273 research outputs found
Nachbauprobleme bei Apfelkulturen
Bei wiederholtem Anbau von ObstbĂ€umen am gleichen Standort wird hĂ€ufig verminderter Wuchs und reduzierter Ertrag beobachtet. Dieses PhĂ€nomen wird als Nachbauproblem oder BodenmĂŒdigkeit bezeichnet. Auch Schweizer Apfelproduzenten sind davon betroffen. Die ACW untersucht mögliche Ursachen
Donât look back in anger: the rewarding value of a female face is discounted by an angry expression
The modulating effect of emotional expression on the rewarding nature of attractive and nonattractive female faces in heterosexual men was explored in a motivated viewing paradigm. This paradigm, which is an indicator of neural reward, requires the viewer to expend effort to maintain or reduce image-viewing times. Males worked to extend the viewing time for happy and neutral attractive faces but to reduce the viewing time for the attractive angry faces. Attractive angry faces were rated as more aesthetically pleasing than the nonattractive faces; however, the males worked to reduce their viewing time to a level comparable with the nonattractive neutral and happy faces. Therefore, the addition of an angry expression onto an otherwise attractive face renders it unrewarding and aversive to potential mates. Mildly happy expressions on the nonattractive faces did little to improve their attractiveness or reward potential, with males working to reduce viewing time for all nonattractive faces
Automated tracking and analysis of centrosomes in early Caenorhabditis elegans embryos
Motivation: The centrosome is a dynamic structure in animal cells that serves as a microtubule organizing center during mitosis and also regulates cell-cycle progression and sets polarity cues. Automated and reliable tracking of centrosomes is essential for genetic screens that study the process of centrosome assembly and maturation in the nematode Caenorhabditis elegans
Physics-Informed Echo State Networks for Chaotic Systems Forecasting
We propose a physics-informed Echo State Network (ESN)
to predict the evolution of chaotic systems. Compared to conventional
ESNs, the physics-informed ESNs are trained to solve supervised learning
tasks while ensuring that their predictions do not violate physical laws.
This is achieved by introducing an additional loss function during the
training of the ESNs, which penalizes non-physical predictions without
the need of any additional training data. This approach is demonstrated
on a chaotic Lorenz system, where the physics-informed ESNs improve
the predictability horizon by about two Lyapunov times as compared to
conventional ESNs. The proposed framework shows the potential of using
machine learning combined with prior physical knowledge to improve the
time-accurate prediction of chaotic dynamical systems
Physics-Informed Echo State Networks for Chaotic Systems Forecasting
We propose a physics-informed Echo State Network (ESN) to predict the
evolution of chaotic systems. Compared to conventional ESNs, the
physics-informed ESNs are trained to solve supervised learning tasks while
ensuring that their predictions do not violate physical laws. This is achieved
by introducing an additional loss function during the training of the ESNs,
which penalizes non-physical predictions without the need of any additional
training data. This approach is demonstrated on a chaotic Lorenz system, where
the physics-informed ESNs improve the predictability horizon by about two
Lyapunov times as compared to conventional ESNs. The proposed framework shows
the potential of using machine learning combined with prior physical knowledge
to improve the time-accurate prediction of chaotic dynamical systems.Comment: 7 pages, 3 figure
Identification of key risk factors related to serious road injuries and their health impacts, deliverable 7.4 of the H2020 project SafetyCube
Because of their high number and slower reduction compared to fatalities, serious road injuries are
increasingly being adopted as an additional indicator for road safety, next to fatalities. Reducing the
number of serious road injuries is one of the key priorities in the EU road safety programme 2011-
2020. In 2013, the EU Member States agreed on the following definition of serious road traffic
injuries: a serious road traffic injury is a road traffic casualty with a Maximum AIS level of 3 or higher
(MAIS3+).
One recommendation created by the EU SUSTAIN project was to conduct âA more detailed study of
the causes of serious road injuries, [which] could reveal more specific keys to reduce the number of
serious injuries in the EUâ. This recommendation is addressed through the identification of crashrelated
causation and contributory factors for selected groups of casualties with relatively many
MAIS3+ casualties compared to fatalities and groups with a relatively high burden of injury of
MAIS3+ casualties.
This deliverable is made up of two parts brought together in order to determine the main
contributory factors detailed above. This two-step approach initially identifies groups of casualties
that are specifically relevant from a serious injury perspective using national level collision and
hospital datasets from 6 countries.
Following the determination of groups of interest a detailed analysis of the selected groups using indepth
data was conducted. On the basis of in-depth data from 4 European countries the main
contributory and causal factors are determined for the selected MAIS3+ casualty groups.
Alongside the three proceeding deliverables that have formed the major outputs of WP7, deliverable
D7.4 is aimed at addressing serious injury policy at an EU levels. As such this report is broadly aimed
at policy makers although the inclusion of results from in-depth data analysis also provides
information relevant to stakeholders, particularly those working in vehicle design and manufacture
or road user behaviour
Neoliberalism as a Political Rationality: Australian Public Policy Since the 1980s
Since the 1980s, a remarkable transformation has occurred in the rationale that informs public policy in Australia. This transformation reflects a fundamental change in the way national economies and populations are conceived by policy makers and has led to the emergence of new strategies of governance as a consequence. We argue that this change of direction in Australian public policy may be best thought of as a specific neoliberal political rationality. The first section of the paper outlines changes to conceptions of the economy and subjectivity which are associated with neoliberalism as a political rationality. The second part of the paper examines the articulation and implementation of neoliberalism in Australia over the last couple of decades
Sheep Updates 2005 - Part 2
This session covers seven papers from different authors: CONCURRENT SESSIONS - STRATEGIC MANAGEMENT 1.Finishing Pastoral Lambs, Peter Tozer, Patricia Harper, Janette Drew, Department of Agriculture Western Australia 2. Coating Improves Wool Quality under Mixed Farming Conditions, KE Kemper, ML Hebart, FD Brien, KS Grimson, DH Smith AMM Ramsay, South Australian Research and Development Institute 3. J. S. Richards, K.D. Atkins, T. Thompson, W. K. Murray, Australian Sheep Industry Co-operative Research Centre and NSW Department of Primary Industries, Orange Agricultural Institute, Forest Rd. Orange 4. Strategic Risk Management in the Sheep Industry, J.R.L. Hall, ICON Agriculture (JRL Hall & Co) 5. Joining Prime Lambs for the Northern End of the Market - a Systems Approach, Chris Carter, Peter Tozer, Department of Agriculture Western Australia 6. Lifetime Wool - Dry feed budgeting tool, Mike Hyder, department of Agriculture Western Australia, John Young, Farming Systems Analysis Service, Kojonup, Western Australia 7. Influence of ultrafine wool fibre curvature and blending with cashmere on attributes of knitwear, B. A. McGregor, Primary Industries Research Victoria, Department of Primary Industries, Victori
The development of a multidisciplinary system to understand causal factors in road crashes
The persistent lack of crash causation data to help inform and monitor road and vehicle
safety policy is a major obstacle. Data are needed to assess the performance of road
and vehicle safety stakeholders and is needed to support the development of further
actions. A recent analysis conducted by the European Transport Safety Council
identified that there was no single system in place that could meet all of the needs and
that there were major gaps including in-depth crash causation information. This paper
describes the process of developing a data collection and analysis system designed to fill
these gaps. A project team with members from 7 countries was set up to devise
appropriate variable lists to collect crash causation information under the following topic
levels: accident, road environment, vehicle, and road user, using two quite different sets
of resources: retrospective detailed police reports (n=1300) and prospective,
independent, on-scene accident research investigations (n=1000). Data categorisation
and human factors analysis methods based on Cognitive Reliability and Error Analysis
Method (Hollnagel, 1998) were developed to enable the causal factors to be recorded,
linked and understood. A harmonised, prospective âon-sceneâ method for recording the
root causes and critical events of road crashes was developed. Where appropriate, this
includes interviewing road users in collaboration with more routine accident investigation
techniques. The typical level of detail recorded is a minimum of 150 variables for each
accident. The project will enable multidisciplinary information on the circumstances of
crashes to be interpreted to provide information on the causal factors. This has major
applications in the areas of active safety systems, infrastructure and road safety, as well
as for tailoring behavioural interventions. There is no direct model available
internationally that uses such a systems based approach
- âŠ