Potential of pulsed electric field to control Aspergillus parasiticus,aflatoxin and mutagenicity levels: Sesame seed quality

Seed processing technologies are essential for seed safety and functionality through protection of physicochemical quality, pathogen inactivation, aflatoxin detoxification and alleviation of mutagenicity. Design of a pilot-scale unit of pulsed electric fields (PEF) to treat sesame seeds with respect to quality parameters, Aspergillus parasiticus inactivation and aflatoxin reduction as well as alleviation of aflatoxin mutagenicity were prompted in this study. PEF energy ranged from 0.97 to 17.28 J achieved maximum reductions of peroxide value and acidity number of 67.4 and 85.7%, respectively, and did not change color L*, a*, b* and hue values. A 60% reduction of A. parasiticus counts occurred at the maximum PEF energy. Aflatoxins G1, G2, B1, and B2 contents decreased by 94.7, 92.7, 86.9, and 98.7%, respectively. Except for the samples treated by 2.16 J with 100 μg/plate and by 6.80 J with 10 μg/plate, PEF treatment provided elimination of aflatoxin mutagenity. It is concluded that PEF treatment can be used to treat sesame seeds with preservation of physicochemical properties, inactivation of A. parasiticus and decomposition of aflatoxins with reduced mutagenicity.     

Subsurface Characterization at Ground Failure Sites in Adapazari, Turkey

Ground failure in Adapazari, Turkey during the 1999 Kocaeli earthquake was severe. Hundreds of structures settled, slid, tilted, and collapsed due in part to liquefaction and ground softening. Ground failure was more severe adjacent to and under buildings. The soils that led to severe building damage were generally low plasticity silts. In this paper, the results of a comprehensive investigation of the soils of Adapazari, which included cone penetration test (CPT) profiles followed by borings with standard penetration tests (SPTs) and soil index tests, are presented. The effects of subsurface conditions on the occurrence of ground failure and its resulting effect on building performance are explored through representative case histories. CPT- and SPT-based liquefaction triggering procedures adequately identified soils that liquefied if the clay-size criterion of the Chinese criteria was disregarded. The CPT was able to identify thin seams of loose liquefiable silt, and the SPT (with retrieved samples) allowed for reliable evaluation of the liquefaction susceptibility of fine-grained soils. A well-documented database of in situ and index testing is now available for incorporating in future CPT- and SPT-based liquefaction triggering correlations.     

Design and Comparison Base Analysis of Adaptive Estimator for Completely Unknown Linear Systems in the Presence of OE Noise and Constant Input Time Delay

In this paper, an adaptive estimator (AE) is introduced to learn the approximate Q‐function and control policy by only using the noisy states and control signals of the unknown linear, discrete time systems having constant input time delay. The system measurements are uncertain owing to output error (OE)‐type noise acting randomly on the system measurements. Therefore, this research differs from the designed AE in the literature since previous research ignores the role of the external random disturbances on AE‐based learning. In order to compare the AE‐based learning results with traditional system identification (SI) approaches, a modified version of the OE model structure for unstable systems is reviewed and parameters of a second‐order unstable system with constant input time delay are identified. The simulation results demonstrate that the designed AE efficiently minimizes the stochastic cost function and the temporal difference error by learning the approximate solution for the Hamilton‐Jacobi‐Bellman (HJB) equation. It is noted that the error in the Q‐function obtained with the AE is slightly larger than the Q‐function attained with the identified OE parameters. However, as the noise standard deviation increases, the error in the AE‐based learning results reduces whereas the error in the OE‐based learning increases. This indicates that even though the added random noise deteriorates the performance of the OE predictor, it improves the learning efficiency of the AE since it acts like exploration noise.     

Dynamic stability of a shaft system connected through a Hooke's joint

Dynamic stability of the torsional vibrations of a shaft system consisting of two torsionally elastic shafts interconnected through a Hooke's joint is investigated by means of a two degree-of-freedom model. The linearized equations of motion are shown to consist of a set of Mathieu-Hill equations and stability of their solutions is analyzed by means of a monodromy matrix method. Results are presented in the form of stability charts constructed on various parameter planes visualizing the effect of various selected pairs of system parameters on the stability.     

Improved assignment with ant colony optimization for multi-target tracking

Detecting and tracking ground targets is crucial in military intelligence in battlefield surveillance. Once targets have been detected, the system used can proceed to track them where tracking can be done using Ground Moving Target Indicator (GMTI) type indicators that can observe objects moving in the area of interest. However, when targets move close to each other in formation as a convoy, then the problem of assigning measurements to targets has to be addressed first, as it is an important step in target tracking. With the increasing computational power, it became possible to use more complex association logic in tracking algorithms. Although its optimal solution can be proved to be an NP hard problem, the multidimensional assignment enjoyed a renewed interest mostly due to Lagrangian relaxation approaches to its solution. Recently, it has been reported that randomized heuristic approaches surpassed the performance of Lagrangian relaxation algorithm especially in dense problems. In this paper, impelled from the success of randomized heuristic methods, we investigate a different stochastic approach, namely, the biologically inspired ant colony optimization to solve the NP hard multidimensional assignment problem for tracking multiple ground targets.     

Control-oriented modeling of a three-way catalytic converter with observation of the relative oxygen level profile

The paper presents a novel control-oriented, first-principle model of a three-way catalytic converter (TWC). The model accurately predicts the air–fuel ratio downstream of the catalyst and provides insights into the relative oxygen level (ROL) profile along the catalyst. The reaction mechanism of the TWC model is simplified to only two reactions, with oxygen being the only species stored on the active surface of the catalyst. All the information about the gas composition is taken from the upstream wide-range oxygen sensor. Additional model inputs are the exhaust gas temperature and the exhaust mass flow. The model is parameterized with only a few measurements from an engine test bench. Exact values of gas concentrations are not needed at any point.The ROL profile is a good indicator for the condition of the TWC. It can therefore be used to derive optimal TWC depletion strategies after fuel cut-off phases. Since the model is real-time capable, the ROL profile can even be used for on-line control strategies. Based thereon, a causal strategy is proposed with results that match those of the non-causal strategies found in off-line optimizations.     

The influence of nitrogen doping on reduced graphene oxide as highly cyclable Li-ion battery anode with enhanced performance

A straightforward, one-step route has been established to fabricate reduced- (rGO) and nitrogen-doped reduced graphene oxide (NrGO) with remarkable lithium-ion storage properties. The graphene oxide (GO) was synthesized as starting material by improved Hummers’ method. Thereafter, thermally annealing GO with NH₃ at elevated temperature to synthesize NrGO was yielded a more open structure with nitrogen sites suitable for enhanced Li intercalation. NrGO exhibited a reversible capacity of 240 mAhg^?1 at 10 Ag^-1 after 500 cycles with 90% capacity retention, which is the best result achieved among graphene oxide-based anodes at this current density. In contrast to rGO, NrGO cells exhibited a gradually increasing capacity profile, reaching up to 114% of the initial capacity at 0.1, 2, and 10 Ag^-1 current densities. Results showed that high occupancy of pyridinic N within NrGO enhanced battery performance and cell kinetics upon cycling which offers long-time operability at high current density.     

Friction and Wear Characteristics of Haynes 25, 188, and 214 Superalloys Against Hastelloy X up to 540 <Emphasis Type="Bold">°</Emphasis>C

As demand for more power increases, compression ratios, and operating temperatures keep rising. High speeds combined with high temperatures make turbomachinery sealing applications even more challenging. In order to confirm sufficient service life material pairs should be tested under conditions similar to engine operating conditions. This study presents high temperature friction and wear characteristics of cobalt/nickel superalloys, Haynes 25 (51Co–10Ni–20Cr–15W), Haynes 188 (39Co–22Ni–22Cr–14W), and Haynes 214 (75Ni–16Cr–3Fe–0.5Mn) sheets when rubbed against Hastelloy X (47Ni–22Cr–18Fe–9Mo) pins. Tests are conducted at 25, 200, 400, and 540 °C with a validated custom design linear reciprocating tribometer. Sliding speed and sliding distance are 1 Hz and 1.2 km, respectively. Friction coefficients are calculated with friction force data acquired from a load cell. Wear coefficients are calculated through weight loss measurements. Results indicate that Haynes 25 (H25) has the lowest friction coefficients at all test temperatures. Above 400 °C, H25 and Haynes 188 (H188) exhibit the best wear resistance. Protective cobalt oxide layers are formed on the H25 and H188 at 540 °C in addition to nickel, chrome, and tungsten oxides. Although, it has better oxidation resistance, Haynes 214 has relatively higher wear rates than other tested materials especially at low temperatures. However, its wear performance improves beyond 200 °C.     

Screening,Molecular Cloning,and Biochemical Characterization of an Alcohol Dehydrogenase from Pichia pastoris Useful for the Kinetic Resolution of a Racemic β‐Hydroxy‐β‐trifluoromethyl Ketone

The stereoselective synthesis of chiral 1,3‐diols with the aid of biocatalysts is an attractive tool in organic chemistry. Besides the reduction of diketones, an alternative approach consists of the stereoselective reduction of β‐hydroxy ketones (aldols). Thus, we screened for an alcohol dehydrogenase (ADH) that would selectively reduce a β‐hydroxy‐β‐trifluoromethyl ketone. One potential starting material for this process is readily available by aldol addition of acetone to 2,2,2‐trifluoroacetophenone. Over 200 strains were screened, and only a few yeast strains showed stereoselective reduction activities. The enzyme responsible for the reduction of the β‐hydroxy‐β‐trifluoromethyl ketone was identified after purification and subsequent MALDI‐TOF mass spectrometric analysis. As a result, a new NADP⁺‐dependent ADH from Pichia pastoris (PPADH) was identified and confirmed to be capable of stereospecific and diastereoselective reduction of the β‐hydroxy‐β‐trifluoromethyl ketone to its corresponding 1,3‐diol. The gene encoding PPADH was cloned and heterologously expressed in Escherichia coli BL21(DE3). To determine the influence of an N‐ or C‐terminal His‐tag fusion, three different recombinant plasmids were constructed. Interestingly, the variant with the N‐terminal His‐tag showed the highest activity; consequently, this variant was purified and characterized. Kinetic parameters and the dependency of activity on pH and temperature were determined. PPADH shows a substrate preference for the reduction of linear and branched aliphatic aldehydes. Surprisingly, the enzyme shows no comparable activity towards ketones other than the β‐hydroxy‐β‐trifluoromethyl ketone.