Subsurface Drip Nitrogen Fertigation of Corn

The efficient management of nitrogen (N) fertilizer and irrigation is of utmost importance because they are two of the greatest expenses for corn production. This project was conducted to determine if yield and efficiency of fertilizer N in corn could be improved by applying N at later developmental stages through a subsurface drip irrigation (SDI) system. Experiments in 2014 and 2015 compared a Preplant Surface application that injected fertilizer in bands below the residue at planting, to four versions of SDI fertigation that differed in timing and total amount of N applied. The SDI Sidedress treatment concluded at corn tassel stage (VT). The SDI Maximum treatment supplied an additional 40 lb N/a through corn blister stage (R2). The SDI Sensor treatment received N fertigations after corn V10 stage only if the ratio of the SPAD readings from SDI Sensor plots to Reference plots was less than 95%. The Reference treatment received both the surface band injections and all SDI fertigations for total seasonal N application that far exceeded crop N requirements. The Reference treatment produced up to 32 bu/a more grain than the Preplant Surface treatment, but produced an average of 0.7 bushels of grain per pound of N fertilizer. The SDI Maximum treatment averaged only slightly less grain yield than the reference treatment but produced 1.15 bushels of grain per pound of N fertilizer on average. The SDI Sidedress and SDI Sensor treatments resulted in similar yields that averaged 16 bu/a more than the Preplant Surface treatment. The SDI Sidedress treatment used fertilizer N the most efficiently, producing 1.3 bushels of grain per pound of N fertilizer. Applying N into the reproductive stages of corn increased yield, but N fertilizer was used most efficiently when N applications were completed by VT. Although using the sensor to determine later N applications reduced fertilizer input slightly compared to a maximum fertilizer approach, yields were reduced enough to result in similar efficiency of fertilizer use

Road Network Simulation Using FLAME GPU

Demand for high performance road network simulation is increasing due to the need for improved traffic management to cope with the globally increasing number of road vehicles and the poor capacity utilisation of existing infrastructure. This paper demonstrates FLAME GPU as a suitable Agent Based Simulation environment for road network simulations, capable of coping with the increasing demands on road network simulation. Gipps’ car following model is implemented and used to demonstrate the performance of simulation as the problem size is scaled. The performance of message communication techniques has been evaluated to give insight into the impact of runtime generated data structures to improve agent communication performance. A custom visualisation is demonstrated for FLAME GPU simulations and the techniques used are described

Why the idea of framework propositions cannot contribute to an understanding of delusions

One of the tasks that recent philosophy of psychiatry has taken upon itself is to extend the range of understanding to some of those aspects of psychopathology that Jaspers deemed beyond its limits. Given the fundamental difficulties of offering a literal interpretation of the contents of primary delusions, a number of alternative strategies have been put forward including regarding them as abnormal versions of framework propositions described by Wittgenstein in On Certainty. But although framework propositions share some of the apparent epistemic features of primary delusions, their role in partially constituting the sense of inquiry rules out their role in helping to understand delusions

Memory effects in microscopic traffic models and wide scattering in flow-density data

By means of microscopic simulations we show that non-instantaneous adaptation of the driving behaviour to the traffic situation together with the conventional measurement method of flow-density data can explain the observed inverse-$\lambda$ shape and the wide scattering of flow-density data in ``synchronized'' congested traffic. We model a memory effect in the response of drivers to the traffic situation for a wide class of car-following models by introducing a new dynamical variable describing the adaptation of drivers to the surrounding traffic situation during the past few minutes (``subjective level of service'') and couple this internal state to parameters of the underlying model that are related to the driving style. % For illustration, we use the intelligent-driver model (IDM) as underlying model, characterize the level of service solely by the velocity and couple the internal variable to the IDM parameter ``netto time gap'', modelling an increase of the time gap in congested traffic (``frustration effect''), that is supported by single-vehicle data. % We simulate open systems with a bottleneck and obtain flow-density data by implementing ``virtual detectors''. Both the shape, relative size and apparent ``stochasticity'' of the region of the scattered data points agree nearly quantitatively with empirical data. Wide scattering is even observed for identical vehicles, although the proposed model is a time-continuous, deterministic, single-lane car-following model with a unique fundamental diagram.Comment: 8 pages, submitted to Physical Review

Congested Traffic States in Empirical Observations and Microscopic Simulations

We present data from several German freeways showing different kinds of congested traffic forming near road inhomogeneities, specifically lane closings, intersections, or uphill gradients. The states are localized or extended, homogeneous or oscillating. Combined states are observed as well, like the coexistence of moving localized clusters and clusters pinned at road inhomogeneities, or regions of oscillating congested traffic upstream of nearly homogeneous congested traffic. The experimental findings are consistent with a recently proposed theoretical phase diagram for traffic near on-ramps [D. Helbing, A. Hennecke, and M. Treiber, Phys. Rev. Lett. {\bf 82}, 4360 (1999)]. We simulate these situations with a novel continuous microscopic single-lane model, the ``intelligent driver model'' (IDM), using the empirical boundary conditions. All observations, including the coexistence of states, are qualitatively reproduced by describing inhomogeneities with local variations of one model parameter. We show that the results of the microscopic model can be understood by formulating the theoretical phase diagram for bottlenecks in a more general way. In particular, a local drop of the road capacity induced by parameter variations has practically the same effect as an on-ramp.Comment: Now published in Phys. Rev. E. Minor changes suggested by a referee are incorporated; full bibliographic info added. For related work see http://www.mtreiber.de/ and http://www.helbing.org

Integrating constructive feedback in personalised e-learning

When using e-learning material some students progress readily, others have difficulties. In a traditional classroom the teacher would identify those with difficulties and direct them to additional resources. This support is not easily available within e-learning. A new approach to providing constructive feedback is developed that will enable an e-learning system to identify areas of weakness and provide guidance on further study. The approach is based on the tagging of learning material with appropriate keywords that indicate the contents. Thus if a student performs poorly on an assessment on topic X, there is a need to suggest further study of X and participation in activities related to X such as forums. As well as supporting the learner this type of constructive feedback can also inform other stakeholders. For example a tutor can monitor the progress of a cohort; an instructional designer can monitor the quality of learning objects in facilitating the appropriate knowledge across many learners

Combination of simulation and model-checking for the analysis of autonomous vehicles’ behaviors: A case study

International audienceAutonomous vehicles’ behavioural analysis represents a major challenge in the automotive world. In order to ensure safety and fluidity of driving, various methods are available, in particular, simulation and formal verification. The analysis, however, has to cope with very complex environments depending on many parameters evolving in real time. In this context, none of the aforementioned approaches is fully satisfactory, which lead us to propose a combined methodology in order to point out suspicious behaviours more efficiently. We illustrate this approach by studying a non deterministic scenario involving a vehicle, which has to react to some perilous situation

Academic self-concept, gender and single-sex schooling

This paper assesses gender differences in academic self-concept for a cohort of children born in 1958 (the National Child Development Study). We address the question of whether attending single-sex or co-educational schools affected students’ perceptions of their own academic abilities (academic self-concept). Academic selfconcept was found to be highly gendered, even controlling for prior test scores. Boys had higher self-concepts in maths and science, and girls in English. Single-sex schooling reduced the gender gap in self-concept, while selective schooling was linked to lower academic self-concept overall

Pedestrian, Crowd, and Evacuation Dynamics

This contribution describes efforts to model the behavior of individual pedestrians and their interactions in crowds, which generate certain kinds of self-organized patterns of motion. Moreover, this article focusses on the dynamics of crowds in panic or evacuation situations, methods to optimize building designs for egress, and factors potentially causing the breakdown of orderly motion.Comment: This is a review paper. For related work see http://www.soms.ethz.c

Performance over professional learning and the complexity puzzle: lesson observation in England’s further education sector

Attempts to measure the quality of teaching and learning have resulted in an overreliance on quantitative performance data and the normalisation of a set of reductionist practices in England’s further education sector in recent years. Focusing on lesson observation as an illustrative example and drawing on data from a national study, this article examines the application of observation and its impact on further education teachers’ practice. In viewing lesson observation through a complexity theory lens and contextualising it against the wider neoliberal backdrop of the marketisation of education, we seek to critique the inadequacies of current reductionist approaches to teacher evaluation, whilst simultaneously opening up a debate regarding the consequences of seeing classrooms as complex adaptive systems. In focusing on performative models of lesson observation in particular, the article exposes what we perceive as some of the epistemological and methodological shortcomings of neoliberalism in practice, but also offers an alternative way forward in dealing with the contested practice of evaluating the quality of teaching and learning