Noldus Information Technology

Abstract Predicting crop nitrogen (N) fertilizer needs is a major challenge in contemporary agriculture. Despite the success of current N recommendation tools, environmental concerns over N pollution from agriculture, and the adoption of improved corn (Zea mays L.) technologies with enhanced N efficiencies highlight the need for more accurate N fertilizer recommendation systems. Here, we aimed to develop a methodology to predict corn N requirements based on delta yield (dY = maximum yield−unfertilized yield). To develop this delta yield‐based nitrogen (dY‐based N) tool, we selected 486 quadratic‐plateau corn yield response to N curves (from 732 N rate trials across northern US) to calculate dY and N fertilizer required to reach the yield plateau (Nx). The economic optimum nitrogen rate (EONR) was calculated using different fertilizer:crop price ratios (PR). The response curve outputs were then partitioned into calibration and validation sets. The calibration set was used to select linear models to predict Nx based on dY, resulting in nine state, agroecosystem region, and irrigation‐specific sub‐models. These sub‐models predicted Nx of the validation set with a mean absolute error (MAE) of 33.0 kg N ha−1. Predicted values from the site‐year quadratic‐plateau response fits were used to improve further predictions’ outcomes. Predictions of EONR based on dY had a lower MAE than the predictions of Nx, ranging between 19.9 and 25.4 kg N ha−1 depending on the PR, highlighting the system's predictive power. The exclusion of non‐responsive and linear‐response trials in our proposed dY‐based approach enables future model refinement to improve EONR prediction accuracy across a broader range of yield responses to fertilizer‐N rates. The proposed dY‐based N system, which integrates both economic and agronomic inputs (including management, environmental effects on soil N supply, and maximum yields), could help to reduce N losses and provide functional benefits for N optimization.

Abstract Universities are large, complex and highly hierarchical organisations with deeply engrained gendered values, norms and practices. This chapter reflects on the experiences of two universities in initiating structural change towards gender equality as supported by the TARGET project. A common aspect thereby is the lack of a national policy in higher education and research providing specific support for implementing gender equality policies. The process of audit, design, implementation, monitoring and evaluation of the first gender equality plan (GEP) in each of these universities was conceived as a first step in a long journey, providing a framework for engaging different institutional actors and fostering reflexive, evidence-based policy making. The analysis deals with reflexivity and resistance and seeks to draw lessons from bottom-up and top-down experiences of GEP implementation. It is the result of shared reflection between the GEP ‘implementers’ in the two universities and the team who provided support and acted as ‘critical friends’.

Deep convolutional networks are widely used in video action recognition. 3D convolutions are one prominent approach to deal with the additional time dimension. While 3D convolutions typically lead to higher accuracies, the inner workings of the trained models are more difficult to interpret. We focus on creating human-understandable visual explanations that represent the hierarchical parts of spatio-temporal networks. We introduce Class Feature Pyramids, a method that traverses the entire network structure and incrementally discovers kernels at different network depths that are informative for a specific class. Our method does not depend on the network's architecture or the type of 3D convolutions, supporting grouped and depth-wise convolutions, convolutions in fibers, and convolutions in branches. We demonstrate the method on six state-of-the-art 3D convolution neural networks (CNNs) on three action recognition (Kinetics-400, UCF-101, and HMDB-51) and two egocentric action recognition datasets (EPIC-Kitchens and EGTEA Gaze+).

BackgroundHuntington disease (HD) is a devastating inherited neurodegenerative disorder characterized by progressive motor, cognitive, and psychiatric symptoms without any cure to slow down or stop the progress of the disease. The BACHD rat model for HD carrying the human full-length mutant huntingtin protein (mHTT) with 97 polyQ repeats has been recently established as a promising model which reproduces several HD-like features. While motor and cognitive functions have been characterized in BACHD rats, little is known about their social phenotype.ObjectiveThis study focuses especially on social behavior since evidence for social disturbances exists in human patients. Our objective was to compare social behavior in BACHD and wild-type (WT) rats at different ages, using two different measures of sociability.MethodsAnimals were tested longitudinally at the age of 2, 4 and 8 months in the social interaction test to examine different parameters of sociability. A separate cohort of 7 month old rats was tested in the three chamber social test to measure both sociability and social novelty. Gene expression analyses in 8 months old animals were performed by real time qRT-PCR to evaluate a potential involvement of D1 and D2 dopaminergic receptors and the contribution of Brain-derived neurotrophic factor (BDNF) to the observed behavioral alterations.ResultsIn the social interaction test, BACHD rats showed age-dependent changes in behaviour when they were-re introduced to their cagemate after a 24 hours-period of individual housing. The time spent on nape attacks increased with aging. Furthermore, a significant higher level of pinning at 2 months of age was shown in the BACHD rats compared to wild-types, followed by a reduction at 4 and 8 months. On the other hand, BACHD rats exhibited a decreased active social behaviour compared to wild-types, reflected by genotype-effects on approaching, following and social nose contact. In the three chamber social test, BACHD rats seemed to show a mild deficit in preference for social novelty, but no changes in social interest. Molecular analyses revealed that BACHD animals exposed to the social interaction test displayed decreased mRNA levels of the total form of BDNF in ventral striatum and unaltered striatal expression of D1 and D2 dopamine receptors.ConclusionsTaken together, these results indicate deficits in several parameters representative of sociability. Altered BDNF expression in the ventral striatum may contribute to the deficits in sociability in 8 months old BACHD rats. These data support the validity of the BACHD rat model in mimicking features of certain social deficits that could be relevant to symptoms in patients.

Neuromarketing is a hype, yet it is faced with a number of teething problems, including the costliness and complexity of its state-of-the-art techniques like electroencephalogram and functional magnetic resonance imaging. Such techniques require laboratory set-ups and so do not lend themselves to day-to-day market research processes. And neuromarketing still faces a number of other barriers. It still lacks supporting scientific proofs and it faces credibility issues as some early neuromarketing enterprises have made exaggerated, unverified and scientifically irresponsible claims. Additionally, most studies still rely on laboratory set-ups and expensive technologies which do not allow the necessary scalability for the techniques to be applied more widely. In order to overcome these obstacles, policy makers could make strategic initiatives and introduce ethical codes (EU, 2014). Yet as too many providers entered the neuromarketing field in its early days and failed to apply sound and robust scientific methods, a lot of credibility was lost. Although the methods applied nowadays have a more profound scientific basis, neuromarketing approaches still lack the scientific proofs that would support their case as meaningful methods and not just 'hocus-pocus'.

We propose a framework for the design and implementation of service systems, especially to design controls for long-term sustainable value co-creation. The framework is based on the software support tool e3-control. To illustrate the framework we use a large-scale case study, the Beer Living Lab, for simplification of customs procedures in international trade. The BeerLL shows how value co-creation can be achieved by reduction of administrative burden in international beer export due to electronic customs. Participants in the BeerLL are Heineken, IBM and Dutch Tax & Customs.

The view of evaluating Strategic Information Systems Planning (Grover & Segars, 2005) process and effectiveness has matured. However, the inter-organizational view or network view is understudied. The introduction of information strategy in networks seems more reactive than proactive; many organizations continue to use SISP as a way to support their internal decision-making process without actually cooperating with their business partners. This article aims to qualitatively explore and validate, respectively, context and process dimensions in two inter-organizational cases: a network of municipalities in Finland and a network of healthcare organizations in the Netherlands. The first case study explores the network context and theorizes how network context influences inter-organizational SISP, discovering that the inter-organisational SISP process is influenced by the context, especially by the role of trust and complexity. The second case study is the exploration of three process dimensions: contingency, certainty and contractual agreements.

The main naming system in the Internet today, DNS, is based on globally unique, hierarchically structured domain names. It does not match the names people use in everyday life. This should change in the Future Internet, if it is to live up to its promise of seamless integration into people's everyday lives. Based on this observation, we propose to develop a new, intuitive naming system. This system allows human users to identify people, applications and content that they want to interact with in a completely intuitive manner. The intuitive naming system is based on two new functions, context collection and contextual analysis, placed in a new layer on top of the existing Internet naming layers. It is our belief that an intuitive naming system is a new concept that would substantially enhance the value of the Future Internet. It therefore deserves further analysis and development by European researchers.