Conserved histidine of metal transporter AtNRAMP1 is crucial for optimal plant growth under manganese deficiency at chilling temperatures

Manganese (Mn) is an essential nutrient required for plant growth, in particular in the process of photosynthesis. Plant performance is influenced by various environmental stresses including contrasting temperatures, light or nutrient deficiencies. The molecular responses of plants exposed to such stress factors in combination are largely unknown. 

Screening of 108 Arabidopsis thaliana (Arabidopsis) accessions for reduced photosynthetic performance at chilling temperatures was performed and one accession (Hog) was isolated. Using genetic and molecular approaches, the molecular basis of this particular response to temperature (GxE interaction) was identified. 

Hog showed an induction of a severe leaf chlorosis and impaired growth after transfer to lower temperatures. We demonstrated that this response was dependent on the nutrient content of the soil. Genetic mapping and complementation identified NRAMP1 as the causal gene. Chlorotic phenotype was associated with a histidine to tyrosine (H239Y) substitution in the allele of Hog NRAMP1. This led to lethality when Hog seedlings were directly grown at 4 degrees C. 

Chemical complementation and hydroponic culture experiments showed that Mn deficiency was the major cause of this GxE interaction. For the first time, the NRAMP-specific highly conserved histidine was shown to be crucial for plant performance.

Optimal Scheduling Methods to Integrate Plug-In Electric Vehicles with the Power System: A Review

The introduction of the Tesla in 2008 has demonstrated to the public of the potential of electric vehicles in terms of reducing fuel consumption and green-house gas from the transport sector. It has brought electric vehicles back into the spotlight worldwide at a moment when fossil fuel prices were reaching unexpected high due to increased demand and strong economic growth. The energy storage capabilities from of fleets of electric vehicles as well as the potentially random discharging and charging offers challenges to the grid in terms of operation and control. Optimal scheduling strategies are key to integrating large numbers of electric vehicles and the smart grid. In this paper, state-of-the-art optimization methods are reviewed on scheduling strategies for the grid integration with electric vehicles. The paper starts with a concise introduction to analytical charging strategies, followed by a review of a number of classical numerical optimization methods, including linear programming, non-linear programming, dynamic programming as well as some other means such as queuing theory. Meta-heuristic techniques are then discussed to deal with the complex, high-dimensional and multi-objective scheduling problem associated with stochastic charging and discharging of electric vehicles. Finally, future research directions are suggested.

Optimal design of cold-formed steel portal frames for stressed-skin action using genetic algorithm

This paper describes a stressed-skin diaphragm approach to the optimal design of the internal frame of a cold-formed steel portal framing system, in conjunction with the effect of semi-rigid joints. Both ultimate and serviceability limit states are considered. Wind load combinations are included. The designs are optimized using a real-coded niching genetic algorithm, in which both discrete and continuous decision variables are processed. For a building with two internal frames, it is shown that the material cost of the internal frame can be reduced by as much as 53%, compared with a design that ignores stressed-skin action.

Optimal design of long-span steel portal frames using fabricated beams

This paper considers the optimal design of fabricated steel beams for long-span portal frames. The design optimisation takes into account ultimate as well as serviceability limit states, adopting deflection limits recommended by the Steel Construction Institute (SCI). Results for three benchmark frames demonstrate the efficiency of the optimisation methodology. A genetic algorithm (GA) was used to optimise the dimensions of the plates used for the columns, rafters and haunches. Discrete decision variables were adopted for the thickness of the steel plates and continuous variables for the breadth and depth of the plates. Strategies were developed to enhance the performance of the GA including solution space reduction and a hybrid initial population half of which is derived using Latin hypercube sampling. The results show that the proposed GA-based optimisation model generates optimal and near-optimal solutions consistently. A parametric study is then conducted on frames of different spans. A significant variation in weight between fabricated and conventional hot-rolled steel portal frames is shown; for a 50 m span frame, a 14–19% saving in weight was achieved. Furthermore, since Universal Beam sections in the UK come from a discrete section library, the results could also provide overall dimensions of other beams that could be more efficient for portal frames. Eurocode 3 was used for illustrative purposes; any alternative code of practice may be used.

Determining the optimal current direction of transcranial magnetic stimulation to induce motor responses in the tongue: A preliminary study of neurologically healthy individuals

Objective
To determine the optimal transcranial magnetic stimulation (TMS) coil direction for inducing motor responses in the tongue in a group of non-neurologically impaired participants.
Methods
Single-pulse TMS was delivered using a figure-of-eight Magstim 2002 TMS coil. Study 1 investigated the effect of eight different TMS coil directions on the motor-evoked potentials elicited in the tongue in eight adults. Study 2 examined active motor threshold levels at optimal TMS coil direction compared to a customarily-used ventral-caudal direction. Study 3 repeated the procedure of Study 1 at five different sites across the tongue motor cortex in one adult.
Results
Inter-individual variability in optimal direction was observed, with an optimal range of directions determined for the group. Active motor threshold was reduced when a participant's own optimal TMS coil direction was used compared to the ventral-caudal direction. A restricted range of optimal directions was identified across the five cortical positions tested.
Conclusions
There is a need to identify each individual's own optimal TMS coil direction in investigating tongue motor cortex function. A recommended procedure for determining optimal coil direction is described.
Significance
Optimized TMS procedures are needed so that TMS can be utilized in determining the underlying neurophysiological basis of various motor speech disorders.

The determination of optimal processing conditions for PLA and PLA/CaCO3 in twin screw extrusion using DoE and multivariate analysis

Biodegradable polymers, such as PLA (Polylactide), come from renewable resources like corn starch and if disposed of correctly, degrade and become harmless to the ecosystem making them attractive alternatives to petroleum based polymers. PLA in particular is used in a variety of applications including medical devices, food packaging and waste disposal packaging. However, the industry faces challenges in melt processing of PLA due to its poor thermal stability which is influenced by processing temperatures and shearing.
Identification and control of suitable processing conditions is extremely challenging, usually relying on trial and error, and often sensitive to batch to batch variations. Off-line assessment in a lab environment can result in high scrap rates, long lead times and lengthy and expensive process development. Scrap rates are typically in the region of 25-30% for medical grade PLA costing between €2000-€5000/kg.
Additives are used to enhance material properties such as mechanical properties and may also have a therapeutic role in the case of bioresorbable medical devices, for example the release of calcium from orthopaedic implants such as fixation screws promotes healing. Additives can also reduce the costs involved as less of the polymer resin is required.
This study investigates the scope for monitoring, modelling and optimising processing conditions for twin screw extrusion of PLA and PLA w/calcium carbonate to achieve desired material properties. A DAQ system has been constructed to gather data from a bespoke measurement die comprising melt temperature; pressure drop along the length of the die; and UV-Vis spectral data which is shown to correlate to filler dispersion. Trials were carried out under a range of processing conditions using a Design of Experiments approach and samples were tested for mechanical properties, degradation rate and the release rate of calcium. Relationships between recorded process data and material characterisation results are explored.

Drug Polymer Thermodynamic Phase Diagrams in the Selection of Optimal API-Polymer Compositions for Amorphous Solid Dispersions

Purpose The aim of this work was to examine, for amorphous solid dispersions, how the thermal analysis method selected impacts on the construction of thermodynamic phase diagrams, and to assess the predictive value of such phase diagrams in the selection of optimal, physically stable API-polymer compositions. Methods Thermodynamic phase diagrams for two API/polymer systems (naproxen/HPMC AS LF and naproxen/Kollidon 17 PF) were constructed from data collected using two different thermal analysis methods. The “dynamic” method involved heating the physical mixture at a rate of 1 &[deg]C/minute. In the "static" approach, samples were held at a temperature above the polymer Tg for prolonged periods, prior to scanning at 10 &[deg]C/minute. Subsequent to construction of phase diagrams, solid dispersions consisting of API-polymer compositions representative of different zones in the phase diagrams were spray dried and characterised using DSC, pXRD, TGA, FTIR, DVS and SEM. The stability of these systems was investigated under the following conditions: 25 &[deg]C, desiccated; 25 &[deg]C, 60 % RH; 40 &[deg]C, desiccated; 40 &[deg]C, 60 % RH. Results Endset depression occurred with increasing polymer volume fraction (Figure 1a). In conjunction with this data, Flory-Huggins and Gordon-Taylor theory were applied to construct thermodynamic phase diagrams (Figure 1b). The Flory-Huggins interaction parameter (&[chi]) for naproxen and HPMC AS LF was + 0.80 and + 0.72, for the dynamic and static methods respectively. For naproxen and Kollidon 17 PF, the dynamic data resulted in an interaction parameter of - 1.1 and the isothermal data produced a value of - 2.2. For both systems, the API appeared to be less soluble in the polymer when the dynamic approach was used. Stability studies of spray dried solid dispersions could be used as a means of validating the thermodynamic phase diagrams. Conclusion The thermal analysis method used to collate data has a deterministic effect on the phase diagram produced. This effect should be considered when constructing thermodynamic phase diagrams, as they can be a useful tool in predicting the stability of amorphous solid dispersions.

Optimal Route Search with the Coverage of Users' Preferences

The preferences of users are important in route search and planning. For example, when a user plans a trip within a city, their preferences can be expressed as keywords shopping mall, restaurant, and museum, with weights 0.5, 0.4, and 0.1, respectively. The resulting route should best satisfy their weighted preferences. In this paper, we take into account the weighted user preferences in route search, and present a keyword coverage problem, which finds an optimal route from a source location to a target location such that the keyword coverage is optimized and that the budget score satisfies a specified constraint. We prove that this problem is NP-hard. To solve this complex problem, we pro- pose an optimal route search based on an A* variant for which we have defined an admissible heuristic function. The experiments conducted on real-world datasets demonstrate both the efficiency and accu- racy of our proposed algorithms.

Methods for Optimal Work Instruction Delivery: Pictograms v Images

This paper focuses on quantifying the benefits of pictogram based instructions relative to static images for work instruction delivery. The assembly of a stiffened aircraft panel has been used as an exemplar for the work which seeks to address the challenge of identifying an instructional mode that can be location or language neutral while at the same time optimising assembly build times and maintaining build quality. Key performance parameters measured using a series of panel build experiments conducted by two separate groups were: overall build time, the number of subject references to instructional media, the number of build errors and the time taken to correct any mistakes. Overall build time for five builds for a group using pictogram instructions was about 20% lower than for the group using image based instructions. Also, the pictogram group made fewer errors. Although previous work identified that animated instructions result in optimal build times, the language neutrality of pictograms as well as the fact that they can be used without visualisation hardware mean that, on balance, they have broader applicability in terms of transferring assembly knowledge to the manufacturing environment.

Zero-Reflectance Metafilms for Optimal Plasmonic Sensing

An ultrathin layer of metasurface that almost completely annihilates the reflection of light (>99.5%) over a wide range of incident angles (>80°) is experimentally demonstrated. Such zero-reflectance metafilms exhibit optimal performance for plasmonic sensing, since their sensitivity to changes of local refractive index is far superior to films of nonzero reflectance. Since both main detection mechanisms tracking intensity changes and wavelength shifts are improved, zero-reflectance metafilms are optimal for localized surface plasmon resonance molecular sensing. Such nanostructures have significant opportunities in many areas, including enhanced light harvesting as well as in developing high-performance molecular sensors for a wide range of chemical and biomedical applications.

Decentralized Computation of Pareto Optimal Pure Nash Equilibria of Boolean Games with Privacy Concerns

In Boolean games, agents try to reach a goal formulated as a Boolean formula. These games are attractive because of their compact representations. However, few methods are available to compute the solutions and they are either limited or do not take privacy or communication concerns into account. In this paper we propose the use of an algorithm related to reinforcement learning to address this problem. Our method is decentralized in the sense that agents try to achieve their goals without knowledge of the other agents’ goals. We prove that this is a sound method to compute a Pareto optimal pure Nash equilibrium for an interesting class of Boolean games. Experimental results are used to investigate the performance of the algorithm.