algorithm (BFOA), based heuristic approach is proposed for solving simple straight and U-shaped assembly line balancing problems. The performance of the proposed algorithm is evaluated using a well-known data set taken from the literature in which the number of tasks varies between 7 and 111, and results are also compared with both an ant-colony-optimization-based heuristic approach and a genetic-algorithm-based heuristic approach. The proposed algorithm provided optimal solutions for 123 out of 128 (96.1 %) test problems in seconds and is proven to be promising.     

Environmental flow assessment for energy generation sustainability employing different hydraulic evaluation methods: Çambaşi hydropower plant case study in Turkey

The operating principle of hydroelectric power plants (HPP) is based on utilizing the potential energy of water, which constitutes the basic component of the plant. In other words, water is crucially important in energy production in hydroelectric power plants. The importance of water is not only limited to the energy production, but also can affect directly or indirectly all living things in the water basin. This study deals with the methods of determining the environmental flow, which will not damage the integrity of the rivers and the ecosystem in HPPs, together with enabling the sustainable electricity production as an indirect result. Suggestions are made for determining the environmental flow for Çambas? regulator and Hydropower plant, a run-of-river type power plant in Turkey, after reviewing commonly used methods all over the world. Tennant, Tessmann, and flow duration curve methods were used in determining the environmental flow. Separate calculations were carried out for Cambas? and Ogene regulators, which constitute the hydropower plant. The calculated values were compared with the normal (regime) flow rates and project flow values. As a result, Tessmann method, one of the hydrological based environmental flow determination methods, and good category of Tennant method, 20 % of annual average flow in dry period and 40 % of annual average flow in wet period, are proposed for Çamba?? HPP.     

Purification and characterization of a novel thermostable phytase from the thermophilic Geobacillus sp. TF16

A novel phytase from thermophilic Geobacillus sp. TF16 was puri?ed approximately 5-fold using ammonium sulfate precipitation and ion exchange chromatography, and determined as a single band 106.04 kDa on sodium dodecyl sulfate-polyacrylamide gel electrophoresis. Optimum temperature and optimum pH were found to be 85°C and 4.0, respectively. The enzyme is highly thermostable and V_max and K_m values were calculated as 526.28 U/mg and 1.31 mM, respectively. It was also found that the enzyme exhibited a broad substrate selectivity and resistance toward proteases and effectively hydrolyzed soymilk phytate. These results suggest that this study provides an alternative phytase enzyme with enhanced properties.     

Dephytinization of food stuffs by phytase of Geobacillus sp. TF16 immobilized in chitosan and calcium-alginate

In this work, Geobacillus sp. TF16 phytase was separately immobilized in chitosan and Ca-alginate with the efficiency of 38% and 42%, respectively. These enzymes exhibited broad substrate specificity. Maximal relative phytase activity was measured at pH 5.0 and 95°C and pH 3.0 and 75°C for chitosan and Ca-alginate, respectively. The enzymes were highly stable in a wide pH and temperature range. Values of K_m and V_max were determined as 2.38 mM and 3401.36 U/mg protein for chitosan, and 7.5 mM and 5011.12 U/mg protein for Ca-alginate. The immobilized enzymes showed higher resistance to proteolysis. After 4 h incubation, hydrolysis capacities of chitosan- and Ca-alginate immobilized enzymes for soymilk phytate were calculated as 24% and 33%, respectively. The chitosan- and Ca-alginate immobilized phytases conserved its original activity after 8 and 6 cycles of reuse, respectively. The features of the enzymes were very attractive and they might be useful for some industrial applications.     

Fe2O3–TiO2 Nano‐heterostructure Photoanodes for Highly Efficient Solar Water Oxidation

Harnessing solar energy for the production of clean hydrogen by photo­electrochemical water splitting represents a very attractive, but challenging approach for sustainable energy generation. In this regard, the fabrication of Fe₂O₃–TiO₂ photoanodes is reported, showing attractive performances [≈2.0 mA cm⁻² at 1.23 V vs. the reversible hydrogen electrode in 1 M NaOH] under simulated one‐sun illumination. This goal, corresponding to a tenfold photoactivity enhancement with respect to bare Fe₂O₃, is achieved by atomic layer deposition of TiO₂ over hematite (α‐Fe₂O₃) nanostructures fabricated by plasma enhanced‐chemical vapor deposition and final annealing at 650 °C. The adopted approach enables an intimate Fe₂O₃–TiO₂ coupling, resulting in an electronic interplay at the Fe₂O₃/TiO₂ interface. The reasons for the photocurrent enhancement determined by TiO₂ overlayers with increasing thickness are unraveled by a detailed chemico‐physical investigation, as well as by the study of photo­generated charge carrier dynamics. Transient absorption spectroscopy shows that the increased photoelectrochemical response of heterostructured photoanodes compared to bare hematite is due to an enhanced separation of photogenerated charge carriers and more favorable hole dynamics for water oxidation. The stable responses obtained even in simulated seawater provides a feasible route in view of the eventual large‐scale generation of renewable energy.     

Guanine oxidation signal enhancement in single strand DNA with polyacrylonitrile/polyaniline (PAN/PAni) hybrid nanofibers

Pure polyacrylonitrile (PAN) and polyacrylonitrile/polyaniline (PAN/PAni) hybrid nanofibers (NFs) were produced via electrospinning and used to monitor guanine oxidation in single strand DNA (ssDNA) by electrochemical methods. Two different methodologies were conducted. First, pre‐synthesized PAni was added into electrospinning PAN solution and electrospun into composite PAN/PAni nanofibrous structure on cylindrical pencil graphite (PGE) surface. In the second route, PAN NFs were electrospun on a PGE surfaces and polymerization of PAni was conducted on the surfaces of the as‐spun PAN NFs. NFs were kept at ?18 °C in a refrigerator for several days. ssDNA was immobilized on the prepared NFs and guanine oxidation signals were observed for each system. The results revealed that use of PAN NFs enhanced signal intensity from 0.92 µA (PGE) to 1.04 µA (PAN NFs). Addition of PAni to PAN increased signal intensity to 1.23 µA. When the PAN NF surfaces were coated with PAni, signal enhancement continued to increase up to 4.19 µA for fourth day and decreased again when PAni‐coated NFs were kept at ?18 °C in the refrigerator. Since the prepared system is fast and cheap, it is promising for application in DNA biosensor devices. © 2017 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2018 , 135, 45567.