Simulation par le modèle AgriFlux du devenir de l'atrazine et du dééthylatrazine dans un sol du Québec sous mais sucré

Les outils mathématiques sont de plus en plus utilisés pour simuler la contamination d'origine agricole des eaux souterraines. Le modèle AgriFlux permet, à l'aide du module PestiFlux, de simuler les processus responsables du devenir des pesticides dans le sol: ruissellement, volatilisation, adsorption/désorption rapide, adsorption/désorption lente, complexation par la matière organique dissoute, biodégradation en sous-produits, hydrolyse, drainage et lessivage. AgriFlux est utilisé pour simuler le devenir de l'atrazine et du dééthylatrazine sur une parcelle expérimentale de la région de Québec (Québec, Canada) cultivée en maïs sucré (Zea mays, L.) traité à l'atrazine. Des prélèvements d'eau interstitielle ont été réalisés (1986-1990) à l'aide de lysimètres avec succion (0,5 et 1,0 m de profondeur) et analysés pour leur contenu en atrazine et dééthylatrazine. De manière générale, AgriFlux reproduit bien l'évolution des concentrations mesurées, dans le temps et dans le profil de sol (r=0,76). Certains pics de concentrations observés sur le terrain ne sont toutefois pas représentés ou sont décalés dans le temps, ce qui pourrait être attribué à une sous-estimation de la variabilité spatiale des paramètres. Le rapport dééthylatrazine/atrazine est relativement bien simulé en 1988 à 0,5 m, mais est moins représentatif pour les autres données, ce qui pourrait être dû à une certaine imprécision dans la simulation de la biodégradation. Une analyse de sensibilité du modèle aux variations de différents paramètres a montré que le paramètre le plus influent dans les conditions testées est la constante de biodégradation. Les résultats obtenus montrent la pertinence d'AgriFlux (PestiFlux) dans la simulation du devenir des pesticides dans le sol et donc des risques de contamination des eaux souterraines en région agricole.Groundwater and surface water contamination by agricultural practices has become an increasingly preoccupying problem. Mathematical models are valuable tools to help prevent this type of pollution from non-point sources. AgriFlux is a mechanistic, stochastic model simulating the fate of agricultural contaminants in the unsaturated zone at the scale of the agricultural field. AgriFlux, through the PestiFlux module, now simulates pesticide transformations in the soil from their application to the field until their leaching with percolating water. The processes represented include volatilization, complexation by the soluble organic matter, instantaneous adsorption and desorption, slow adsorption and desorption to less available sites, biodegradation to by-products and hydrolysis to non-toxic compounds. The pesticide freely dissolved in solution or complexed with soluble organic matter can be mobilized with runoff, drainage and leaching waterAn application of PestiFlux to an experimental field near Quebec City (Quebec, Canada) is presented. The soil is a well-drained loamy sand cropped from 1986 to 1990 with sweet corn (Zea Mays, L.) receiving atrazine treatments (1.6 to 1.8 kg.ha-1 of active ingredient). Interstitial water was sampled using 12 suction lysimeters located at both the 0.5 and 1.0 m depths in the soil. All stations were sampled monthly in 1986 and 1987 and the collected water was analyzed for atrazine alone. In 1988, the sampling (every two weeks) was limited to the lysimeters which had previously shown the highest pesticide concentrations (two lysimeters at 0.5 m and one lysimeter at 1.0 m). The interstitial water was analyzed for atrazine and deethylatrazine. There was no sampling in 1989. In 1990, all stations were sampled on a weekly basis and a composite water sample obtained for each depth was analyzed for both compounds. Most of the pesticide-related parameters required to run PestiFlux were deduced from the literature, with the exception of the biodegradation rate coefficient which was estimated from field monitoring of atrazine. The parameters required to simulate water fluxes and plant uptake were the same as those used in a previous application of AgriFlux to the same experimental field for the simulation of nitrate fluxes (LAROCQUE and BANTON, 1995).Results show that PestiFlux generally represents well the measured atrazine and deethylatrazine concentrations in the interstitial water at 0.5 and 1.0 m. A linear regression using all measured and simulated concentrations indiscriminately gives a correlation coefficient of 0.76 when using the logarithm of concentrations. The temporal evolution of the pesticide concentrations is relatively well simulated, especially on the long term with an adequate representation of the increase in pesticide concentrations in the soil profile at 1.0 m. This increase is probably due to the fallow existing in 1985 which would have favored leaching of adsorbed pesticide below the soil profile, leaving only low residual pesticide concentrations. Over one growing season, the transport of atrazine and deethylatrazine is well represented by the model, although some peak concentrations are delayed or attenuated. This result could be due to an underestimation of the spatial variability of the different parameters. It is possible that the coefficient of variation of 10% adopted may not represent adequately the spatial variation of some parameters. Nevertheless, most measured concentrations of both compounds are within the mean simulated concentrations and included between two standard deviations. For 1988, most of the measured concentrations are located near the upper limit of the envelope curve which is consistent with the fact that the sampled lysimeters were those yielding the highest concentrations. The simulated concentrations show a generally good representation of the relative atrazine and deethylatrazine concentrations. The ratio of the mean deethylatrazine to atrazine concentrations provides a closer look at the adequacy between the simulated concentrations of both compounds. A comparison between the measured and the simulated ratios shows a good adequacy at 0.5 m in 1988 and both over- and under-estimation of the ratio for the other available data. This is probably due to an imprecision in the simulation of biodegradation rates during some periods. All the parameters used in the simulation have an important uncertainty, due to the significant spatial variation of the parameters in the field and to the imprecise knowledge of some pesticide characteristics. In order to identify the parameters which have the most important influence on the results, an analysis of the sensitivity of the cumulated leaching mass of both compounds at 1.0 m to variations of the different input parameters was performed. The results show that the biodegradation rate has the greatest influence on the results. This is probably due to the importance of this process in the simulated situation. This result confirms the importance of an adequate quantification of this parameter and of its spatial variation. PestiFlux offers a comprehensive representation of pesticide transformations in the soil and is easy to use. As a module of AgriFlux, it has the advantage of being integrated into a well-tested and reliable modeling environment. The presented simulation results show that, apart from some limits due to the quantification of some of the parameters, PestiFlux is a useful and comprehensive tool for estimating potential groundwater pollution by pesticides

Simplification rationnelle des outils hydrologiques de gestion : recommandations méthodologiques pour la construction de modèles semi-empiriques à origine mécaniste

Les modèles de simulation hydrologiques sont reconnus comme des outils mathématiques très performants mais généralement d'application difficile, principalement à cause du nombre élevé des paramètres requis. À l'inverse, les outils actuels de gestion sont généralement développés à l'aide d'approches empiriques limitant leur application. De plus, leurs paramètres ne sont pas des grandeurs mesurables et doivent être ajustés pour chaque situation. Une approche est proposée pour le développement d'outils semi empiriques de gestion. Elle consiste à simuler un grand nombre de scénarios en utilisant un modèle complexe de simulation puis à rationaliser l'information obtenue pour développer un nouveau modèle semi empirique. L'exemple illustrant cette approche concerne l'évaluation des flux d'eau ruisselée à la surface des champs, lessivée vers la nappe souterraine et drainée par les drains agricoles spécifiquement pour le contexte du Québec. À partir des résultats de simulation de 4500 scénarios, une simplification.rationalisation a permis de réduire à 120 le nombre de scénarios de référence à l'aide desquels peuvent être évalués tous les scénarios possibles par de simples interpolations linéaires. Une application de l'algorithme résultant sur un site du Québec a montré la bonne concordance entre les résultats calculés et mesurés. À la fois l'ordre de grandeur du ruissellement et du drainage et leur grandeur relative sont bien évalués.Considering the complexity of the water cycle in soil systems, models are used more than ever in parallel with field investigations to assist in the decision making process (KHAKURAL et ROBERT, 1993). Most available models are either too complicated (many non-measurable parameters) or too simple (empirical or site-specific) to be used as management tools. Such tools should conform to known theory and should be structured to enable efficient analysis of field situations with minimal requirements for parameters (CARSEL et al 1984). However, if the mechanistic models are very performing tools with regards to their representation of the processes and for the accuracy and reliability of their results, they are criticized for their complexity and for the large number of parameters they require. For this reason, their potential application as management tools cannot be recommended especially in preliminary investigations when the methodology has to be straight forward and rapidly implemented. On the other hand, existing management tools are often developed using an empirical approach for a specific context which considerably limits their transferability to different situations. Moreover, their empirical parameters often cannot be measured for the new situations, and must be adjusted for each new application. A new approach conciliating the qualities of both kinds of tools was elaborated for the development of management tools. This approach consists in using mechanistic models for simulating a set of possible situations and in rationalizing the information obtained by simulation through regression analyses or other methods. An example of this methodology is presented in this paper with the development of the hydrological part (runoff, leaching and drainage) of a management tool dedicated to the evaluation of nutrient losses related to manure applications. Developed for the Quebec conditions, 4500 theoretical situations were considered corresponding to ten climates, nine soil textures, 25 crops and two slope values. Independently, agricultural management practices and drainage were taken into account.For the mechanistic simulation of the water budget in the 4500 theoretical situations, the hydrologic module of the mechanistic-stochastic model AgriFlux was used (BANTON et al. 1993b). Because of the important field variability of most parameters, the stochastic AgriFlux model incorporates the variability resulting from field heterogeneity, measurement errors and intrinsic uncertainty related to parameter definition. The soil profile is divided in plot scale homogeneous horizons (or compartments) and a daily time step is used in the calculations. The water budget module in AgriFlux is named HydriFlux and simulates all the water-related processes (precipitations, snowmelt, infiltration, runoff, water uptake by plants, evaporation, percolation and drainage) using characteristic water contents and unsaturated hydraulic conductivity.In the example presented, the simulation results obtained by running HydriFlux have shown that the soil water fluxes (runoff and percolation) vary as linear functions of both the annual rain volume (the most important characteristic of the climate) and the logarithm of the saturated hydraulic conductivity (the most important characteristic of the soil type). A reduction of the number of crops could also be achieved by taking into account the water needs and the water uptake curves of the crops. This rationalization-simplification reduced the number of theoretical simulations to be stored in the management tool to 120 (2 climates x 3 textures x 10 crops x 2 slopes). These represent only 2.7% of the initial situations simulated by the mechanistic HydriFlux model. The different water fluxes are stored in the management tool as tables in which direct interpolations are performed to calculate the fluxes corresponding to all the potential intermediary situations. Such developed management tool presents good qualities at the same time for its calculation speed, for its easy parameterization, for the reliability of its evaluation (through the evaluation of the mechanistic model) and for its high transferability and applicability to various situations. The calculations are rapidly done and their programming can be very easily made by using a spreadsheet software.An application of this evaluation method has been done on an experimental site located in Quebec (ENRIGHT et MADRAMOOTOO, 1994), the only one for which both the runoff and the drainage have been measured during many years (1989 to 1991, April to December). The application on two fields (1.84 et 4.63 ha) has shown a good concordance between the calculated and measured results, as well for the magnitude of the fluxes than for the relative importance of these fluxes. Moreover, this application has shown that the variability of the measured values is higher than the calculated ones, attesting of the great influence of the variations in climatic, soil, crop and management conditions on the water budget. However, the good evaluation of the fluxes (for relative and absolute values) confirms the reliability of the proposed approach and of the simplification

Contamination nitratée des eaux souterraines d'un bassin versant agricole hétérogène: 1. Évaluation des apports à la nappe (modèle Agriflux)

Au cours des dernières décennies, la hausse de la productivité agricole s'est accompagnée d'une forte augmentation des fertilisations azotées qui a entraîné l'augmentation des concentrations en nitrates dans les eaux souterraines. Récemment, les études sur la gestion des pollutions diffuses agricoles ont intégré l'échelle du bassin versant hydrologique. Dans cet article, une approche basée sur un découpage en secteurs pédologiquement et agronomiquement homogènes a été élaborée pour permettre l'utilisation d'un modèle d'évaluation (AgriFlux), et obtenir les flux d'eau et de nitrates sortant de la zone racinaire sur l'ensemble d'un bassin. La modélisation du bassin de La Jannerie a porté sur une période de quatre ans impliquant 19 zones de simulation. L'influence du cycle végétatif des cultures et leur nature sur l'évolution des flux de nitrates a été mise en évidence par des simulations préliminaires, de même que l'influence du type de sol. L'évolution des concentrations moyennes saisonnières en nitrates sortant de la zone racinaire montre que les fertilisations minérales ne sont pas les seules sources importantes de nitrates dans les sols. Les pratiques culturales, comme le retournement des prairies, l'enfouissement des résidus de récoltes ou l'assolement, ont une forte influence sur la dynamique spatiale et temporelle des flux de nitrates percolant vers la nappe.In agricultural regions, groundwater contamination by nitrogen compounds originating from fertilizers is one of the most significant environmental problems. Along with in situ monitoring, simulation models have been developed for non point pollution (nitrates, pesticides) in order to evaluate both the level and the extent of the contamination. Simulation models, originally intended for research purposes in relation to the dynamics of agricultural systems, have been adapted and applied to environmental management in order to quantify water volumes and contaminant masses likely to reach groundwater systems. Recently, mechanistic models such as Agriflux (Banton et al., 1993) have been developed for use in the field. Agriflux is based on a mechanistic approach to the processes and incorporates a stochastic analysis that takes into account the spatial variability of the parameters. lt. calculates nitrate concentrations as well as water fluxes in the unsaturated zone. In the present study, environmental management principles integrating heterogeneity in soils and agricultural practices were applied to an agricultural watershed in Poitou (France). Preliminary simulations were carried out in order to estimate the influence of various parameters on the nitrate and water fluxes. First, a three-year wheat mono-crop was simulated using the same fertilization rate for each year. The calculated nitrate concentrations follow a trend opposite to that of the seasonal growing crop. To estimate the influence of the soil characteristics on the nitrate concentrations, the four types of soil in the watershed were simulated using the same three-year crop rotation. The results show that the soil type directly influences the amount of nitrate leaching. Under different soils types, the evolution of the concentrations over time follows the same pattern, but the concentration levels are significantly different. To quantify the impact of crops on the nitrate concentrations, the main crop rotations were simulated for the same type of soil. This set of simulations underlines the environmental differences between winter and spring crops. lt. also shows the differences induced by the presence of residues. The La Jannerie watershed was divided into homogeneous zones for soil and crop characteristics. During a four-year period, seasonal and annual nitrate concentrations were calculated for each homogeneous zone from the daily water and nitrate fluxes simulated with Agriflux. The results demonstrate the influence of the agricultural practices on the calculated concentrations. Overall, nitrate levels remain quasi-constant during the periods when the crops are active but vary considerably during the winter when the crops are absent or inactive. This winter period corresponds to a peak in nitrate leaching because of the excess rainfall and the absence of nitrogen uptake by the plants. The incorporation of crop residues in the soil in the autumn generates a high production of nitrates during winter due to the mineralization of the organic nitrogen.Two different environmental approaches can be used jointly to evaluate agricultural practices. The first consists of a comparison between the nitrate flux that can reach the saturated area and the fertilizer rate. This approach provides an estimate of the amount of nitrogen lost to the aquifer. Simulations with Agriflux show that the nitrate fluxes are highest during the autumn when plant uptake is non-existent, except in fields with winter crops. The second approach compares the calculated nitrate concentrations that may occur in the aquifer with recognized water quality criteria. lt. is interesting and important to note that, during the simulated period, the calculated concentrations in the leach were often much lower than the water quality criterion (50 mg NO3/L). This result indicates that the fertilization practices applied in the watershed during this period tended to approach the real crop requirements (minimal requirements) and were more environmentally adequate (environmental optimum) than those used previously

Diarrhoea, Dysentery, and the Clap: Connecting the Military Lifestyle to Literary & Skeletal Evidence of Reactive Arthropathy Induced by Bacterial Infections

Military combatants are frequently exposed to physical exertion, sleep deprivation, deficient diets, and stress, which can all reduce the immune system’s ability to ward off infections. Making matters worse, combatants frequently inhabit overcrowded and unsanitary living conditions, which allow bacteria to thrive. As a result of these circumstances, the military lifestyle is associated with increased exposure and susceptibility to infectious diseases. This explains why epidemics are extremely common during times of war, especially in pre-twentieth century conflicts. Though military infectious diseases have been the topic of much research, bioarchaeological contributions have been limited, as most infectious diseases do not cause direct skeletal changes. For example, diarrhoea, dysentery, gonorrhea, and tonsillitis do not cause skeletal changes, but all are known to have been common among historical combatants. Though direct skeletal changes are not produced, the pathogenic bacteria causing these ailments can trigger reactive arthropathies (arthritic conditions caused by microbial infections), which includes the Spondyloarthropathies. Spondyloarthropathies cause skeletal changes and can be observed in archaeological remains. As such, the present research has chosen to explore the potential consequences of military infectious disease by answering the following question: were reactive arthropathies an occupational hazard to past military combatants? This question is answered through two methods. First, historical research methods were employed to investigate the primary research question and to provide a detailed medical history of the emblematic example of reactive arthropathy, Reactive Arthritis. Secondly, a palaeoepidemiological study was designed and implemented to understand the prevalence of reactive pathology in military skeletal assemblages; this is a novel bioarchaeological means of understanding the potential impact of military infectious diseases

A Deep Learning-based Approach to Identifying and Mitigating Network Attacks Within SDN Environments Using Non-standard Data Sources

Modern society is increasingly dependent on computer networks, which are essential to delivering an increasing number of key services. With this increasing dependence, comes a corresponding increase in global traffic and users. One of the tools administrators are using to deal with this growth is Software Defined Networking (SDN). SDN changes the traditional distributed networking design to a more programmable centralised solution, based around the SDN controller. This allows administrators to respond more quickly to changing network conditions. However, this change in paradigm, along with the growing use of encryption can cause other issues. For many years, security administrators have used techniques such as deep packet inspection and signature analysis to detect malicious activity. These methods are becoming less common as artificial intelligence (AI) and deep learning technologies mature. AI and deep learning have advantages in being able to cope with 0-day attacks and being able to detect malicious activity despite the use of encryption and obfuscation techniques. However, SDN reduces the volume of data that is available for analysis with these machine learning techniques. Rather than packet information, SDN relies on flows, which are abstract representations of network activity. Security researchers have been slow to move to this new method of networking, in part because of this reduction in data, however doing so could have advantages in responding quickly to malicious activity. This research project seeks to provide a way to reconcile the contradiction apparent, by building a deep learning model that can achieve comparable results to other state-of-the-art models, while using 70% fewer features. This is achieved through the creation of new data from logs, as well as creation of a new risk-based sampling method to prioritise suspect flows for analysis, which can successfully prioritise over 90% of malicious flows from leading datasets. Additionally, provided is a mitigation method that can work with a SDN solution to automatically mitigate attacks after they are found, showcasing the advantages of closer integration with SDN

Bacterial Death Results from Mutations Made in Translocation Peptide of Leucyl-tRNA Synthetase

The family of aminoacyl-tRNA synthetases (aaRSs) ensures the fidelity of translation through providing a pool of correctly aminoacylated tRNA products that become incorporated by the ribosome. Leucyl-tRNA synthetase (LeuRS) has two functionally separate domains, one is the aminoacylation domain and the other is the CP1 editing domain. LeuRS can aminoacylate noncognate amino acids, therefore it relies on the CP1 editing domain to hydrolyze misaminoacylated tRNA products before they are released from the enzyme. The LeuRS enzyme must undergo a structural transition state in its reaction cycle in order to translocate the 3\u27 acceptor stem of tRNA 30 Å from the aminoacylation active site to the CP1 domain hydrolytic active site. The translocation event is difficult to study, but we believe that we have generated mutations within LeuRS that alter the translocation event of tRNA. The mutations that we have generated lead to bacterial death in Escherichia coli (E. coli). Circular dichorism experiments indicate that our mutations do not significantly alter the secondary structure of LeuRS. In vitro biochemical studies demonstrate that these mutations reduce the rates of aminoacylation and hydrolysis, while also displaying misaminoacylation activity. We attribute these biochemical findings to the resulting bacterial death that is caused by these mutation

Bacterial Death Results from Mutations Made in Translocation Peptide of Leucyl-tRNA Synthetase

The family of aminoacyl-tRNA synthetases (aaRSs) ensures the fidelity of translation through providing a pool of correctly aminoacylated tRNA products that become incorporated by the ribosome. Leucyl-tRNA synthetase (LeuRS) has two functionally separate domains, one is the aminoacylation domain and the other is the CP1 editing domain. LeuRS can aminoacylate noncognate amino acids, therefore it relies on the CP1 editing domain to hydrolyze misaminoacylated tRNA products before they are released from the enzyme. The LeuRS enzyme must undergo a structural transition state in its reaction cycle in order to translocate the 3\u27 acceptor stem of tRNA 30 Å from the aminoacylation active site to the CP1 domain hydrolytic active site. The translocation event is difficult to study, but we believe that we have generated mutations within LeuRS that alter the translocation event of tRNA. The mutations that we have generated lead to bacterial death in Escherichia coli (E. coli). Circular dichorism experiments indicate that our mutations do not significantly alter the secondary structure of LeuRS. In vitro biochemical studies demonstrate that these mutations reduce the rates of aminoacylation and hydrolysis, while also displaying misaminoacylation activity. We attribute these biochemical findings to the resulting bacterial death that is caused by these mutation

Single-Cell Regulatory Network Inference and Clustering Identifies Cell-Type Specific Expression Pattern of Transcription Factors in Mouse Sciatic Nerve

Advances in single-cell RNA sequencing technologies and bioinformatics methods allow for both the identification of cell types in a complex tissue and the large-scale gene expression profiling of various cell types in a mixture. In this report, we analyzed a single-cell RNA sequencing (scRNA-seq) dataset for the intact adult mouse sciatic nerve and examined cell-type specific transcription factor expression and activity during peripheral nerve homeostasis. In total, we identified 238 transcription factors expressed in nine different cell types of intact mouse sciatic nerve. Vascular smooth muscle cells have the lowest number of transcription factors expressed with 17 transcription factors identified. Myelinating Schwann cells (mSCs) have the highest number of transcription factors expressed, with 61 transcription factors identified. We created a cell-type specific expression map for the identified 238 transcription factors. Our results not only provide valuable information about the expression pattern of transcription factors in different cell types of adult peripheral nerves but also facilitate future studies to understand the function of key transcription factors in the peripheral nerve homeostasis and disease.</jats:p

Expression profiling and cross-species RNA interference (RNAi) of desiccation-induced transcripts in the anhydrobiotic nematode Aphelenchus avenae.

BACKGROUND: Some organisms can survive extreme desiccation by entering a state of suspended animation known as anhydrobiosis. The free-living mycophagous nematode Aphelenchus avenae can be induced to enter anhydrobiosis by pre-exposure to moderate reductions in relative humidity (RH) prior to extreme desiccation. This preconditioning phase is thought to allow modification of the transcriptome by activation of genes required for desiccation tolerance. RESULTS: To identify such genes, a panel of expressed sequence tags (ESTs) enriched for sequences upregulated in A. avenae during preconditioning was created. A subset of 30 genes with significant matches in databases, together with a number of apparently novel sequences, were chosen for further study. Several of the recognisable genes are associated with water stress, encoding, for example, two new hydrophilic proteins related to the late embryogenesis abundant (LEA) protein family. Expression studies confirmed EST panel members to be upregulated by evaporative water loss, and the majority of genes was also induced by osmotic stress and cold, but rather fewer by heat. We attempted to use RNA interference (RNAi) to demonstrate the importance of this gene set for anhydrobiosis, but found A. avenae to be recalcitrant with the techniques used. Instead, therefore, we developed a cross-species RNAi procedure using A. avenae sequences in another anhydrobiotic nematode, Panagrolaimus superbus, which is amenable to gene silencing. Of 20 A. avenae ESTs screened, a significant reduction in survival of desiccation in treated P. superbus populations was observed with two sequences, one of which was novel, while the other encoded a glutathione peroxidase. To confirm a role for glutathione peroxidases in anhydrobiosis, RNAi with cognate sequences from P. superbus was performed and was also shown to reduce desiccation tolerance in this species. CONCLUSIONS: This study has identified and characterised the expression profiles of members of the anhydrobiotic gene set in A. avenae. It also demonstrates the potential of RNAi for the analysis of anhydrobiosis and provides the first genetic data to underline the importance of effective antioxidant systems in metazoan desiccation tolerance.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are