1,720,987 research outputs found
Introducing state variables in Organic Electrochemical Transistors with application to biophysical systems
No full textOrganic electrochemical transistors (OECTs) are transducing devices that, placed in contact with an electrolyte solution, detect the ionic composition of that solution by measuring the channel current I. OECTs enable the streaming of continuously updated zero-to-low latency information and show, therefore, promise for being used as highly efficient biosensors. Nevertheless, apart from simple geometries, decoding such an information may be infeasible. Here, we show how.. can be processed to derive a reduced set of two variables that account for most of the information of a system: (i) the modulation m is the current gained by the system compared to its initial value; (ii) the effective time te is the time over which the response of the system stays above the 65% of its final value m and te can be reported in a diagram that is akin to the state space diagrams used in thermodynamics: points in the diagram describe the state of a system at a specific time; trajectories in the diagram describe the time evolution of that system. We show that the total electric charge.. exchanged by the system between two states A and B is independent on the path taken between them. This, in turn, implies that m and te are state variables of the system. In experiments with Solanum lycopersicum tomato plants, we show how this concept can be used to extract relevant information about a biophysical system without direct knowledge of its internal workings
An Explainable Smart Agriculture System based on In- Vivo Biosensors
No full textSome of the most significant factors regarding plant growth and food production are for sure water stress and drought. Predicting the water stress of crops in advance with respect to its visible signs is priceless and could permit one to intervene early to restore healthy growth conditions. In this paper, we discuss an Explainable Smart Agriculture System for monitoring the water stress status of tomato plants based on a novel in-vivo biosensor. Specifically, we embed, in the proposed system, an intrinsically explainable classifier, namely a fuzzy decision tree, to characterize the status of the plants in four different categories. To this aim, we extract four features related to the ionic currents inside the sap of the plants themselves. Thanks to the explainable classifier, we offer insights into the classification of the status of the plants. This contributes to a deeper understanding of the unseen processes occurring within the plants, enabling early detection of stress due to water shortage before it becomes visibly apparent. We evaluate the effectiveness of our approach considering the real data extracted from in-vivo biosensors deployed on two different types of tomato plants. Preliminary results show that the proposed explainable classifier achieves promising results in terms of both explainability and classification capability. Additionally, we present and discuss some examples of rules derived from the decision trees, emphasizing their significance in understanding the sap activities within plants. This understanding aids in implementing effective countermeasures, for example in real-world on-the-field automated irrigation systems, to maintain plant health
Towards continuous water stress classification in tomato plants via fuzzy Hoeffding trees and in-vivo biosensors
No full textWater stress and drought have a critical impact on plant growth and health, influencing and compromising agricultural productivity. Tools that can predict water stress in crops through quantifiable indicators provide valuable information and facilitate timely interventions aimed at maintaining and/or restoring optimal growth conditions before visible and difficult-to-recover symptoms appear. This study introduces an explainable Plant Health Monitoring System (PHMS), based on the continuous monitoring of water stress parameters in tomato plants using a novel in-vivo biosensor called "Bioristor". Our system integrates an explainable incremental classifier by design, specifically experimenting with the traditional Hoeffding decision tree and its fuzzy variant. By analyzing data from the Bioristor, the system evaluates plant health and classifies it into two distinct categories. Additionally, it employs an incremental learning approach, allowing the model to adapt and update during the monitoring period to maintain high classification performance. This continuous monitoring ensures the early detection of water stress, enabling prompt corrective actions. We present results based on a real-world dataset, leveraging four features derived from ionic currents within the plant sap, as measured by the Bioristor. The system performance was evaluated in terms of classification accuracy and model complexity, yielding promising outcomes. Moreover, the extracted decision rules offer valuable insights for implementing effective countermeasures to sustain plant health for extended periods
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
A Wireless Biosensor for in-Vivo and Real-Time Plant Monitoring for Smart Agriculture
No full textThis paper presents a wireless biosensor based on an organic electrochemical transistor and a low-power electronic system, with NB-Iot/Cat-M1 radio interface. The biosensor, implanted in the plant stem, allows the in-vivo evaluation of the concentration of nutrients dissolved as cations in the sap. The electronic circuit enables the real-time monitoring of the plant in the crop. The NB-IoT or Cat-M1 link, both available in the System-in-Package device selected for the proposed system, ensures almost ubiquitous availability of the network link, without severe limitations on the data payload. The low power consumption of the device allows more than 3-month of battery life time, adequate for most seasonal crops. Measurements on KCl solutions showed adequate sensor linearity up to 10-mM K+ concentration, while those performed on a sap of kiwi vines are in agreement with data available in the literature. The final electronic device will have a size of 30mm x 60mm, fitting the requirements of a monitoring device for small plants like tomato
From landraces to haplotypes, exploiting a genomic and phenomic approach to identify heat tolerant genotypes within durum wheat landraces
No full textDry and hot climates severely impact wheat yields, necessitating the development of innovative solutions to accelerate the breeding and selection of more adaptable durum wheat genotypes. The aim of this study was to identify new wheat ecotypes that can bridge the gap between commercial varieties and adaptability to ongoing climate change. In this study, advanced genomic and phenomic techniques were combined to characterize a set of durum wheat landraces derived from single seed descent (SSD). This approach enabled the identification of novel variability in the TdHsp26-A1 and -B1 genes. As a result, 38 durum wheat genotypes were analyzed using targeted enrichment PCR, leading to the identification of 17 novel haplotype combinations with SNPs in the TdHsp26 genes. The response of these SSD haplotypes to heat stress was characterized at both the seedling and tillering growth stages. Phenotypic analysis of contrasting genotypes led to the selection of two distinct genotypes: SSD69 and SSD397. During heat stress, SSD69 exhibited altered accumulation of H2O2 and MDA content under both growth conditions, providing new insights into the oxidative response to heat stress. Additionally, this work identifies phenotypic traits that are suitable for detecting differences between variants. The geographic distribution of the different alleles aligned with the spread of durum wheat from its center of origin
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Development of an In Vivo Sensor to Monitor the Effects of Vapour Pressure Deficit (VPD) Changes to Improve Water Productivity in Agriculture
No full textEnvironment, biodiversity and ecosystem services are essential to ensure food security and nutrition. Managing natural resources and mainstreaming biodiversity across agriculture sectors are keys towards a sustainable agriculture focused on resource efficiency. Vapour Pressure Deficit (VPD) is considered the main driving force of water movements in the plant vascular system, however the tools available to monitor this parameter are usually based on environmental monitoring. The driving motif of this paper is the development of an in-vivo sensor to monitor the effects of VPD changes in the plant. We have used an in vivo sensor, termed "bioristor", to continuously monitor the changes occurring in the sap ion's status when plants experience different VPD conditions and we observed a specific R (sensor response) trend in response to VPD. The possibility to directly monitor the physiological changes occurring in the plant in different VPD conditions, can be used to increase efficiency of the water management in controlled conditions thus achieving a more sustainable use of natural resources
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