Using long time series of agricultural-derived nitrates for estimating catchment transit times

The estimation of water and solute transit times in catchments is crucial for predicting the response of hydrosystems to external forcings (climatic or anthropogenic). The hydrogeochemical signatures of tracers (either natural or anthropogenic) in streams have been widely used to estimate transit times in catchments as they integrate the various processes at stake. However, most of these tracers are well suited for catchments with mean transit times lower than about 4-5 years. Since the second half of the 20th century, the intensification of agriculture led to a general increase of the nitrogen load in rivers. As nitrate is mainly transported by groundwater in agricultural catchments, this signal can be used to estimate transit times greater than several years, even if nitrate is not a conservative tracer. Conceptual hydrological models can be used to estimate catchment transit times provided their consistency is demonstrated, based on their ability to simulate the stream chemical signatures at various time scales and catchment internal processes such as N storage in groundwater. The objective of this study was to assess if a conceptual lumped model was able to simulate the observed patterns of nitrogen concentration, at various time scales, from seasonal to pluriannual and thus if it was relevant to estimate the nitrogen transit times in headwater catchments. A conceptual lumped model, representing shallow groundwater flow as two parallel linear stores with double porosity, and riparian processes by a constant nitrogen removal function, was applied on two paired agricultural catchments which belong to the Research Observatory ORE AgrHys. The Global Likelihood Uncertainty Estimation (GLUE) approach was used to estimate parameter values and uncertainties. The model performance was assessed on (i) its ability to simulate the contrasted patterns of stream flow and stream nitrate concentrations at seasonal and inter-annual time scales, (ii) its ability to simulate the patterns observed in groundwater at the same temporal scales, and (iii) the consistency of long-term simulations using the calibrated model and the general pattern of the nitrate concentration increase in the region since the beginning of the intensification of agriculture in the 1960s. The simulated nitrate transit times were found more sensitive to climate variability than to parameter uncertainty, and average values were found to be consistent with results from others studies in the same region involving modeling and groundwater dating. This study shows that a simple model can be used to simulate the main dynamics of nitrogen in an intensively polluted catchment and then be used to estimate the transit times of these pollutants in the system which is crucial to guide mitigation plans design and assessment. (C) 2015 Elsevier B.V. All rights reserved.

Synthesis of Graphene from a Used Battery Electrode

Graphene was produced by electrochemical exfoliation of a used battery electrode. Aqueous solutions of cationic (cetyltrimethylammonium bromide), anionic (sodium dodecyl sulphate), and nonionic (poly vinyl pyrrolidone) surfactants, along with NaCl and combinations of these surfactants with NaCl, were used as the electrolyte. The following observations were made: (I) up to several micrometer sized graphene sheets were produced, (II) the addition of NaCl into the electrolytes significantly enhanced the yield of the exfoliated graphene, (III) the type of surfactant affected the defect density of the exfoliated product, and (IV) electrochemical impedance spectroscopy provided insight into the reason for the changes in the defect density ratio between the graphene samples.

Simple repetitive sequences in the genome: structure and functional significance

The current explosion of DNA sequence information has generated increasing evidence for the claim that noncoding repetitive DNA sequences present within and around different genes could play an important role in genetic control processes, although the precise role and mechanism by which these sequences function are poorly understood. Several of the simple repetitive sequences which occur in a large number of loci throughout the human and other eukaryotic genomes satisfy the sequence criteria for forming non-B DNA structures in vitro. We have summarized some of the features of three different types of simple repeats that highlight the importance of repetitive DNA in the control of gene expression and chromatin organization. (i) (TG/CA)n repeats are widespread and conserved in many loci. These sequences are associated with nucleosomes of varying linker length and may play a role in chromatin organization. These Z-potential sequences can help absorb superhelical stress during transcription and aid in recombination. (ii) Human telomeric repeat (TTAGGG)n adopts a novel quadruplex structure and exhibits unusual chromatin organization. This unusual structural motif could explain chromosome pairing and stability. (iii) Intragenic amplification of (CTG)n/(CAG)n trinucleotide repeat, which is now known to be associated with several genetic disorders, could down-regulate gene expression in vivo. The overall implications of these findings vis-à-vis repetitive sequences in the genome are summarized.

The shear dynamo problem for small magnetic Reynolds numbers

We study large-scale kinematic dynamo action due to turbulence in the presence of a linear shear flow in the low-conductivity limit. Our treatment is non-perturbative in the shear strength and makes systematic use of both the shearing coordinate transformation and the Galilean invariance of the linear shear flow. The velocity fluctuations are assumed to have low magnetic Reynolds number (Re-m), but could have arbitrary fluid Reynolds number. The equation for the magnetic fluctuations is expanded perturbatively in the small quantity, Re-m. Our principal results are as follows: (i) the magnetic fluctuations are determined to the lowest order in Rem by explicit calculation of the resistive Green's function for the linear shear flow; (ii) the mean electromotive force is then calculated and an integro-differential equation is derived for the time evolution of the mean magnetic field. In this equation, velocity fluctuations contribute to two different kinds of terms, the 'C' and 'D' terms, respectively, in which first and second spatial derivatives of the mean magnetic field, respectively, appear inside the space-time integrals; (iii) the contribution of the D term is such that its contribution to the time evolution of the cross-shear components of the mean field does not depend on any other components except itself. Therefore, to the lowest order in Re-m, but to all orders in the shear strength, the D term cannot give rise to a shear-current-assisted dynamo effect; (iv) casting the integro-differential equation in Fourier space, we show that the normal modes of the theory are a set of shearing waves, labelled by their sheared wavevectors; (v) the integral kernels are expressed in terms of the velocity-spectrum tensor, which is the fundamental dynamical quantity that needs to be specified to complete the integro-differential equation description of the time evolution of the mean magnetic field; (vi) the C term couples different components of the mean magnetic field, so they can, in principle, give rise to a shear-current-type effect. We discuss the application to a slowly varying magnetic field, where it can be shown that forced non-helical velocity dynamics at low fluid Reynolds number does not result in a shear-current-assisted dynamo effect.

An inverse problem for the Helmholtz equation involving two semi-infinite fluids

An analytical method is developed for solving an inverse problem for Helmholtz's equation associated with two semi-infinite incompressible fluids of different variable refractive indices, separated by a plane interface. The unknowns of the inverse problem are: (i) the refractive indices of the two fluids, (ii) the ratio of the densities of the two fluids, and (iii) the strength of an acoustic source assumed to be situated at the interface of the two fluids. These are determined from the pressure on the interface produced by the acoustic source. The effect of the surface tension force at the interface is taken into account in this paper. The application of the proposed analytical method to solve the inverse problem is also illustrated with several examples. In particular, exact solutions of two direct problems are first derived using standard classical methods which are then used in our proposed inverse method to recover the unknowns of the corresponding inverse problems. The results are found to be in excellent agreement.

Exploring Transfer Learning Approaches for Head Pose Classification from Multi-view Surveillance Images

Head pose classification from surveillance images acquired with distant, large field-of-view cameras is difficult as faces are captured at low-resolution and have a blurred appearance. Domain adaptation approaches are useful for transferring knowledge from the training (source) to the test (target) data when they have different attributes, minimizing target data labeling efforts in the process. This paper examines the use of transfer learning for efficient multi-view head pose classification with minimal target training data under three challenging situations: (i) where the range of head poses in the source and target images is different, (ii) where source images capture a stationary person while target images capture a moving person whose facial appearance varies under motion due to changing perspective, scale and (iii) a combination of (i) and (ii). On the whole, the presented methods represent novel transfer learning solutions employed in the context of multi-view head pose classification. We demonstrate that the proposed solutions considerably outperform the state-of-the-art through extensive experimental validation. Finally, the DPOSE dataset compiled for benchmarking head pose classification performance with moving persons, and to aid behavioral understanding applications is presented in this work.

Self-Assembled, Aligned ZnO Nanorod Buffer Layers for High-Current-Density, Inverted Organic Photovoltaics

Two different soft-chemical, self-assembly-based solution approaches are employed to grow zinc oxide (ZnO) nanorods with controlled texture. The methods used involve seeding and growth on a substrate. Nanorods with various aspect ratios (1-5) and diameters (15-65 nm) are grown. Obtaining highly oriented rods is determined by the way the substrate is mounted within the chemical bath. Furthermore, a preheat and centrifugation step is essential for the optimization of the growth solution. In the best samples, we obtain ZnO nanorods that are almost entirely oriented in the (002) direction; this is desirable since electron mobility of ZnO is highest along this crystallographic axis. When used as the buffer layer of inverted organic photovoltaics (I-OPVs), these one-dimensional (1D) nanostructures offer: (a) direct paths for charge transport and (b) high interfacial area for electron collection. The morphological, structural, and optical properties of ZnO nanorods are studied using scanning electron microscopy, X-ray diffraction, and ultraviolet-visible light (UV-vis) absorption spectroscopy. Furthermore, the surface chemical features of ZnO films are studied using X-ray photoelectron spectroscopy and contact angle measurements. Using as-grown ZnO, inverted OPVs are fabricated and characterized. For improving device performance, the ZnO nanorods are subjected to UV-ozone irradiation. UV-ozone treated ZnO nanorods show: (i) improvement in optical transmission, (ii) increased wetting of active organic components, and (iii) increased concentration of Zn-O surface bonds. These observations correlate well with improved device performance. The devices fabricated using these optimized buffer layers have an efficiency of similar to 3.2% and a fill factor of 0.50; this is comparable to the best I-OPVs reported that use a P3HT-PCBM active layer.