Data reduction in the ITMS system through a data acquisition model with self-adaptive sampling rate

Long pulse or steady state operation of fusion experiments require data acquisition and processing systems that reduce the volume of data involved. The availability of self-adaptive sampling rate systems and the use of real-time lossless data compression techniques can help solve these problems. The former is important for continuous adaptation of sampling frequency for experimental requirements. The latter allows the maintenance of continuous digitization under limited memory conditions. This can be achieved by permanent transmission of compressed data to other systems. The compacted transfer ensures the use of minimum bandwidth. This paper presents an implementation based on intelligent test and measurement system (ITMS), a data acquisition system architecture with multiprocessing capabilities that permits it to adapt the system’s sampling frequency throughout the experiment. The sampling rate can be controlled depending on the experiment’s specific requirements by using an external dc voltage signal or by defining user events through software. The system takes advantage of the high processing capabilities of the ITMS platform to implement a data reduction mechanism based in lossless data compression algorithms which are themselves based in periodic deltas

A versatile trigger and synchronization module with IEEE1588 capabilities and EPICS support.

Event timing and synchronization are two key aspects to improve in the implementation of distributed data acquisition (dDAQ) systems such as the ones used in fusion experiments. It is also of great importance the integration of dDAQ in control and measurement networks. This paper analyzes the applicability of the IEEE1588 and EPICS standards to solve these problems, and presents a hardware module implementation based in both of them that allow adding these functionalities to any DAQ. The IEEE1588 standard facilitates the integration of event timing and synchronization mechanisms in distributed data acquisition systems based on IEEE 803.3 (Ethernet). An optimal implementation of such system requires the use of network interface devices which include specific hardware resources devoted to the IEE1588 functionalities. Unfortunately, this is not the approach followed in most of the large number of applications available nowadays. Therefore, most solutions are based in software and use standard hardware network interfaces. This paper presents the development of a hardware module (GI2E) with IEEE1588 capabilities which includes USB, RS232, RS485 and CAN interfaces. This permits to integrate any DAQ element that uses these interfaces in dDAQ systems in an efficient and simple way. The module has been developed with Motorola's Coldfire MCF5234 processor and National Semiconductors's PHY DP83640T, providing it with the possibility to implement the PTP protocol of IEEE1588 by hardware, and therefore increasing its performance over other implementations based in software. To facilitate the integration of the dDAQ system in control and measurement networks the module includes a basic Input/Output Controller (IOC) functionality of the Experimental Physics and Industrial Control System (EPICS) architecture. The paper discusses the implementation details of this module and presents its applications in advanced dDAQ applications in the fusion community

New information processing methods for control in magnetically confinement nuclear fusion

Thermonuclear plasmas are complex and highly non-linear physical objects and therefore, in the most advanced present day devices for the study of magnetic confinement fusion, thousands of signals have to be acquired for each experiment, in order to progress with the understanding indispensable for the final reactor. On the other hand, the resulting massive databases, more than 40 Tbytes in the case of the JET joint Undertaking, pose significant problems. In this paper, solutions to reduce the shear amount of data by different compression techniques and adaptive sampling frequency architectures are presented. As an example of methods capable of providing significant help in the data analysis and real time control, a Classification and Regression Tree software is applied to the problem of regime identification, to discriminate in an automatic way whether the plasma is in the L or H confinement mode

Service-oriented architecture of adaptive, intelligent data acquisition and processing systems for long-pulse fusion experiments

The data acquisition systems used in long-pulse fusion experiments need to implement data reduction and pattern recognition algorithms in real time. In order to accomplish these operations, it is essential to employ software tools that allow for hot swap capabilities throughout the temporal evolution of the experiments. This is very important because processing needs are not equal during different phases of the experiment. The intelligent test and measurement system (ITMS) developed by UPM and CIEMAT is an example of a technology for implementing scalable data acquisition and processing systems based on PXI and CompactPCI hardware. In the ITMS platform, a set of software tools allows the user to define the processing algorithms associated with the different experimental phases using state machines driven by software events. These state machines are specified using the State Chart XML (SCXML) language. The software tools are developed using JAVA, JINI, an SCXML engine and several LabVIEW applications. Within this schema, it is possible to execute data acquisition and processing applications in an adaptive way. The power of SCXML semantics and the ability to work with XML user-defined data types allow for very easy programming of the ITMS platform. With this approach, the ITMS platform is a suitable solution for implementing scalable data acquisition and processing systems based on a service-oriented model with the ability to easily implement remote participation applications

Urban road surface discrimination by tire-road noise analysis and data clustering

The surface condition of roadways has direct consequences on a wide range of processes related to the transportation technology, quality of road facilities, road safety, and traffic noise emissions. Methods developed for detection of road surface condition are crucial for maintenance and rehabilitation plans, also relevant for driving environment detection for autonomous transportation systems and e-mobility solutions. In this paper, the clustering of the tire-road noise emission features is proposed to detect the condition of the wheel tracks regions during naturalistic driving events. This acoustic-based methodology was applied in urban areas under nonstop real-life traffic conditions. Using the proposed method, it was possible to identify at least two groups of surface status on the inspected routes over the wheel-path interaction zone. The detection rate on urban zone reaches 75% for renewed lanes and 72% for distressed lanes

Estimation of the noise emissions generated by a single vehicle while driving

This article presents a method of calculation that allows us to separate the contribution of a specific vehicle to the overall noise pollution in an urban environment. This method will provide local authorities with new operating models so that the cost of noise can be allocated to a vehicle according to factors such as the number of people it affects, the distance traveled and journey time, the driving style and the type of vehicle and tires. The proposed methodology can be adapted to different noise emission and propagation models, and we select as a basis the CNOSSOS-EU framework for compatibility with the European noise mapping strategy. This method will make it possible to reduce road traffic noise using two long-term strategies: (a) separate distributions of the costs of noise among the vehicles that generate it, with the aim of achieving (b) an increase in pro-environmental behavior with regard to this pollutant

Advantages of a Polycentric Approach to Climate Change Policy

Lack of progress in global climate negotiations has led scholars to reconsider polycentric approaches to climate policy. Several examples of subglobal mechanisms to reduce greenhouse-gas emissions have been touted, but it remains unclear why they might achieve better climate outcomes than global negotiations alone. Decades of work conducted by researchers associated with the Vincent and Elinor Ostrom Workshop in Political Theory and Policy Analysis at Indiana University have emphasized two chief advantages of polycentric approaches over monocentric ones: they provide more opportunities for experimentation and learning to improve policies over time, and they increase communications and interactions — formal and informal, bilateral and multilateral — among parties to help build the mutual trust needed for increased cooperation. A wealth of theoretical, empirical and experimental evidence supports the polycentric approach

Proposal of a Nutritional Quality Index (NQI) to Evaluate the Nutritional Supplementation of Sportspeople

Background: Numerous supplements are used by sportspeople. They are not always appropriate for the individual or the sports activity and may do more harm than good. Vitamin and mineral supplements are unnecessary if the energy intake is sufficient to maintain body weight and derives from a diet with an adequate variety of foods. The study objectives were to evaluate the main nutrients used as supplements in sports and to propose a nutritional quality index (NQI) that enables sportspeople to optimize their use of supplements and detect and remedy possible nutritional deficits. Material and Methods: A nutritional study was performed in 485 sportspeople recruited from Centros Andaluces de Medicina del Deporte, (CAMD). All completed socio-demographic, food frequency, and lifestyle questionnaires. The nutritional quality of their diet and need for supplementation were evaluated by scoring their dietary intake with and without supplementation, yielding two NQI scores (scales of 0-21 points) for each participant. Results: A superior mean NQI score was obtained when the supplements taken by participants were not included (16. 28 (SD of 3.52)) than when they were included (15.47 (SD: 3.08)), attributable to an excessive intake of some nutrients through supplementation. Conclusions: These results indicate that sportspeople with a varied and balanced diet do not need supplements, which appear to offer no performance benefits and may pose a health risk.The authors are grateful to the Junta de Andalucía, Spain (Research Group AGR-255“Nutrition. Diet and Risk Assessment”), a collaboration agreement with the Andalusian Centres of Sports Medicine (Junta de Andalucía) and the FPU program of the Spanish Ministry of Education and Science. Study participants were recruited through the project “Nutritional and diet assessment methodologies applied to the Andalusian sportsperson in Andalusian Sports centres”, Research project FMD2010SC0071 of the Junta de Andalucía

Vascular and root tip GPT2 expression mediates the PGI1-independent response of Arabidopsis to small microbial volatiles

Resumen del trabajo presentado en el XVI Meeting of Plant Molecular Biology, celebrado en Sevilla (España), del 14 al 16 de septiembre de 2022Microorganisms emit a plethora of volatile compounds (VCs) that promote plant growth and photosynthesis as well as strong developmental and metabolic changes. In Arabidopsis, the plastidial isoform of phosphoglucose isomerase PGI1 mediates photosynthesis, metabolism and development, probably due to its involvement in the synthesis of isoprenoid-derived signals in vascular tissues (Bahaji et al., 2015; Bahaji et al., 2018). Like in wild-type (WT) plants, microbial VCs promote growth and photosynthesis as well as starch and CK accumulation in PGI1-lacking pgi1-2 plants (Sánchez-López et al. 2016). A striking alteration in the transcriptome of leaves of small fungal VC-treated plants involves strong up-regulation of levels of transcripts of GPT2 (At1g61800), a gene that codes for a plastidial G6P/Pi transporter. We hypothesized that the PGI1-independent response to microbial volatile emissions involves GPT2 action. To test this hypothesis, we characterized responses of WT, GPT2-null gpt2-1, PGI1-null pgi1-2 and pgi1- 2gpt2-1 plants to small fungal VCs. In addition, we characterized responses of pgi1-2gpt2-1 plants expressing GPT2 under the control of a vascular tissue- and root tip-specific promoter to small fungal VCs. Results presented in this work provide evidence that, under conditions in which PGI1 activity is reduced, long-distance action of GPT2 plays an important role in the response of plants to small VCs through mechanisms involving resetting of the photosynthesis-related proteome in leaves and complex GPT2 regulation.This work was supported by the Ministerio de Ciencia e Innovación (MCIN) and Agencia Estatal de Investigación (AEI) / 10.13039/501100011033/ (grants BIO2016-78747-P, PID2019-104685GB-100 and PID2019-107657RB-C22) and the Ministry of Education, Youth and Sport of the Czech Republic and ERDF project entitled “Plants as a tool for sustainable global development” (No. CZ.02.1.01/0.0/0.0/16_019/0000827)

Consequences of converting graded to action potentials upon neural information coding and energy efficiency

Information is encoded in neural circuits using both graded and action potentials, converting between them within single neurons and successive processing layers. This conversion is accompanied by information loss and a drop in energy efficiency. We investigate the biophysical causes of this loss of information and efficiency by comparing spiking neuron models, containing stochastic voltage-gated Na+ and K+ channels, with generator potential and graded potential models lacking voltage-gated Na+ channels. We identify three causes of information loss in the generator potential that are the by-product of action potential generation: (1) the voltage-gated Na+ channels necessary for action potential generation increase intrinsic noise and (2) introduce non-linearities, and (3) the finite duration of the action potential creates a ‘footprint’ in the generator potential that obscures incoming signals. These three processes reduce information rates by ~50% in generator potentials, to ~3 times that of spike trains. Both generator potentials and graded potentials consume almost an order of magnitude less energy per second than spike trains. Because of the lower information rates of generator potentials they are substantially less energy efficient than graded potentials. However, both are an order of magnitude more efficient than spike trains due to the higher energy costs and low information content of spikes, emphasizing that there is a two-fold cost of converting analogue to digital; information loss and cost inflation