(6<Emphasis Type="Italic">R</Emphasis>, 10<Emphasis Type="Italic">R</Emphasis>)-6,10,14-Trimethylpentadecan-2-one,a Dominant and Behaviorally Active Component in Male Orchid Bee Fragrances

6,10,14-Trimethylpentadecan-2-one (Hexahydrofarnesyl acetone; HHA) previously has been found to be a major component in tibial fragrances of male orchid bees, Euglossa spp. HHA is a chiral molecule with four possible stereoisomers, (6R, 10R)-, (6R, 10S)-, (6S, 10R)-, and (6S, 10S)-6,10,14-trimethylpentadecan-2-one. In the present study, we characterized HHA extracted from Euglossa as the pure enantiomer (6R, 10R)-6,10,14-trimethylpentadecan-2-one. During bioassays in Mexico and Panama, the synthetic RR-isomer attracted males of six species of orchid bees, including three that were known to contain HHA in their tibial fragrances. Possible sources of HHA for wild bees are flowers of euglossophilous orchids and aroids. With a molecular weight of 268, HHA is the largest natural molecule known to attract male orchid bees in pure form. Its attractiveness to males suggests that low-volatility compounds have a function in male signals, e.g., serve as a “base note” in complex odor bouquets.     

Removal of heavy metals from kaolin using an upward electrokinetic soil remedial (UESR) technology

An upward electrokinetic soil remedial (UESR) technology was proposed to remove heavy metals from contaminated kaolin. Unlike conventional electrokinetic treatment that uses boreholes or trenches for horizontal migration of heavy metals, the UESR technology, applying vertical non-uniform electric fields, caused upward transportation of heavy metals to the top surface of the treated soil. The effects of current density, treatment duration, cell diameter, and different cathode chamber influent (distilled water or 0.01 M nitric acid) were studied. The removal efficiencies of heavy metals positively correlated to current density and treatment duration. Higher heavy metals removal efficiency was observed for the reactor cell with smaller diameter. A substantial amount of heavy metals was accumulated in the nearest to cathode 2 cm layer of kaolin when distilled water was continuously supplied to the cathode chamber. Heavy metals accumulated in this layer of kaolin can be easily excavated and disposed off. The main part of the removed heavy metals was dissolved in cathode chamber influent and moved away with cathode chamber effluent when 0.01 M nitric acid was used, instead of distilled water. Energy saving treatment by UESR technology with highest metal removal efficiencies was provided by two regimes: (1) by application of 0.01 M nitric acid as cathode chamber influent, cell diameter of 100 mm, duration of 18 days, and constant voltage of 3.5 V (19.7 k Wh/m(3) of kaolin) and (2) by application of 0.01 M nitric acid as cathode chamber influent, cell diameter of 100 cm, duration of 6 days, and constant current density of 0.191 mA/cm(2) (19.1 k Wh/m(3) of kaolin).     

Reflectivity spectra and colors of porous anodic aluminum oxide containing silver nanoparticles by plasmonic absorption

The reflectivity spectra and color of porous anodic aluminum oxide (AAO) nanostructures containing the assembly of silver (Ag) nanoparticles (NPs) with a diameter of -10 nm were investigated. The Ag NPs were assembled inside the pores of AAO with a diameter of -60 nm by dip-coating process during which Ag NPs adsorbed on the surface of AAO and driven inside the pores by capillary force upon the evaporation of solvent. The reflectivity spectra and associated colors of AAO with Ag NPs were determined by the plasmonic absorption of light by Ag NPs. Even with the monolayer coverage of Ag NPs in the pores of AAO, the reflectivity is significantly reduced specifically at -465 nm wavelength by a strong plasmonic absorption, resulting in its golden color. Aggregating Ag NPs by post-annealing at 300 and 400 degrees C changed the color to pink due to the red-shift of absorption. These results are indicative of potential color-engineering of NPs/AAO platform by wavelength-selective reduction of reflected light intensity and using it in direct optical read-out of change of surface and morphology conditions.     

Photovoltaic device performance of single-walled carbon nanotube and polyaniline films on n-Si: device structure analysis

In this paper, we explore the use of two organic materials that have been touted for use as photovoltaic (PV) materials: inherently conducting polymers (ICPs) and carbon nanotubes (CNTs). Due to these materials' attractive features, such as environmental stability and tunable electrical properties, our focus here is to evaluate the use of polyaniline (PANI) and single wall carbon nanotube (SWNT) films in heterojunction diode devices. The devices are characterized by electron microscopy (film morphology), current-voltage characteristics (photovoltaic behavior), and UV/visible/NIR spectroscopy (light absorption). We have found that both PANI and SWNT can be utilized as photovoltaic materials in a simple bilayer configuration with n-type Silicon: n-Si/PANI and n-Si/SWNT. It was our aim to determine how photovoltaic performance was affected utilizing both PANI and SWNT layers in multilayer devices: n-Si/PANI/SWNT and n-Si/SWNT/PANI. The short-circuit current density increased from 4.91 mA/cm(2) (n-Si/PANI) to 12.41 mA/cm(2) (n-Si/PANI/SWNT), while an increase in power conversion efficiency by ~91% was also observed. In the case of n-Si/SWNT/PANI and its corresponding device control (n-Si/SWNT), the short-circuit current density was decreased by an order of magnitude. The characteristics of the device were affected by the architecture and the findings have been attributed to the more effective transport of holes from the PANI to SWNT and less effective transport of holes from PANI to SWNT in the respective multilayer devices.     

Bioaccumulation, biotransformation, and metabolite formation of fipronil and chiral legacy pesticides in rainbow trout

To assess the fate of current-use pesticides, it is important to understand their bioaccumulation and biotransformation by aquatic biota. We examined the dietary accumulation and enantioselective biotransformation of the chiral current-use pesticide fipronil, along with a mixture of selected chiral [alpha-hexachlorocyclohexane (alpha-HCH), heptachlor epoxide (HEPX), polychlorinated biphenyls (PCBs) 84, 132, 174, o,p'-DDT, and o,p'-DDD] and nonchiral (p,p'-DDT, p,p'-DDD) organochlorine compounds in juvenile rainbow trout (Oncorhynchus mykiss). Fish rapidly accumulated all compounds, as measured in the carcass (whole body minus liver and GI tract) during the 32 d uptake phase, which was followed by varying elimination rates of the chemicals (half-lives (t1/2s) ranging from 0.6 d for fipronil to 77.0 d for PCB 174) during the 96 d depuration period. No biotransformation was observed for alpha-HCH, HEPX, PCB 174, o,p'-DDT, or o,p'-DDD based on consistent enantiomeric fractions (EFs) in the fish and their t1/2s falling on a log K(ow)--log t1/2 relationship established for recalcitrant contaminants in fish. p,p'-DDT and PCBs 84 and 132 were biotransformed based on the former's t1/2 position below the log K(ow)--log t1/2 relationship, and the PCBs change in EF. Fipronil was rapidly biotransformed, based on a change in EF, a t1/2 that fell below the log K(ow)--log t1//2 relationship, which accounted for 88% of its elimination, and the rapid formation of fipronil sulfone, a known metabolite. Fipronil sulfone was found to persist longer (t1/2 approximately 2 d) than its parent compound fipronil (t1/2 approximately 0.6 d) and needs to be considered in fate studies of fipronil. This research demonstrates the utilities of the log K(ow)--log t1/2 relationship as a mechanistic tool for quantifying biotransformation and of chiral analysis to measure biotransformation in fish.     

Nanocrystalline diamond film for biosensor applications

In this study, we have developed a novel capacitive biosensor based on interdigitated gold nanodiamond (GID-NCD) electrode for detection of C-reactive protein (CRP) antigen. CRP is one of the plasma proteins known as acute-phase proteins and its levels rise dramatically during inflammatory processes occurring in the body. It has been reported that CRP in serum can be used for risk assessment of cardiovascular diseases. The antibodies immobilization were confirmed by fourier transform spectroscopy (FTIR) and contact angle measurements. In this capacitive biosensor, nanocrystalline diamond acting as a dielectric layer between the electrodes. The CRP antigen detection was performed by capacitive/dielectric-constant measurements. Our results showed that the response of NCD-based capacitive-based biosensor for CRP antigen was dependent on both concentration (25–800 ng/ml) as well as frequency (50–350 MHz). Furthermore, using optimized conditions, the biosensors developed in this study can be potentially used for detection of elevated level of risk markers protein in suspected subjects for early diagnosis of disease.     

The teaching of qualitative research methods in information systems: an explorative study utilizing learning theory

Empirical evidence suggests that the Information Systems field continues to be dominated by the positivist paradigm and the use of quantitative methods. This is so despite the diversity of research methods available, the emergence of an interpretivist tradition, and some isolated examples of methodological pluralism. While there have been significant contributions in guiding qualitative research methods teaching, little research has been undertaken that considers the training actually provided, and the possible impacts this may have on the quality and quantity of qualitative research articles in our journals. This explorative study aims to provide some insight into what training is provided, the issues confronted, and possible impediments to publishing qualitative research. Data were collected from interviews with a panel of international colleagues who have a range of experience in teaching and applying qualitative methods. Grounded Theory is used to identify emergent and interconnected themes. Experiential and social learning lenses are used to reflect on the results, providing some initial understanding of the complexities of teaching and undertaking qualitative research. Theoretical as well as practical contributions are made regarding the means by which qualitative research may be introduced, developed and extended within the IS academy, and further theorisation of social and experiential learning.     

Efficient Interval Linear Equality Solving in Constraint Logic Programming

Existing interval constraint logic programming languages, such as BNR Prolog, work under the framework of interval narrowing and are deficient in solving systems of linear constraints over real numbers, which constitute an important class of problems in engineering and other applications. In this paper, we suggest to separate linear equality constraint solving from inequality and non-linear constraint solving. The implementation of an efficient interval linear constraint solver, which is based on the preconditioned interval Gauss-Seidel method, is proposed. We show how the solver can be adapted to incremental execution and incorporated into a constraint logic programming language already equipped with a non-linear solver based on interval narrowing. The two solvers share common interval variables, interact and cooperate in a round-robin fashion during computation, resulting in an efficient interval constraint arithmetic language CIAL. The CIAL prototypes, based on CLP(R), are constructed and compared favorably against several major interval constraint logic programming languages.     

Denoising Medical Images Using Deep Learning in IoT Environment

Medical Resonance Imaging (MRI) is a noninvasive, nonradioactive, and meticulous diagnostic modality capability in the field of medical imaging. However, the efficiency of MR image reconstruction is affected by its bulky image sets and slow process implementation. Therefore, to obtain a high-quality reconstructed image we presented a sparse aware noise removal technique that uses convolution neural network (SANR_CNN) for eliminating noise and improving the MR image reconstruction quality. The proposed noise removal or denoising technique adopts a fast CNN architecture that aids in training larger datasets with improved quality, and SARN algorithm is used for building a dictionary learning technique for denoising large image datasets. The proposed SANR_CNN model also preserves the details and edges in the image during reconstruction. An experiment was conducted to analyze the performance of SANR_CNN in a few existing models in regard with peak signal-to-noise ratio (PSNR), structural similarity index (SSIM), and mean squared error (MSE). The proposed SANR_CNN model achieved higher PSNR, SSIM, and MSE efficiency than the other noise removal techniques. The proposed architecture also provides transmission of these denoised medical images through secured IoT architecture.