The influence of long-term inputs of catch crops and cereal straw on yield, protein composition and technological quality of a spring and a winter wheat

Under conditions of restricted nitrogen (N) input such as in organic farming systems, crop N uptake must rely on N mineralised from applied animal manure, crop residues and native soil organic matter. Scarcity of N may impede the production of quality grain for bread production, and input and retention of N in soil are therefore important parameters for soil fertility. Toretain N in the crop-soilsystem, catch crops may be grown in breaks between main crops where they provide a significant sink for N mineralised in late summer and autumn (Thomsen, 2005). In corporation of straw may likewise retain mineralised N by microbial immobilisation (Christensen, 1986) and will also directly add to the N mineralisation potential when the N supplied in the straw accumulates (Thomsen & Christensen, 2004). Under northern European conditions, winter wheat may generally be of lower quality than spring wheat, but winter wheat has a higher yield potential. When the N uptake is mainly based on N mineralised from either applied or indigenous soil organic matter, however, this may even out the quality difference between winter and spring wheat as the longer growing season of winter wheat may boost its N utilisation. Growing conditions are highly important for protein quantity whereas main lygenetic factors influence protein composition (Amesetal., 1999; Luoetal., 2000). Wheat grain proteins have been classified as albumins, globulins, gliadins and glutenins on the basis of their solubility (Osborne, 1907). Reverse-phase (RP) high performance liquid chromatography (HPLC) allows the quantitative determination of these different flour protein groups together with single proteins (α5-, α1,2-, α-, γc-type gliadins, x- and γ-type high (HMW) and low (LMW) molecular weights subunits of glutenin) (Wieser & Seilmeier, 1998). The proteins can also be divided into polymers (glutenins) or monomers (gliadins, albumins, globulins) based on their aggregating properties. The polymeric proteins are critical for governing wheat flour processing properties, and their quantity and size distribution reliably measured by size-exclusion (SE) HPLC techniques have been shown to be important indicators of baking quality (Dachkevitch & Autran, 1989; Bateyetal., 1991). The aim of this study was to examine whether wheat yield and baking quality determined by chromatographic techniques together with rheological and chemical quality measurements could be improved by combining agronomic strategies consisting of wheat cultivars and long-term organic matter inputs. The variables tested were (A) a winter wheat and a spring wheat cultivar, (B) three catch crop strategies and (C) four straw incorporation rates

Realising damage-tolerant nacre-inspired CFRP

Inthiswork,anacre-inspiredCarbonFibreReinforcedPolymer(CFRP)compositeis designed,synthesisedandtested. Analyticalandnumericalmodelsareusedtodesign a tiled micro-structure, mimicking the staggered arrangement of ceramic platelets in nacreandexploitinggeometricalinterlocksforcrackdeflectionanddamagediffusion. The designed pattern of tiles is then laser-engraved in the laminate plies. In order to increase the damage-spreading capability of the material, a thin layer of poly(lactic acid) (PLA) is film-cast on the interlaminar region, both as a continuous film and as a pattern of fractal-shaped patches. Three-point bending tests show how the nacre-like micro-structure succeeds in deflecting cracks, with damage diffusion being significantly improved by the addition of PLA at the interface between tiles. It is observed that a texture of discontinuous fractal-shaped PLA patches can increase damage diffusion, by promoting the unlocking of tiles whilst preserving the interface strength

Model-independent measurements of the sodium magneto-optical trap's excited-state population

We present model-independent measurements of the excited-state population of atoms in a sodium (Na) magneto-optical trap (MOT) using a hybrid ion-neutral trap composed of a MOT and a linear Paul trap (LPT). We photoionize excited Na atoms trapped in the MOT and use two independent methods to measure the resulting ions: directly by trapping them in our LPT, and indirectly by monitoring changes in MOT fluorescence. By measuring the ionization rate via these two independent methods, we have enough information to directly determine the population of MOT atoms in the excited-state. The resulting measurement reveals that there is a range of trapping-laser intensities where the excited-state population of atoms in our MOT follows the standard two-level model intensity-dependence. However, an experimentally determined effective saturation intensity must be used instead of the theoretically predicted value from the two-level model. We measured the effective saturation intensity to be $I_\mathrm{se}=22.9(3)\:\textrm{mW}/\textrm{cm}^2$ for the type-I Na MOT and $I_\mathrm{se}=48.9(7)\;\textrm{mW}/\textrm{cm}^2$ for the type-II Na MOT, approximately 1.7 and 3.6 times the theoretical estimate, respectively. Lastly, at large trapping-laser intensities, our experiment reveals a clear departure from the two-level model at a critical intensity that we believe is due to a state-mixing effect, whose critical intensity can be determined by a simple power broadening model.Comment: 10 pages, 8 figure

A general aspect-term-extraction model for multi-criteria recommendations

In recent years, increasingly large quantities of user reviews have been made available by several e-commerce platforms. This content is very useful for recommender systems (RSs), since it reflects the users' opinion of the items regarding several aspects. In fact, they are especially valuable for RSs that are able to exploit multi-faceted user ratings. However, extracting aspect-based ratings from unstructured text is not a trivial task. Deep Learning models for aspect extraction have proven to be effective, but they need to be trained on large quantities of domain-specific data, which are not always available. In this paper, we explore the possibility of transferring knowledge across domains for automatically extracting aspects from user reviews, and its implications in terms of recommendation accuracy. We performed different experiments with several Deep Learning-based Aspect Term Extraction (ATE) techniques and Multi-Criteria recommendation algorithms. Results show that our framework is able to improve recommendation accuracy compared to several baselines based on single-criteria recommendation, despite the fact that no labeled data in the target domain was used when training the ATE model

Learning from nature: Bio-Inspiration for damage-tolerant high-performance fibre-reinforced composites

Over millions of years Nature has attained highly optimized structural designs with remarkable toughness, strength, damage resistance and damage tolerance - properties that are so far difficult to combine in artificial high-performance fibre-reinforced polymers (HPFRPs). Recent studies, which have successfully replicated the structures and especially the toughening mechanisms found in flora and fauna, are reviewed in this work. At the core of the manufacturing of damage-tolerant bio-inspired composites, an understanding of the design principles and mechanisms is key. Universal and naturally-inherent design features, such as hierarchical- and organic-inorganic-structures as well as helical or fibrous arrangements of building blocks were found to promote numerous toughening mechanisms. Common to these features, the outstanding ability of diffusing damage at a sub-critical state has been identified as a powerful and effective mechanism to achieve high damage tolerance. Novel manufacturing processes suitable for HPFRP (such as tailored high-precision tape placement, micro-moulding, laser-engraving and additive manufacturing) have recently gained immense traction in the research community. This stems from the achievable and required geometrical complexity for HPFRPs and the replication of subtly balanced interaction between the material constituents. Even though trends in the literature clearly show that a bio-inspired material design philosophy is a successful strategy to design more efficient composite structures with enhanced damage tolerance and mechanical performance, Nature continues to offer new challenging opportunities yet to be explored, which could lead to a new era of HPFRP composites

Evidence of sympathetic cooling of Na+ ions by a Na MOT in a hybrid trap

A hybrid ion-neutral trap provides an ideal system to study collisional dynamics between ions and neutrals. This system provides a general cooling method that can be applied to optically inaccessible species and can also potentially cool internal degrees of freedom. The long range polarization potentials ($V\propto-\alpha/r^4$) between ions and neutrals result in large scattering cross sections at cold temperatures, making the hybrid trap a favorable system for efficient sympathetic cooling of ions by collisions with neutral atoms. We present experimental evidence of sympathetic cooling in a hybrid trap of \ce{Na+} ions, which are closed shell and therefore do not have a laser induced atomic transition, by equal mass cold Na atoms in a magneto-optical trap (MOT).Comment: 7 figure

An investigation on the impact of natural language on conversational recommendations

In this paper, we investigate the combination of Virtual Assistants and Conversational Recommender Systems (CoRSs) by designing and implementing a framework named ConveRSE, for building chatbots that can recommend items from different domains and interact with the user through natural language. An user experiment was carried out to understand how natural language influences both the cost of interaction and recommendation accuracy of a CoRS. Experimental results show that natural language can indeed improve user experience, but some critical aspects of the interaction should be mitigated appropriately

Ion-neutral sympathetic cooling in a hybrid linear rf Paul and magneto-optical trap

Long range polarization forces between ions and neutral atoms result in large elastic scattering cross sections, e.g., 10^6 a.u. for Na+ on Na or Ca+ on Na at cold and ultracold temperatures. This suggests that a hybrid ion-neutral trap should offer a general means for significant sympathetic cooling of atomic or molecular ions. We present SIMION 7.0 simulation results concerning the advantages and limitations of sympathetic cooling within a hybrid trap apparatus, consisting of a linear rf Paul trap concentric with a Na magneto-optical trap (MOT). This paper explores the impact of various heating mechanisms on the hybrid system and how parameters related to the MOT, Paul trap, number of ions, and ion species affect the efficiency of the sympathetic cooling

Heisenberg scaling precision in multi-mode distributed quantum metrology

We consider the estimation of an arbitrary parameter φ, such as the temperature or a magnetic field, affecting in a distributed manner the components of an arbitrary linear optical passive network, such as an integrated chip. We demonstrate that Heisenberg scaling precision (i.e. of the order of 1/N, where N is the number of probe photons) can be achieved without any iterative adaptation of the interferometer hardware and by using only a simple, single, squeezed light source and well-established homodyne measurements techniques. Furthermore, no constraint on the possible values of the parameter is needed but only a preliminary shot-noise estimation (i.e. with a precision of) easily achievable without any quantum resources. Indeed, such a classical knowledge of the parameter is enough to prepare a single, suitable optical stage either at the input or the output of the network to monitor with Heisenberg-limited precision any variation of the parameter to the order of without the need to iteratively modify such a stage