Conceptualizing Export Growth in the Context of Triple Helix in Shrinking Regions A Case Study of South East Drenthe (The Netherlands)

This paper is a theoretical exercise to conceptualize the application of triple helix concept in one of the shrinking provinces of the Netherland. The triple helix concept is embodied in the form of the so called export promotion measure to provide low threshold alternative to the marginalized companies in the province. With help of revenue matrix, there are four sketches are depicted graphically to show the result of export promotion measure. The results show that the content wise high expertise of the professional education, the strategical assignments from the willing companies and the support of funding from the government turn out to be necessary conditions for the success for moving to the potential sector for the export, that in turn is able to create the necessary demand essential to the existence of the corporate sector in the shrinking provinces

Method for Semi-Automated Improvement of Smart Factories Using Synthetic Data and Cause-Effect-Relationships

Smart factories, driven by the integration of automation and digital technologies, have revolutionized industrial production by enhancing efficiency, productivity, and flexibility. However, the optimization and continuous improvement of these complex systems present numerous challenges, especially when real-world data collection is time-consuming, expensive, or limited. In this paper, we propose a novel method for semi-automated improvement of smart factories using synthetic data and cause-effect-relations, while incorporating the aspect of self-organization. The method leverages the power of synthetic data generation techniques to create representative datasets that mimic the behaviour of real-world manufacturing systems. These synthetic datasets serve together with the cause-and-effect relationships as a valuable resource for factory optimization, as they enable extensive experimentation and analysis without the constraints of limited or costly real-world data. Furthermore, the method embraces the concept of self-organization within smart factories. By allowing the system to adapt and optimize itself based on feedback from the synthetic data, cause-effect-relationships, the factory can dynamically reconfigure and adjust its processes. To facilitate the improvement process, the method integrates the synthetic data with advanced analytics and machine learning algorithms as well as and the cause-and-effect relationships. This synergy between human expertise and technological advancements represents a compelling path towards a truly optimized smart factory of the future

Species-specific analysis of protein sequence motifs using mutual information

BACKGROUND: Protein sequence motifs are by definition short fragments of conserved amino acids, often associated with a specific function. Accordingly protein sequence profiles derived from multiple sequence alignments provide an alternative description of functional motifs characterizing families of related sequences. Such profiles conveniently reflect functional necessities by pointing out proximity at conserved sequence positions as well as depicting distances at variable positions. Discovering significant conservation characteristics within the variable positions of profiles mirrors group-specific and, in particular, evolutionary features of the underlying sequences. RESULTS: We describe the tool PROfile analysis based on Mutual Information (PROMI) that enables comparative analysis of user-classified protein sequences. PROMI is implemented as a web service using Perl and R as well as other publicly available packages and tools on the server-side. On the client-side platform-independence is achieved by generally applied internet delivery standards. As one possible application analysis of the zinc finger C(2)H(2)-type protein domain is introduced to illustrate the functionality of the tool. CONCLUSION: The web service PROMI should assist researchers to detect evolutionary correlations in protein profiles of defined biological sequences. It is available at where additional documentation can be found

Right Prefrontal TMS Disrupts Interregional Anticipatory EEG Alpha Activity during Shifting of Visuospatial Attention

Visual attention can be shifted in space without moving the eyes. Amplitude decrease of rhythmical brain activity around 10 Hz (so called alpha activity) at contralateral posterior sites has been reported during covered shifts of visuospatial attention to one visual hemi-field. Alpha amplitude increase, on the other hand, can be found at ipsilateral visual cortex. There is some evidence suggesting an involvement of prefrontal brain areas during the control of attention-related anticipatory alpha amplitude asymmetry. This open question has been studied in detail using a multimodal approach combining transcranial magnetic stimulation (TMS) and multichannel electroencephalography (EEG) in healthy humans. Slow (1 Hz) repetitive TMS leading to reduced excitability of the stimulation site was delivered either to right frontal eye field (FEF) or a control site (vertex). Subsequently, participants had to perform a spatial cuing task in which covert shifts of attention were required to either the left or the right visual hemi-field. After stimulation at the vertex (control condition) a pattern of anticipatory, attention-related ipsilateral alpha increase/contralateral alpha decrease over posterior recording sites could be obtained. Additionally, there was pronounced coupling between (in particular right) FEF and posterior brain sites at EEG alpha frequency. When, however, right prefrontal cortex had been virtually lesioned preceding the task, these EEG correlates of visuospatial attention were attenuated. Notably, the effect of TMS at the right FEF on interregional fronto-parietal alpha coupling predicted the effect of TMS on response times. This suggests that visual attention processes associated with posterior EEG alpha activity are at least partly top-down controlled by the prefrontal cortex

Ultra Performance Liquid Chromatography and High Resolution Mass Spectrometry for the Analysis of Plant Lipids

Holistic analysis of lipids is becoming increasingly popular in the life sciences. Recently, several interesting, mass spectrometry-based studies have been conducted, especially in plant biology. However, while great advancements have been made we are still far from detecting all the lipids species in an organism. In this study we developed an ultra performance liquid chromatography-based method using a high resolution, accurate mass, mass spectrometer for the comprehensive profiling of more than 260 polar and non-polar Arabidopsis thaliana leaf lipids. The method is fully compatible to the commonly used lipid extraction protocols and provides a viable alternative to the commonly used direct infusion-based shotgun lipidomics approaches. The whole process is described in detail and compared to alternative lipidomic approaches. Next to the developed method we also introduce an in-house developed database search software (GoBioSpace), which allows one to perform targeted or un-targeted lipidomic and metabolomic analysis on mass spectrometric data of every kind