AN ECONOMIC ANALYSIS OF A CORN-SOYBEAN CROP ROTATION UNDER VARIOUS INPUT COMBINATIONS IN SOUTH CENTRAL TEXAS

Eight input combinations of commercial fertilizer, insecticides, and herbicides on a corn-soybean crop rotation in the Brazos River Bottom of Texas are evaluated. Input combinations which do not fully utilize all three inputs are consistently ranked higher by all criteria as the preferred input strategy for the corn-soybean rotation system. These results, which indicate limited input crop rotations that fall somewhere between the extremes of conventional agricultural production and organic agriculture, deserve further attention as a possible production alternative.corn, limited input, soybean, Crop Production/Industries,

The effect of silica nanoparticles on the morphology, mechanical properties and thermal degradation kinetics of polycarbonate

Polycarbonate/silica nanocomposites with different silica quantities were prepared by a melt compounding method. The effect of silica amount, in the range 1\u20135 wt.%, on the morphology, mechanical properties and thermal degradation kinetics of polycarbonate (PC) was investigated. Clusters of silica nanoparticles were well dispersed in the polycarbonate whose structure remained amorphous. NMR results showed intermolecular interactions involving the carbonyl groups of different polymeric chains which did not affect the intramolecular rotational motions. The presence of the lowest silica content showed a decrease in the storage and loss moduli below the glass transition temperature, probably due to a plasticization effect. However, an increase in the amount of silica increased the moduli. The presence of silica in PC slightly increased the thermal stability, except for the highest silica content which showed a decrease. The activation energies of thermal degradation for the nanocomposites depended on the amount of silica and on the degree of conversion

Oxidative bio-desulfurization by nanostructured peroxidase mediator system

Bio-desulfurization is an efficient technology for removing recalcitrant sulfur derivatives from liquid fuel oil in environmentally friendly experimental conditions. In this context, the development of heterogeneous bio-nanocatalysts is of great relevance to improve the performance of the process. Here we report that lignin nanoparticles functionalized with concanavalin A are a renewable and efficient platform for the layer-by-layer immobilization of horseradish peroxidase. The novel bio-nanocatalysts were applied for the oxidation of dibenzothiophene as a well-recognized model of the recalcitrant sulfur derivative. The reactions were performed with hydrogen peroxide as a green primary oxidant in the biphasic system PBS/n-hexane at 45 °C and room pressure, the highest conversion of the substrate occurring in the presence of cationic polyelectrolyte layer and hydroxy-benzotriazole as a low molecular weight redox mediator. The catalytic activity was retained for more transformations highlighting the beneficial effect of the support in the reusability of the heterogeneous system

Tracking with heavily irradiated silicon detectors operated at cryogenic temperatures

In this work we show that a heavily irradiated double-sided silicon microstrip detector recovers its performance when operated at cryogenic temperatures. A DELPHI microstrip detector, irradiated to a fluence of $\sim\,4\times 10^{14}$ p/cm$^2$, no longer operational at room temperature, cannot be distinguished from a non-irradiated one when operated at $T<120$~K. Besides confirming the previously observed `Lazarus effect' in single diodes, these results establish for the first time, the possibility of using standard silicon detectors for tracking applications in extremely demanding radiation environments

Floating Patches of HCN at the Surface of Their Aqueous Solutions - Can They Make "HCN World" Plausible?

The liquid/vapor interface of the aqueous solutions of HCN of different concentrations has been investigated using molecular dynamics simulation and intrinsic surface analysis. Although HCN is fully miscible with water, strong interfacial adsorption of HCN is observed at the surface of its aqueous solutions, and, at the liquid surface, the HCN molecules tend to be located even at the outer edge of the surface layer. It turns out that in dilute systems the HCN concentration can be about an order of magnitude larger in the surface layer than in the bulk liquid phase. Furthermore, HCN molecules show a strong lateral self-association behavior at the liquid surface, forming thus floating HCN patches at the surface of their aqueous solutions. Moreover, HCN molecules are staying, on average, an order of magnitude longer at the liquid surface than water molecules, and this behavior is more pronounced at smaller HCN concentrations. Because of this enhanced dynamical stability, the floating HCN patches can provide excellent spots for polymerization of HCN, which can be the key step in the prebiotic synthesis of partially water-soluble adenine. All of these findings make the hypothesis of "HCN world" more plausible

Modeling complex metabolic reactions, ecological systems, and financial and legal networks with MIANN models based on Markov-Wiener node descriptors

[Abstract] The use of numerical parameters in Complex Network analysis is expanding to new fields of application. At a molecular level, we can use them to describe the molecular structure of chemical entities, protein interactions, or metabolic networks. However, the applications are not restricted to the world of molecules and can be extended to the study of macroscopic nonliving systems, organisms, or even legal or social networks. On the other hand, the development of the field of Artificial Intelligence has led to the formulation of computational algorithms whose design is based on the structure and functioning of networks of biological neurons. These algorithms, called Artificial Neural Networks (ANNs), can be useful for the study of complex networks, since the numerical parameters that encode information of the network (for example centralities/node descriptors) can be used as inputs for the ANNs. The Wiener index (W) is a graph invariant widely used in chemoinformatics to quantify the molecular structure of drugs and to study complex networks. In this work, we explore for the first time the possibility of using Markov chains to calculate analogues of node distance numbers/W to describe complex networks from the point of view of their nodes. These parameters are called Markov-Wiener node descriptors of order kth (Wk). Please, note that these descriptors are not related to Markov-Wiener stochastic processes. Here, we calculated the Wk(i) values for a very high number of nodes (>100,000) in more than 100 different complex networks using the software MI-NODES. These networks were grouped according to the field of application. Molecular networks include the Metabolic Reaction Networks (MRNs) of 40 different organisms. In addition, we analyzed other biological and legal and social networks. These include the Interaction Web Database Biological Networks (IWDBNs), with 75 food webs or ecological systems and the Spanish Financial Law Network (SFLN). The calculated Wk(i) values were used as inputs for different ANNs in order to discriminate correct node connectivity patterns from incorrect random patterns. The MIANN models obtained present good values of Sensitivity/Specificity (%): MRNs (78/78), IWDBNs (90/88), and SFLN (86/84). These preliminary results are very promising from the point of view of a first exploratory study and suggest that the use of these models could be extended to the high-throughput re-evaluation of connectivity in known complex networks (collation)