Jia Liu

Wenyan Zhang

Haijian Du

Xiaoyun Leng

Jin-Hua Li

Hongmiao Pan

Jianhong Xu

Long-Fei Wu

Tian Xiao
email: txiao@qdio.ac.cn

Seasonal changes in the vertical distribution of two types of multicellular magnetotactic prokaryotes in the sediment of Lake Yuehu, China

There are two genetically distinct morphological types of multicellular magnetotactic prokaryotes (MMPs) in the intertidal zone of Lake Yuehu (China): ellipsoidal MMPs (eMMPs) and spherical MMPs (sMMPs). We studied the vertical distribution of both types of MMPs in the sediment at Lake Yuehu during 1 year. Both types of MMPs were observed at sediment depths ranging from 1 to 34 cm, depending on the seasons. The eMMPs distributed at depths of 2-34 cm during spring, 1-11 cm during summer, 2-21 cm during autumn and 9-32 cm during winter. The eMMP species Candidatus Magnetananas rongchenensis, with magnetite magnetosomes, dominated at all distribution depths. These results suggested that Ca. M. rongchenensis migrated vertically during four seasons. The vertical profiles of oxidation-reduction potential (ORP) in Lake Yuehu changed seasonally, and these changes coincided with the seasonal distribution of MMPs, suggesting that the ORP affected the vertical distribution of MMPs. In addition, high concentrations of ammonium and silicate were associated with low abundances of MMPs.

Introduction

Magnetotactic bacteria (MTB) synthesize magnetosomes (intracellular single-magnetic-domain crystals) that allow them to orient and navigate along geomagnetic field lines. Multicellular magnetotactic prokaryotes (MMPs) are gram-negative cell aggregates [START_REF] Farina | Ultrastructure of a Magnetotactic Microorganism[END_REF][START_REF] Amann | Diversity and taxonomy of magnetotactic bacteria[END_REF][START_REF] Keim | Structure, behavior, ecology and diversity of multicellular magnetotactic prokaryotes[END_REF][START_REF] Lefe `vre | Nonmagnetotactic multicellular prokaryotes from low-saline, nonmarine aquatic environments and their unusual negative phototactic behavior[END_REF][START_REF] Kolinko | Single-cell analysis reveals a novel uncultivated magnetotactic bacterium within the candidate division OP3[END_REF] that are unique because of their synchronized cell division and coordination of complex movements (Keim et al., 2004b;[START_REF] Abreu | Candidatus Magnetoglobus multicellularis', a multicellular, magnetotactic prokaryote from a hypersaline environment[END_REF]. There are two genetically distinct morphotypes of MMPs. The spherical MMPs (sMMPs) are 3-12 lm in diameter and comprise 10-40 cells arranged with helical symmetry [START_REF] Keim | Structure, behavior, ecology and diversity of multicellular magnetotactic prokaryotes[END_REF][START_REF] Abreu | Candidatus Magnetoglobus multicellularis', a multicellular, magnetotactic prokaryote from a hypersaline environment[END_REF][START_REF] Wenter | Ultrastructure, tactic behaviour and potential for sulfate reduction of a novel multicellular magnetotactic prokaryote from North Sea sediments[END_REF]Zhang et al., 2014a). The ellipsoidal MMPs (eMMPs) are 8-23 lm long, 7-17 lm wide and comprise 28-101 cells arranged in interlaced circles [START_REF] Lefe `vre | Characterization of Mediterranean magnetotactic bacteria[END_REF][START_REF] Zhou | A novel genus of multicellular magnetotactic prokaryotes from the Yellow Sea[END_REF][START_REF] Chen | A novel species of ellipsoidal multicellular magnetotactic prokaryotes from Lake Yuehu in China[END_REF]. The sMMPs were first discovered in a brackish lagoon in Brazil [START_REF] Farina | Ultrastructure of a Magnetotactic Microorganism[END_REF] and have a wide geographic distribution in sediments [START_REF] Rodgers | Intercellular Structure in a Many-Celled Magnetotactic Prokaryote[END_REF]Keim et al., 2004a;Keim et al., 2004b;[START_REF] Greenberg | Observation of magnetoreceptive behavior in a multicellular magnetotactic prokaryote in higher than geomagnetic fields[END_REF]Simmons and Edwards, 2007;[START_REF] Wenter | Ultrastructure, tactic behaviour and potential for sulfate reduction of a novel multicellular magnetotactic prokaryote from North Sea sediments[END_REF][START_REF] Zhou | Occurrence and microscopic analyses of multicellular magnetotactic prokaryotes from coastal sediments in the Yellow Sea[END_REF]Zhang et al., 2014a) and chemically stratified waters [START_REF] Simmons | Spatiotemporal distribution of marine magnetotactic bacteria in a seasonally stratified coastal salt pond[END_REF][START_REF] Moskowitz | Magnetic properties of marine magnetotactic bacteria in a seasonally stratified coastal pond (Salt Pond, MA, USA)[END_REF]. In contrast, eMMPs are known from only the intertidal sediments of a few coastal areas [START_REF] Lefe `vre | Characterization of Mediterranean magnetotactic bacteria[END_REF][START_REF] Zhou | A novel genus of multicellular magnetotactic prokaryotes from the Yellow Sea[END_REF][START_REF] Chen | A novel species of ellipsoidal multicellular magnetotactic prokaryotes from Lake Yuehu in China[END_REF][START_REF] Chen | Novel species and expanded distribution of ellipsoidal multicellular magnetotactic prokaryotes[END_REF].

In aquatic environments, sMMPs with greigite magnetosomes occur at the base of the oxic-anoxic interface (OAI) or in the anoxic zone below the OAI, but unicellular MTB, such as cocci and short rods, occur within the OAI [START_REF] Simmons | Spatiotemporal distribution of marine magnetotactic bacteria in a seasonally stratified coastal salt pond[END_REF]Simmons et al., 2007;[START_REF] Moskowitz | Magnetic properties of marine magnetotactic bacteria in a seasonally stratified coastal pond (Salt Pond, MA, USA)[END_REF]. The first study of the vertical distribution of sMMPs in sediments occurred in the Araruama Lagoon (Brazil) and reports that sMMPs exist within the anaerobic zone, especially in the top 4.0 cm layer of sediment [START_REF] Abreu | Candidatus Magnetoglobus multicellularis', a multicellular, magnetotactic prokaryote from a hypersaline environment[END_REF]. A study in the Wadden Sea (Germany) reports that 95% of sMMPs are present in a 5 to 10 mm layer at the upper boundary of the black FeS-containing sediment layer [START_REF] Wenter | Ultrastructure, tactic behaviour and potential for sulfate reduction of a novel multicellular magnetotactic prokaryote from North Sea sediments[END_REF]. A study in Praia da Baleia (Brazil) reports the greatest abundance of sMMPs within the oxycline during June and a very different vertical distribution during March [START_REF] Sobrinho | Geochemical Characteristics Related to the Gregite-Producing Multicellular Magnetotactic Prokaryote Candidatus Magnetoglobus multicellularisin a Hypersaline Lagoon[END_REF]. A previous study in Huiquan Bay (Shandong Province, China) reports a wider and deeper vertical distribution of magnetiteproducing sMMPs during November. Specifically, sMMPs are present from depths of 2 to 16 cm, with a maximum abundance at approximately 10 cm [START_REF] Zhou | Adaptation of spherical multicellular magnetotactic prokaryotes to the geochemically variable habitat of an intertidal zone[END_REF]. In a 45 day microcosm experiment, the vertical distribution of sMMPs was shown to change as they moved to the upper layers, apparently in search of a new microniche [START_REF] Martins | Spatiotemporal distribution of the magnetotactic multicellular prokaryote Candidatus Magnetoglobus multicellularis in a Brazilian hypersaline lagoon and in microcosms[END_REF]. Although there are a few studies on the vertical distributions of sMMPs, only a few centimetres of upper sediment have been examined. However, there are no detailed studies of the distribution of sMMPs at greater depths. Moreover, little is known about the vertical distribution of eMMPs or the seasonal changes in the vertical distribution of sMMPs and eMMPs.

Recent studies have reported a new species of sMMP (Candidatus Magnetomorum rongchengroseum) and a new species of eMMP (Candidatus Magnetananas rongchenensis) in the intertidal sediment of Lake Yuehu (Rongcheng City, China). The sMMPs in this location contain only magnetite-type magnetosomes or both magnetite-type and greigite-type magnetosomes [START_REF] Zhou | Occurrence and microscopic analyses of multicellular magnetotactic prokaryotes from coastal sediments in the Yellow Sea[END_REF]Zhang et al., 2014a). In contrast, eMMPs with bullet-shaped magnetite magnetosomes occur in most cases, but eMMPs with both rectangular greigite magnetosomes and bullet-shaped magnetite magnetosomes occasionally occur during autumn [START_REF] Chen | A novel species of ellipsoidal multicellular magnetotactic prokaryotes from Lake Yuehu in China[END_REF]. A further study has reported that the abundance of eMMPs and sMMPs in the top 10 cm of sediment is high during summer and autumn but low during spring and winter [START_REF] Du | Temporal distributions and environmental adaptations of two types of multicellular magnetotactic prokaryote in the sediments of Lake Yuehu, China[END_REF]. The abundance of sMMPs always peaks before that of eMMPs. No mechanism has been proposed to explain the impact of environmental factors on MMP abundance. Lake Yuehu (368 43 0 2378 27 0 N, 1228 09 0 21228 42 0 E, approximately 4.94 km 2 ), also known as Swan Lake, is a shallow coastal lagoon with stabilized semi-diurnal tides and limited human activities located on the east side of the Shandong Peninsula (China). The four seasons at Lake Yuehu are distinct, and throughout the year, the temperature of the sediment ranges from 20.1 to 27.48C, the pH ranges from 7.43 to 8.60 and the mean annual salinity (SAL) is 28.0&. The sediment consists of well-proportioned fine sand with yellow surface layers, grey subsurface layers and black deep layers that is due to changes in sulfur content with depth (Zhang et al., 2014a;[START_REF] Chen | A novel species of ellipsoidal multicellular magnetotactic prokaryotes from Lake Yuehu in China[END_REF][START_REF] Du | Temporal distributions and environmental adaptations of two types of multicellular magnetotactic prokaryote in the sediments of Lake Yuehu, China[END_REF]. Previous studies have reported the biological characteristics and temporal distribution of MMPs in the top 10 cm of sediment in Lake Yuehu (Zhang et al., 2014a;[START_REF] Chen | A novel species of ellipsoidal multicellular magnetotactic prokaryotes from Lake Yuehu in China[END_REF][START_REF] Du | Temporal distributions and environmental adaptations of two types of multicellular magnetotactic prokaryote in the sediments of Lake Yuehu, China[END_REF], but little is known about the vertical distribution of these MMPs. Here, we report a detailed and systematic investigation of the vertical distribution of eMMPs and sMMPs in Lake Yuehu and try to gain insight into the physiological mechanism.

Results and discussion

Seasonal changes in the vertical distribution of eMMPs and sMMPs

MMPs were present in top 34 cm of sediment in the intertidal zone of Lake Yuehu (Fig. 1A andB). Analysis by depth and season indicated that the maximum abundance of eMMPs was 148 individuals per cm 3 (ind/cm 3 ) at 4 cm in depth during autumn and the maximum abundance of sMMPs was 182 ind/cm 3 at 5 cm during summer (Table 1).

There were seasonal variations in the vertical distribution of eMMPs (Fig. 1A). During spring, eMMPs occurred at depths of 2 to 34 cm. The maximum abundance of eMMPs was at 6 cm (127 ind/cm 3 , Fig. 1A; Table 1). During summer, eMMPs were in the top 1 to 11 cm of sediment, with a maximum abundance at 5 cm (72 ind/cm 3 ). During autumn, eMMPs were present at depths of 2 to 21 cm, with a maximum abundance at 4 cm (148 ind/cm 3 ). During winter, eMMPs were present at depths of 9 to 32 cm, with a maximum abundance at 19 cm (89 ind/cm 3 ). Thus, eMMPs generally occurred in shallow layers during summer, in middle layers during spring and autumn and in deep layers during winter.

There were also seasonal variations in the vertical distribution of sMMPs (Fig. 1B). During spring, sMMPs were present at depths of 3 to 27 cm; during summer, 1 to 18 cm; during autumn, 1 to 21 cm; and during winter, most sMMPs were at depths of 10 to 30 cm (Fig. 1B; Table 1). The maximum abundance of sMMPs was at the upper layers of sediment during spring (134 ind/cm 3 , 5 cm), summer (182 ind/cm 3 , 5 cm) and autumn (125 ind/cm 3 , 3 cm) but at the deep layers during winter (37 ind/cm 3 , 23 cm).

Thus, our data showed wide ranges of vertical distributions of sMMPs and eMMPs, especially the distribution ranges in spring, which spanned 25 cm (3 to 27 cm) and 33 cm (2 to 34 cm) respectively. Furthermore, both eMMPs and sMMPs changed their vertical distributions with seasons. Conversely, unicellular MTB were observed only in less than 10 cm of the surface sediment throughout the year. The wide and variable vertical distribution seems to be unique to MMPs. The vertical distributions of eMMPs and sMMPs were quite different according to present data, which suggested their differences in ecological niches and environmental adaptability.

Identification of eMMP species

We used micromanipulation to sort eMMPs collected from different sediment depths in each season. We identified 30 eMMP individuals and 197 eMMP sequences during spring and 70 individuals and 335 sequences during autumn (Table 2). All the eMMP sequences had 100% sequence identity to Ca. M. rongchenensis. During summer, we identified 15 eMMP individuals at depths of 1-8 cm and obtained 76 eMMP sequences. During winter, we identified 34 eMMP individuals from the deep sediment and 4 eMMP individuals from the top 3-4 cm of the sediment and obtained 262 eMMP sequences. Again, all eMMP sequences had 100% sequence identity to Ca.M . rongchenensis. These results indicated that Ca. M. rongchenensis was the dominant eMMP species at all sediment depths in all four seasons and that there was no seasonal replacement with other eMMP species. Thus, it The sampling site (378 21 0 33.857 00 N, 1228 34 0 41.571 00 E) is on the north side of Lake Yuehu. We sampled 20 times from October 2014 to October 2015 at low tide, when the sampling site was exposed to the air. The sampling frequency was once per month during winter and spring and every 2 weeks during summer and autumn. We made two replicates for MMP observations at each sampling date. The distance between two replicate cores was 10 cm. Samples were sliced at 1 cm intervals to count the MMP abundance. The south poles of two magnetic discs (approximately 300 Gauss) were placed on opposite sides of a sample bottle for 40 min. Then, 2 ml samples near each magnet were removed and transferred into microtubes. A 30 ll mixed water sample from the microtube was examined using the hanging drop method under an Olympus BX51 microscope (Tokyo, Japan) equipped with a differential interference contrast (DIC) system. and the amplified 16S rRNA gene was purified using the TaKaRa MiniBEST Agarose Gel DNA Extraction Kit Ver.4.0 (Japan). After the construction of clone libraries, random clones were sequenced to obtain all possible sequences (>1400 bp) related to the eMMP 16S rRNA gene using the BioEdit Sequence Alignment Editor (version 7.0) and BLAST (http://www.ncbi.nlm.nih. gov/BLAST/) against the nt/nr database. Note that all 16S rRNA gene sequences of eMMPs from different seasons and depths had 100% sequence identity to Candidatus Magnetananas rongchenensis.

was the seasonal migration of Ca. M. rongchenensis that resulted in the changes in vertical distribution.

Studies on the vertical distribution of Candidatus Magnetoglobus multicellularis (sMMP) in sediment samples [START_REF] Sobrinho | Geochemical Characteristics Related to the Gregite-Producing Multicellular Magnetotactic Prokaryote Candidatus Magnetoglobus multicellularisin a Hypersaline Lagoon[END_REF] and in a microcosm experiment [START_REF] Martins | Spatiotemporal distribution of the magnetotactic multicellular prokaryote Candidatus Magnetoglobus multicellularis in a Brazilian hypersaline lagoon and in microcosms[END_REF] indicate that changing environmental conditions cause the sMMP population to migrate vertically through the sediment. Our results for Lake Yuehu indicated that the population of Ca. M. rongchenensis migrated seasonally. Seasonal factors might regulate the vertical migration.

Magnetosomes in eMMPs

A single type of magnetosome was detected in Ca.M . rongchenensis specimens isolated from all sampling depths (Fig. 2A). These magnetosomes were bullet-shaped and composed of iron oxide crystals that commonly consisted solely of magnetite [START_REF] Bazylinski | Magnetotactic bacteria[END_REF]. The genomic magnetosome island (MAI) from the draft genome of Ca. M. rongchenensis contains the magnetite-producing mamAB-cluster and the mad gene cluster [START_REF] Leão | Ultrastructure of ellipsoidal magnetotactic multicellular prokaryotes depicts their complex assemblage and cellular polarity in the context of magnetotaxis[END_REF]. Our observation of magnetite magnetosomes indicated that based on the presence of this MAI, the synthesis of magnetosomes in Ca.M . rongchenensis was under genetic control. In addition, the bullet-shaped magnetosomes from 17 to 22 cm depths of the sediment were not only fewer in number but also smaller in size (Fig. 2B). Furthermore, the magnetosomes there were not well organized into chains (Fig. 2C). These results suggested that the synthesis of magnetite magnetosomes might also be regulated by environmental factors. Transmission electron microscopy (TEM) observations were made using HITACHI HT770 and JEOL JEM-2100 TEMs operating at accelerating voltages of 100 kV and 200 kV respectively. The JEOL JEM2100 was equipped with an X-MaxN TSR silicon drift detector (Oxford Instruments, UK), which enables chemical microanalysis by energy-dispersive X-ray spectroscopy (EDXS) in the TEM mode. The length and width of magnetosomes were measured using ImageJ 1.50b software, and the sizes of magnetosomes were calculated as (length 1 width)/2 [START_REF] Lin | Uncultivated magnetotactic cocci from yuandadu park in beijing, china[END_REF]. A1. The eMMP morphology, with flagella (grey arrow) covering the outer surface, (A2) bullet-shaped magnetosomes and (A3) energydispersive X-ray (EDX) analysis of an individual magnetosome (orange). The white square in (A1) shows the magnified area in (A2). B. Vertical profiles of redox potential (green), eMMP abundance (red), magnetosome size (black) and the number of magnetosomes per cell (orange). C. Magnetosomes of eMMPs from five sections of sediment depths. Note that the magnetosome chains lose organization in the 17-22 cm layer.

In a previous study, greigite magnetosomes were occasionally observed in Ca. M. rongchenensis [START_REF] Chen | A novel species of ellipsoidal multicellular magnetotactic prokaryotes from Lake Yuehu in China[END_REF]. In this study, no greigite magnetosomes were found at all depths of the sediment with redox potentials of 2247 to 253 mV (Fig. 2B). A previous report indicated that the cultured MTB are responsive to external magnetic fields only when the dissolved oxygen concentration (dO 2 ) is below 1% [START_REF] Zhang | Semicontinuous culture of Magnetospirillum gryphiswaldense MSR-1 cells in an autofermentor by nutrientbalanced and isosmotic feeding strategies[END_REF]. In other studies, magnetite MTB start to synthesize magnetosomes only at a low dO 2 level ( 0.45 mg/l at 268C), and high oxygen levels inhibit the formation of magnetite [START_REF] Yang | Effects of growth medium composition, iron sources and atmospheric oxygen concentrations on production of luciferase-bacterial magnetic particle complex by a recombinant Magnetospirillum magneticum AMB-1[END_REF][START_REF] Li | environmental factors affect magnetite magnetosome synthesis in Magnetospirillum magneticum AMB-1: implications for biologically controlled mineralization[END_REF]. Thus, dO 2 serves as a switch for the synthesis of magnetite magnetosomes. The synthesis of greigite magnetosomes in Ca. M. rongchenensis was presumably triggered by a redox potential lower than those reached in this study.

Thus, the migration of eMMPs was orientated only by magnetite magnetosomes at all sediment depths. The occasionally observed greigite magnetosomes in Ca.M . rongchenensis might play another role such as a container of excessive sulfur in low-redox potential environment.

Environmental factors

Temperature. In each sediment column, temperature varied slightly (less than 3.48C) among different depths and became stable in deeper sediment (>5 cm). The average temperature peaked in summer, at 25.48C, and reached its minimum in winter, at 1.28C. The average temperature in spring was slightly lower than that in autumn, 10.28C and 16.88C respectively (Fig. 1C). These results indicated that when the temperature was high (summer), eMMPs and sMMPs occurred within a narrow band in upper layers of sediment. When the temperature was low (winter), eMMPs and sMMPs were present at deeper layers. When the temperature was moderate (spring and autumn), eMMPs and sMMPs were widely present at middle layers (Fig. 1).

A previous study of the temporal distribution of eMMPs and sMMPs based on the upper 10 cm of sediment indicated that eMMPs preferred lower temperatures than sMMPs [START_REF] Du | Temporal distributions and environmental adaptations of two types of multicellular magnetotactic prokaryote in the sediments of Lake Yuehu, China[END_REF]. Considering the entire distribution depths of eMMPs and sMMPs, we calculated the average abundance of MMPs in each sediment column. The average abundance of eMMPs was slightly higher during spring (36 ind/cm 3 ) than during other seasons (30-31 ind/cm 3 , Table 1). The average abundance of sMMPs was slightly higher during summer (38 ind/cm 3 ) than during spring and autumn (31-33 ind/ cm 3 ) but much higher than during winter (19 ind/cm 3 ). Moreover, Student's t-test indicated that sMMPs were significantly more abundant at temperatures above 188C and that eMMPs were significantly more abundant at temperatures below 188C (Fig. 1D).

The average temperature of the sediment columns ranged from 0.1 to 27.18C throughout the year; with the exception of the low average abundance of sMMPs in winter, the average abundances of both sMMPs and eMMPs were relatively uniform throughout the year (Table 1). As the temperature varied slightly (less than 3.48C) at different depths in each sediment column, temperature alone was not the direct cause of the vertical changes in MMP abundance.

Redox potential. Plots of the relationship between the oxidation-reduction potential (ORP) and MMP abundance indicated that the greatest abundance of eMMPs was present at ORPs from 2179 to 237 mV and that the greatest abundance of sMMPs was present at ORPs from 282 to 158 mV (Fig. 3A andB). Thus, eMMPs preferred more reductive environments than sMMPs. The ORP depth profiles for four seasons indicated that MMPs preferred different layers during different seasons (Fig. 3C andD). The preferred layers of eMMPs were a depth of 4-8 cm during summer, 5-14 cm during spring and autumn and 15-20 cm during winter; sMMPs preferred the upper layers during summer (2-5 cm), spring (4-7 cm) and autumn (4-7 cm) but a deeper layer during winter (7-14 cm). These patterns were consistent with the vertical migration of these two types of MMPs, suggesting that vertical migration of MMPs between seasons correlates with the environmental redox potential.

The magnetosomes in MMPs play the same role as those in unicellular magnetotactic bacteria [START_REF] Rodgers | Intercellular Structure in a Many-Celled Magnetotactic Prokaryote[END_REF][START_REF] Zhou | A novel genus of multicellular magnetotactic prokaryotes from the Yellow Sea[END_REF]. They confer on MMPs a net dipolar magnetic moment that allows MMP aligning and swimming along magnetic field lines. This behaviour is termed magnetotaxis. MMPs use magnetotaxis in combination with aerotaxis to seek the optimal redox potential in a vertical gradient in sediments. In a laboratory, when the consumption of oxygen modifies the gradient, the cultivated microaerobic MTB move upward and grow at a position closer to the air-liquid interface from where the oxygen penetrates and diffuses into the culture media (Zhang et al., 2014b). Here, we hypothesize a similar scenario for MMP distribution in the sediment. With seasonal changes, the redox potential values change throughout the sediment, which results in the relocalization of MMPs.

Bazylinski et al. have hypothesized that magnetoaerotaxis helps MMPs to seek electron donors or acceptors dynamically to keep a favourable internal redox state [START_REF] Bazylinski | Magnetotactic bacteria[END_REF]. Cells with internally stored electron acceptors perform excursions from the upper sediment to anoxic deeper zones in order to accumulate reducing substances, that is, electron donors. Eventually, the depletion of electron acceptors and accumulation of electron donors triggers the return of the cells to the upper sediment. For MMPs, the seasonal migration might be accomplished progressively with each magneto-aerotaxis. The long-distance migration depends on the strong swimming ability of the cells. In addition, we hypothesize that the thresholds of optimal redox potential reflect the ability of MMPs in storing electron donors or acceptors.

Inorganic nutrients. There were also changes in the vertical profiles of inorganic nutrients (Fig. 4). In particular, the profiles of NH 1 4 and SiO 22 3 were similar in that their highest concentrations occurred in the deep sediment during summer and early autumn, when the MMPs were most abundant in the shallow layers. This pattern suggested that high concentrations of NH 1 4 and SiO 22 3 might interfere with the vertical migration of MMPs. Additionally, both types of MMPs preferred low concentration of inorganic nutrients (Supporting Information Fig. S1). The eMMPs preferred wider concentration ranges of NH 1 4 , SiO 22 3 and NO 2 2 , while sMMPs preferred wider concentration ranges of NO 2 3 and PO 32 4 .

Principal component analysis (PCA). The first two axes of PCA ordination explained 52.81% of the total variance in MMP abundance (Fig. 5). The first axis was associated with the ORP (26.9%), NH 1 4 concentration (21.8%), temperature (16.6%) and SiO 22 3 concentration (14.9%). In particular, high temperatures were associated with more reductive environments, reflecting the catabolism of organic matter. The high abundance of MMPs was associated with high temperatures and low redox potentials, suggesting the MMPs preferred an environment with active organic catabolism. All five inorganic nutrients were below the zero value on axis 2, whereas the abundance of MMPs was above this value, indicating that both types of MMPs preferred low-inorganic-nutrient environments. The distribution pattern of seasonal samples showed a clear separation into three groups. The environmental conditions during winter were much different from those during other seasons, and the environmental conditions were very similar during summer and autumn.

Conclusion

Taken together, our data indicated the seasonal variations in the vertical distributions of eMMPs and sMMPs. Ca.M . rongchenensis, with magnetite magnetosomes, migrated between different depths. ORP, a measure of the oxidizing and reducing nature of the environment, had a strong relationship with MMP migration. MMPs preferred low concentrations of all five tested inorganic nutrients and migrate away from high concentrations of NH 1 4 and SiO 22

3 . Here, we identified some environmental factors related to the abundance and vertical migration of MMPs. Further genomic studies and studies of the behaviour Pore water was collected each time before the collection of sediment cores. The pore water collection was performed in field using a custommade collector with 30 syringes that could collect 30 layers of pore water at a time (Supporting Information Fig. S2). A SEAL QuAAtro 39-SFA Analyzer (Bran1Luebbe, Germany) was used to analyse the concentrations of inorganic nutrients in the pore water, including those of ammonium (NH 1 4 ), silicate (SiO 22 3 ), nitrate (NO 2 3 ), nitrite (NO 2 2 ) and phosphate (PO 32 4 ). A and B. Red lines (eMMPs) and blue lines (sMMPs) are isolines for 10 ind/cm3 and 50 ind/cm 3 respectively. C-G. Depth profiles of five inorganic nutrients and the upper limit of the preferred nutrient range for eMMPs (red lines) and sMMPs (blue lines). Note that high concentrations of NH 1 4 and SiO 22

and physiology of MMPs will provide important information on the underlying metabolic mechanisms. 4 concentration, NO 2 3 concentration and NO 2 2 concentration. Redox potential is the most important environmental factor and accounts for 26.9% of the seasonal changes in MMP abundance. Note that the five inorganic nutrients and abundance of eMMPs and sMMPs are on opposite sides of axis F2, indicating that MMPs prefer low-nutrient environments. Note also the clear separation into three seasonal groups, indicating that the environmental conditions during winter (blue) are different from those during other seasons and that the environmental conditions during summer (pink) and autumn (purple) are similar.

Fig. 1 .

 1 Fig. 1. Abundance of eMMPs and sMMPs at different sediment depths.The sampling site (378 21 0 33.857 00 N, 1228 34 0 41.571 00 E) is on the north side of Lake Yuehu. We sampled 20 times from October 2014 to October 2015 at low tide, when the sampling site was exposed to the air. The sampling frequency was once per month during winter and spring and every 2 weeks during summer and autumn. We made two replicates for MMP observations at each sampling date. The distance between two replicate cores was 10 cm. Samples were sliced at 1 cm intervals to count the MMP abundance. The south poles of two magnetic discs (approximately 300 Gauss) were placed on opposite sides of a sample bottle for 40 min. Then, 2 ml samples near each magnet were removed and transferred into microtubes. A 30 ll mixed water sample from the microtube was examined using the hanging drop method under an Olympus BX51 microscope (Tokyo, Japan) equipped with a differential interference contrast (DIC) system. A and B. Abundance (left) and representative scanning electron microscopy (SEM) photomicrographs (right) of eMMPs (top) and sMMPs (bottom) at different sediment depths during one year. Black dots indicate the sediment layers of each sample. C. Average abundance of eMMPs (red bars) and sMMPs (blue bars) in each sediment core. The line and error bars indicate the average temperature of the sediment column and standard deviations.D. Student's t-test (significance level: p < 0.05) was used to compare the average abundances of eMMPs and sMMPs at different temperatures using SPSS version 12.0. This test indicated that the overall average abundance of eMMPs was low when the temperature was above 188C but high when the temperature was below 188C( p < 0.05 for both comparisons).

  Fig. 1. Abundance of eMMPs and sMMPs at different sediment depths.The sampling site (378 21 0 33.857 00 N, 1228 34 0 41.571 00 E) is on the north side of Lake Yuehu. We sampled 20 times from October 2014 to October 2015 at low tide, when the sampling site was exposed to the air. The sampling frequency was once per month during winter and spring and every 2 weeks during summer and autumn. We made two replicates for MMP observations at each sampling date. The distance between two replicate cores was 10 cm. Samples were sliced at 1 cm intervals to count the MMP abundance. The south poles of two magnetic discs (approximately 300 Gauss) were placed on opposite sides of a sample bottle for 40 min. Then, 2 ml samples near each magnet were removed and transferred into microtubes. A 30 ll mixed water sample from the microtube was examined using the hanging drop method under an Olympus BX51 microscope (Tokyo, Japan) equipped with a differential interference contrast (DIC) system. A and B. Abundance (left) and representative scanning electron microscopy (SEM) photomicrographs (right) of eMMPs (top) and sMMPs (bottom) at different sediment depths during one year. Black dots indicate the sediment layers of each sample. C. Average abundance of eMMPs (red bars) and sMMPs (blue bars) in each sediment core. The line and error bars indicate the average temperature of the sediment column and standard deviations.D. Student's t-test (significance level: p < 0.05) was used to compare the average abundances of eMMPs and sMMPs at different temperatures using SPSS version 12.0. This test indicated that the overall average abundance of eMMPs was low when the temperature was above 188C but high when the temperature was below 188C( p < 0.05 for both comparisons).

  of eMMPs obtained by micromanipulation; cloning: number of sequenced clones; eMMP sequences: number of eMMP sequences; BLAST: Basic Local Alignment Search Tool results with the highest sequence identity; C. M. R.: Candidatus Magnetananas rongchenensis.Magnetic micromanipulation was used to sort eMMPs from magnetically enriched samples of each sediment layer. A TransferMan ONM-2D micromanipulator and an IM-9B CellTram Oil manual hydraulic pressure-control system were installed on an Olympus IX51 microscope for micromanipulation. We sorted as many eMMPs as possible and then washed them at least five times by aspiration and transference from one filter-sterilized seawater container to another to assure purity. Washed cells were directly transferred into 4 ll of PBS for whole-genome amplification (WGA) using the REPLI-gV R Single Cell Kit (QIAGEN, Germany). The amplified genomic DNA was diluted and used as a template for the amplification of the 16S rRNA gene. The bacteriumspecific primers 27F and 1492R (Sangon Biotech, Shanghai, China) and 2 3 Taq PCR MasterMix (TIANGEN, China) were used for PCR. The PCR products were resolved on agarose gels,

Fig. 2 .

 2 Fig. 2. Magnetosomes of eMMPs from different sediment depths.Transmission electron microscopy (TEM) observations were made using HITACHI HT770 and JEOL JEM-2100 TEMs operating at accelerating voltages of 100 kV and 200 kV respectively. The JEOL JEM2100 was equipped with an X-MaxN TSR silicon drift detector (Oxford Instruments, UK), which enables chemical microanalysis by energy-dispersive X-ray spectroscopy (EDXS) in the TEM mode. The length and width of magnetosomes were measured using ImageJ 1.50b software, and the sizes of magnetosomes were calculated as (length 1 width)/2[START_REF] Lin | Uncultivated magnetotactic cocci from yuandadu park in beijing, china[END_REF]. A1. The eMMP morphology, with flagella (grey arrow) covering the outer surface, (A2) bullet-shaped magnetosomes and (A3) energydispersive X-ray (EDX) analysis of an individual magnetosome (orange). The white square in (A1) shows the magnified area in (A2). B. Vertical profiles of redox potential (green), eMMP abundance (red), magnetosome size (black) and the number of magnetosomes per cell (orange). C. Magnetosomes of eMMPs from five sections of sediment depths. Note that the magnetosome chains lose organization in the 17-22 cm layer.

Fig. 3 .

 3 Fig.3. Redox potential and its relationship with the abundances of eMMPs and sMMPs. The ORP was measured in situ with three replicates at each sampling before the collection of sediment cores using a portable pH meter with a platinum electrode (length: 23 cm) as the working electrode and a Hg/Hg 2 Cl 2 electrode (length: 21 cm) as the reference electrode. The standard potential of the reference electrode (U8) at the measured temperature was added to the measured voltage (U) to obtain the corrected redox voltage (U H ): U H 5 U 1 U8 A and B. The eMMP abundance is greatest at redox potentials between 2179 and 237 mV (left), and sMMP abundance is greatest at redox potentials between 282 mV and 158 mV (right). C and D. Depth profiles of redox potential during four different seasons. The redox potentials preferred by eMMPs (left) and sMMPs (right) occur in different layers in different seasons.

Fig. 4 .

 4 Fig.4. MMP abundances and inorganic nutrient concentration at different sediment depths from April to December 2015. Pore water was collected each time before the collection of sediment cores. The pore water collection was performed in field using a custommade collector with 30 syringes that could collect 30 layers of pore water at a time (Supporting Information Fig.S2). A SEAL QuAAtro 39-SFA Analyzer (Bran1Luebbe, Germany) was used to analyse the concentrations of inorganic nutrients in the pore water, including those of ammonium (NH 1 4 ), silicate (SiO 22 3 ), nitrate (NO 2 3 ), nitrite (NO 2 2 ) and phosphate (PO 32 4 ). A and B. Red lines (eMMPs) and blue lines (sMMPs) are isolines for 10 ind/cm 3 and 50 ind/cm 3 respectively. C-G. Depth profiles of five inorganic nutrients and the upper limit of the preferred nutrient range for eMMPs (red lines) and sMMPs (blue lines). Note that high concentrations of NH 1 4 and SiO 22 3 occur at greater depths during summer and early autumn, when MMP abundance is generally lower.

Fig. 5 .

 5 Fig. 5. Principal component analysis of MMP abundance and environmental factors.Principal component analysis (PCA) using Pearson's matrix and principal components (PC) axis scores was used using XLSTAT-Pro 19. The first two principal components (PCs) (F1 and F2) account for 52.81% of the total variance. The first axis (F1) is associated with redox potential, NH 1 4 concentration, temperature and SiO 22 3 concentration, and the second axis (F2) is associated with eMMP abundance, sMMP abundance, PO 32 4 concentration, NO 2 3 concentration and NO 2 2 concentration. Redox potential is the most important environmental factor and accounts for 26.9% of the seasonal changes in MMP abundance. Note that the five inorganic nutrients and abundance of eMMPs and sMMPs are on opposite sides of axis F2, indicating that MMPs prefer low-nutrient environments. Note also the clear separation into three seasonal groups, indicating that the environmental conditions during winter (blue) are different from those during other seasons and that the environmental conditions during summer (pink) and autumn (purple) are similar.

Table 1 .

 1 Abundance of eMMPs and sMMPs during the four seasons

	eMMPs

DD: distribution depth; MA: maximum abundance; LMA: layer with maximum abundance; AA: average abundance.

Table 2 .

 2 Dominant species of eMMPs at different sediment depths during the four seasons

	Winter
	Autumn	eMMP	sequences BLAST Identity Individuals Cloning
	Summer	eMMP	sequences BLAST Identity Individuals Cloning
	Spring	eMMP	sequences BLAST Identity Individuals Cloning
			Depth Individuals Cloning

occur at greater depths during summer and early autumn, when MMP abundance is generally lower.

Acknowledgements

This study was supported by the National Natural Science Foundation of China (NSFC, Grant Nos. 41330962, U1706208, 41776130 and 41776131). We thank X. Zheng for collecting the sediment samples. The TEM analyses were performed at KLEMB, IOCAS, with the assistance of W. Liu. We thank Dr. J. Sun (Tianjin University of Science and Technology) for conducting the inorganic nutrient analyses.

Supporting Information

Additional Supporting Information may be found in the online version of this article at the publisher's web-site:


Camille Gras
email: camille.gras@grenoble-inp.fr

Van-Dat Cung
email: van-dat.cung@grenoble-inp.fr

Nathalie Herr
email: nathalie.herr@probayes.com

Alantha Newman
email: alantha.newman@grenoble-inp.fr

Nicolas Teypaz
email: nicolas.teypaz@probayes.com

Long-haul Parcel Transportation on a Hierarchical Network

Introduction

E-commerce has experienced strong growth over the past two decades. This trend has been further reinforced by the recent pandemic, pushing people to shop even more online. Designing good logistics and transportation networks to handle point-to-point parcel delivery is key to the success of e-commerce. In this work, we focus mainly on the optimization of long-haul parcel transportation on a road network. We consider a two-level hierarchical transportation network containing three types of sites, where parcels pass through and/or are sorted. We want to determine how to exploit such hierarchical structure when designing an algorithm for long-haul parcel transportation. On the one hand, the simplicity of the network structure is useful because it allows to reduce the number of operational paths in the network. On the other hand, introducing this structure would possibly limit some paths resulting suboptimal routings. Thus, our research goal is to understand and find a good trade-off between the simplicity of hierarchical network design and the optimality of the solutions produced by our algorithms.

Definition of the long-haul parcel transportation problem

We study the problem of delivering parcels via trucks with twin trailers in a national postal network with around 2000 demands per day between sites on the network. We have two types of sites : each site in our network is either a delivery depot or a sorting center (but cannot be both). We have around 15 sorting centers and 150 delivery depots. Among the sorting centers, some are also inner-hubs (intermediate sites between sorting centers) as determined by the transport managers. So the parcels are to be routed on a road network essentially composed of two hierarchically nested hybrid hub-and-spoke networks. The inner layer consists of sorting centers, some of which are designated as inner-hubs. In the outer network, each sorting center serves as an outer-hub for the corresponding delivery depots that are assigned to this sorting center. For both networks, it is possible to bypass the inner-or outer-hubs, which is why the networks are considered to be hybrid [START_REF] Zäpfel | Planning and optimization of hub-and-spoke transportation networks of cooperative third-party logistics providers[END_REF].

Parcels are physical objects which must be routed from a specified origin sorting center to a designated delivery depot. We assume all the parcels have the same size which is an average size. The parcels which have the same origin and destination are grouped in a demand. Demands are represented by the triple (origin, destination, number of parcels). At a sorting center, all parcels in a container can be sorted. By sorting, we mean assigning parcels to containers and assigning containers to trucks. This operation has a cost. Between the origin and the destination sites, a parcel can be reassigned (container and/or truck) at at most two intermediate sites. All pairs of sites are connected and there is a cost for routing a truck between two sites. Our objective is to find paths for trucks in the network provided so that each parcel is delivered while minimizing † Institute of Engineering Univ. Grenoble Alpes the total transportation and sorting costs and respecting the aforementioned reassignment constraints. Moreover, we have to balance the trucks, which means that the number of outgoing and incoming trucks must be equal for each site in the course of a day. Note that as a container can carry parcels with different origins and destinations, an optimal solution might not route a parcel on its shortest path. When a set of demands going to different final sites are put in the same container, it is called consolidation. It allows cost savings as it permits a more parsimonious utilization of trucks, but it makes the problem more computationally difficult.

Hybrid hub-and-spoke networks have been used previously to simplify such networks and reduce the solution space. For example, Zäpfel and Wasner [START_REF] Zäpfel | Planning and optimization of hub-and-spoke transportation networks of cooperative third-party logistics providers[END_REF] study the planning and optimization of hybrid hub-and-spoke transportation on the case of parcel delivery in Austria, and they demonstrate that a hybrid hub-and-spoke network (with the addition of direct paths between origin and destination points) is optimal in their case. Baumung and Gündüz [START_REF] Baumung | Consolidation of residual volumes in a parcel service provider's long-haul transportation network[END_REF] also used this type of network to consolidate residual volumes on the case of parcel delivery in Germany. In our case study, the number of potential paths is too large to be addressed directly by an MILP, so we need to reduce the size of the problem. In a previous work [START_REF] Gras | Point-to-point parcel delivery via clustering[END_REF], we tested clustering methods to address this issue. Here, we use the hierarchical structure of the network and the aggregation of demands to reduce the problem size and simplify the solution space.

Algorithm for parcel routing via aggregate demands

As the number of possible sorting operations for each parcel is bounded, we set up a pathbased MILP. However, this MILP does not yield optimal solutions for a complete data instance in a reasonable amount of time. But it can give optimal solutions for smaller instances (less than 40 sites) in less than 10 minutes. This leads us to consider dividing the original problem into tractable subproblems, guided by the hierarchical nature of the network.

The main idea of this algorithm is to first optimize the transportation on the inner level of the network (sorting centers to sorting centers), then to optimize the extension of this transport plan to the outer level of the network (sorting centers to depots), and finally to optimize on a global level the whole transport plan. Since the original demands of our problem are from sorting centers to delivery depots, we first create aggregate demands which are demands from sorting centers to sorting centers, in order to create a tractable problem for the first level of the network. An aggregate demand is the sum of demands from a sorting center to all the corresponding delivery depots of a same destination sorting center (which is their outer-hub).

If we simply aggregate all the demands into demands from a sorting center to another sorting center and force all parcels to be sorted in their corresponding outer-hub, we will not use any direct paths from a sorting center to a depot. Thus, we split the demands into two sets : the large demands (above a given threshold) which will be separated and allowed to go on a direct path with lower costs, and the residual demands which will be sorted in their sorting center (and maybe also at an inner-hub). This approach gives a solution for the complete instance in reasonable time but it is globally suboptimal because it can remove some possible operational paths that would be chosen in a global optimal solution. We will present experimental results obtained on datasets provided by a postal company and a comparative analysis will be done with those obtained with a global MILP to show the effectiveness of our algorithm with aggregate demands.


Adil Hilmani
email: adilhilmani@gmail.com

Youssef Lasfar
email: lassfaryoussef@gmail.com

Abderrahim Maizate
email: maizate@hotmail.com

Abdelouahed Zakari
email: abdelouahed.zakari@univ-lorraine.fr

SysML Extension by AADL Specification for WSN Modeling

Keywords: Modeling Process, WSN, Performance evaluation, SysML, AADL

In the area of software engineering and system architecture, the design and implementation process has taken a general methodological approach, encompassing all the activities necessary to design, evolve and verify a system providing an economical and efficient solution to needs of a client while satisfying all the stakeholders. For a long time, system engineers have used modeling techniques, the best known of which are AADL (Analysis and Architecture Design Language) and SysML (System Modeling Language). AADL was born as a language specific to the field focused on avionics and later was revised to represent and support a more general category of embedded systems in real time. SysML is an extension of the Unified Modeling Language (UML) to support engineering and modeling of the system. Based on these two languages and these two tools, several approaches have been created and developed to meet the needs and requirements of the system and also to overcome the problems and limitations of these two languages. In this paper, we will study and examine the two AADL and SysML modeling languages in a thorough way in order to extend the SysML language by the AADL language specifications for the modeling and design of sensor networks without (WSN).

Introduction

In recent years, wireless sensor networks (WSNs) have performed enormously in various fields including medicine, military and environmental domains [START_REF] Kalantary | A survey on architectures, protocols, applications, and management in wireless sensor networks[END_REF][START_REF] Lan | akyildiz and mehmet can vuran "wireless sensor networks[END_REF][START_REF] Akyildiz | A survey on sensor networks[END_REF]. This sensor network is an ad hoc network made up of different sensor nodes which are electronic components whose role is to capture and measure specific parameters in a monitoring space called a capture field.

These sensor nodes are small nodes that use limited energy resources and low communication and processing power to collect information in a given geographic area and transfer them to the well node (called Sink). These limits are very important in the study, analysis and deployment of a network of wireless sensors to ensure network longevity and also to guarantee better performance and reliability in receiving data collected in a practical way and effective [START_REF] Hilmani | A Study of Self-Organization protocols in Wireless sensor Network[END_REF]. These sensor networks have another problem that must be taken into consideration and which is to model the behavioral and non-behavioral part of the latter in order to carry out the design and the deployment using the most modeling languages used to implement their functioning and behavior.

Model-based engineering (MBE) has emerged as a key set of technologies for designing complex systems. This technology has seen in recent times a tremendous progress in the realm of development and modeling of real-time systems among them wireless sensor networks (WSN). This modeling of systems is generally relying on the use of one of the two most distinguished and most used languages currently: AADL and SysML.

AADL [START_REF] Behjati | An AADL-Based SysML Profile for Architecture level Systems Engineering: Approach, Metamodels, and Experiments[END_REF] defines several categories of components, divided into three main families of components:

• The software components describe the application elements of the architecture.

• The hardware components define the elements of the execution platform.

• The hybrid components, described through the System component, are used to structure the application architecture (in blocks).

In addition, AADL supports the prediction and early analysis of critical system qualities, such as performance, planning and reliability.

SysML [START_REF]SysML[END_REF][START_REF] Belloir | Utilisation de SysML pour la mod´elisation des r´eseaux de capteurs sans fil, Conf´erence sur les Langages et Mod`eles `a Objets (LMO)[END_REF] is a modeling language with a graphic syntax developed and standardized by Object Management Group (OMG). It has been designed to, inter alia, capture software interactions with physical entities, and is widely used in systems engineering. Compared to UML 2, SysML adds support for systems engineering (for example, by requirements engineering and quantitative analysis of the physical aspects of the system), while removing many UML software centric constructs.

The main objective of this paper is to propose a profile-specific modeling for wireless sensor networks (WSN) based on the use of a new design technique which is based on an extension of the SysML language by adding the critical specifications of the AADL language in order to carry out and implement the modeling of wireless sensor networks.

The rest of the document is organized as follows. Section. 2 provides an overview of WSN modeling methods. In Section 3, we will explain the requirements of the SysML profiles for the modeling of WSN. Then, in Section 4 we will give a new contribution based on a proposed SysML profile. Finally, we conclude with a conclusion and a perspective in Section 5.

WSN Modeling Languages

In this section, we will study and examine the different modeling languages that are the most distinguished and used today in the design and implementation of complex and real-time systems. Among these languages are UML, MARTE, BIP, SysML, AADL.

Current Modeling Languages

UML [START_REF] Booch | The unified modeling language[END_REF] (Unified Modeling Language) is a unified modeling language and Object Oriented by the OMG which is based on the use of graphs and diagrams to visualize, specify, build and document systems covering different areas of application between them the software systems, based on all standardized and object-oriented methods. UML offers thirteen diagrams that are used for the description and design of a system. These diagrams are divided into two categories of diagrams which are:

• Structural diagrams: These diagrams play a crucial role in the description of the body part of the system based on the identification of objects with their behaviors and their operations, not forgetting the operations and methods attributed to them. • Behavior diagrams: These diagrams describe the dynamic part of a system that is based on the output of the results to the user once the system interacts with external events.

MARTE [START_REF] Nice | Le temps dans le profil UML MARTE, 2007wwwi3s.unice.fr[END_REF][START_REF]OMG: UML profile for Modeling and Analysis of Real-Time and Embedded systems (MARTE)[END_REF] (Modeling and Analysis of Real Time and Embedded Systems) is designed to take over from its predecessor called profile for Scheduling, Performance and Time Specification (SPT), it is a recent OMG UML profile consisting of a platform and a which describes the real-time parameters and aspects of systems in UML models. This language also relies on the modeling of systems. Considering the static part, defining the components, functions and methods, and the dynamic part describing the interaction of the system with its entourage and its environment, producing real-time results. The main objective of MARTE is to create and propose a common and unique modeling language to describe and specify at the same time the software and hardware aspects of embedded systems in real time. This language consists of three major models:

• Application model: Defines aspects and functionalities of the system.

• The Resource Model: describes the implementation and execution infrastructure of the behavioral part of the system based on non-functional properties and parameters • Allocation model: describes the interaction between applications and resources. BIP [START_REF] Chkouri | Modélisation des systèmes temps-réel embarqués en utilisant AADL pour la génération automatique d'applications formellement vérifiées[END_REF] (Behavior, Interaction, Priority) is a language with a theoretical basis for the construction and analysis of embedded systems in real time from heterogeneous components. This language allows the implementation and behavioral description of real-time embedded architectures. The BIP models are obtained by the association and integration of three modeling parts:

• The lower part defines the behavioral aspect of a component or object as a set of transitions (that is, an extended state machine with data); • The intermediate part describes the connection with the behavior part using the connectors which provide a description of the interaction between these two parts. • The upper part consists of a group of properties and priority features used to describe the laws and rules of operation and planning of interactions.

Modeling using the BIP language is based on the use of connectors and priorities to develop and build a hierarchical architecture of composite components from atomic components. This modeling has created an open and clear vision that has made it possible to design the behavior and operation of components and the overall structure of a system.

Presentation of The SysML Language

SysML [12-14] is a modeling language developed by OMG, INCOSE and AP233 and is oriented to the field of system engineering which is based on the graph to specify, analyse, describe, verify and validate the feasibility of a system before its realization. SysML has been designed to use and rely on an open source license to develop its contribution and use. SysML is defined as an extension of a subset of UML using the profile mechanism defined by UML.

The SysML language is a way to form and consolidate in a single, common model all feature components, properties, constraints, and parameters to model and design the entire system. To carry out this modeling, the SysML language is based on diagrams that make it easier to approach complex systems and also to implement their operations and their realizations.

With modeling using the SysML language, a system can be modeled and also can be designed in several manners and in different ways in order to formalize the overall behavior of the system. This freedom of modeling can create problems when implementing the realization of the operation of this system. This language does not allow the realization and the execution of the behavior of the system which limits its performance.

Presentation of The AADL Language

AADL (Architecture Analysis and Design Language) [START_REF] Ph Feiler | The SAE Architecture Analysis & Design Language (AADL) a standard for engineering performance critical systems, Computer Aided Control System Design[END_REF][START_REF] Hugues | Développement de systèmes à l'aide d'AADL -Ocarina/Cheddar[END_REF] is an SAE international standard established in 2004 that produces a new project to analyse system designs prior to development and that supports the system architecture description for embedded systems.

The objective of the AADL language is to perform an efficient and precise modeling that includes all functional and non-functional parts of the system without forgetting all these properties and these functions such as complexity, schedulability, message transmission, hardware description (processor, memory, bus, etc.). To carry out this modeling, each component of the system is described in AADL according to two aspects. The first, type, corresponds to the functional interface of the component. The second, the implementation, describes the content of the component (subcomponents, time properties, connections, etc.). Each component belongs to one of the 10 categories predefined in AADL, classified into 3 families: hardware (Execution Platform), software (Application Software) and hybrid (Composite).

To model an architecture, the AADL components must be declared as subcomponents (instances) of other AADL components. At the highest level, a system component contains all instances of other components. Most AADL components can contain subcomponents that allow a hierarchical description of the system.

SysML Profiles Requirements for WSN Modeling

This paper proposes a new process of modeling wireless sensor networks that is based on the combination of two languages SYSML and AADL precisely on the notion of profile in UML/SYSM, this notion which allows specializing a part of the AADL language by SYSML in order to produce a profile that will provide a complete modeling support for WSN designers.

The SysML-AADL Profil

The initial experiments with the SYSML and AADL modeling languages have revealed difficulties in handling these tools. Certainly, the syntax of these languages is very wealth, but the semantics and methodology to be adopted remain dependent on the application field and the context of use. Hence the idea of specializing and customizing a profile dedicated to sensor networks based on the complementarity of these two languages and the possibility offered by extensions with SYSML profile (which is also a UML profile). The ultimate goal is to create a specific profile for wireless sensor networks by integrating new features based on feedback from these two languages.

SysML-AADL Profile requirements for WSN

Generally modeling is a very important operation when it is poorly mastered it can engender a model that does not exactly represent the system and which, in some cases, can cause defects in the behavior or execution of the system which in turn leads to a renunciation of the solution.

In our case, we proposed a new profile of modeling and analyzing SYSML-AADL that will be served as a support for the designers and developers of the WSN. Indeed, a WSN is based on four components: • Nodes containing sensors.

• A wireless interconnection networks.

• A base station for grouping information and acting as an interface between the nodes and the user. • Processing resources at the base station level to manage data correlation.

The SYSML-AADL profile must consider all the requirements related to these components (lifetime, scheduling, communication, etc.) in order to produce a complete solution which allows building a complete support for the modeling of the WSN. In this part, we will describe all these requirements which are divided into four categories:

• Requirements related to the structure of WSN.

• Requirements related to the behavior of WSN.

• Requirements related to energy constraints. • Specific requirements.

Requirements related to the structure of WSN

A wireless sensor network consists of a group of small wireless node networks; each node group is connected to a gateway. The gateways send the collected data to a base station via a transmission network.

In order to model this structure, our profile must support the following requirements: • REQU STRUCT-1: The modeling of the sensor nodes and their characteristics (commercial name, operating systems supported ...) as well as the internal components that ensure the communication and the data processing (ex: transducer, processor). • REQU STRUCT-2: The modeling of communication links between two devices (between two sensor nodes for example) and their characteristics (error rate ....) • REQU STRUCT-3: The modeling of sensors, gateways and base stations and their characteristics. • REQU STRUCT-4: The modeling of the transmission network specification.

Requirements related to the behavior of WSN

In addition to collecting and transmitting data a wireless sensor network can also perform other tasks, such as changing behavior in the event of a failure.

• REQU BEHAVIOR-1: Modeling the process of data collection.

• REQU BEHAVIOR-2: The modeling of the maintenance process (periodic sending of messages to indicate the state of health of a sensor node). • REQU BEHAVIOR-3: Modeling the configuration process and auto-reconfiguration

Requirements related to the energy constraints

Energy conservation is an important issue for WSN as the nodes contain a limited amount of energy, which cannot usually be renewed. REQU ENERG-1: our profile must define the modeling entities for the specification of the energy properties of the different elements of the model.

Requirements related to the specific constraints

The scope of use of the WSN is very wide, which generates a specific constraint related either to the environment of use or to the mechanism of configuration of the network.

However, our SYSML-AADL profile must be scalable and extensible to support any possible constraints.

4

Contribution: Proposal of a SysML Profile

Why a Specific Profile definition?

As we saw in the previous section, SysML is an ideal language to serve the systems modeling as the WSNs without forgetting the AADL. We now have to make the link between these two languages. We set ourselves the objective of demonstrating the interest of such a combination by first developing a SysML profile for AADL. As we know the ideal would be to develop a DSL (Domain Specific Language), completely dedicated to the WSNs. This objective will interest us in a second time and we chose at first to start pragmatically by defining a SYSML profile, The SysML profile will solve a number of AADL language limitations: • It will provide a development environment and graphic support for the expression of the constraints of the WSNs. • It will provide SysML tools that are now starting to be used in industrial settings. • It will make it possible to check the consistency of the operators defined by their implementation in OCL constraints.

• It will make the transition between the expression of needs and the analysis in an efficient way and with a minimum of information loss (seamless). The Expected progress of the project and the expected results: The development of this profile is not the mean goal. It is part of a thesis aiming at the elaboration of a set (WSNs modeling and code generation as long as testing) of software tools for the modeling of the WSNs.

The need for the development of a SysML profile supporting the expression and taking into account AADL elements. The idea is to make (starting with UML) the taxonomy of the types of association. First intra-model (relations, compositions, etc. in a class diagram for example), then inter-model (as dependencies), with in this case the mono levels of meta-modeling (M1) or multi-levels (M1 / M2, for example the type conforms to).

Mapping Component Type and Component Implementation

In AADL, component types and component implementations describe the component, respectively, the visible interfaces and the internal structure. In our case, we will use the blocks for the modeling of the component's types and the components implementations of AADL. To differentiate between these last two, we will use two new stereotypes, "ComponentType" and "ComponentImpl", two SysML extensions. The SysML blocks are extensions of the UML classes, they are chosen for the modeling of the components to describe the two structural and behavioral parts of the system, by adding only the block modeling, this will allow the use of other SysML constructs (ports and parts) for consistent modeling of AADL parts (subcomponents and ports).

AADL provides ten components of different categories. For each identifier in the AADL category, we reserve a stereotype with attributes representing the properties of the chosen category. The values associated with the AADL properties are automatically projected as values of the attributes of the stereotypes applied to the blocks. All category identifiers are generalized by "ComponentType" and "ComponentImpl". We apply two stereotypes for each block: a stereotype specifies whether it is ("Compo-nentType") or it is ("ComponentImpl"), and the other will specified its component categories.

In AADL, the "ComponantImpl" can refine the specification of the "Compo-nantType" by adding implementation details. For example, specifying the subcomponents, connections, modes, properties and the flow.

A realization relationship in the AADL enables all the values of the "Compo-nantType" properties to be transferred to "ComponantImpl", and gives accessibility to all aspects and specifications of the "ComponantType" flows, from the "Componan-tImpl".

For our Model in UML / SysML, this is done by "AADL_Realization", each relation of realization in our model must be stereotyped by "AADL_Realization".

Application and Evaluation of the Profile

In this section, we conducted a case study based on wireless sensor network modeling using the profile proposed in the previous section. In this true study, we will evaluate the capability of this profile to meet the modeling requirements of a wireless sensor network system (WSN) consisting of two sensor nodes, a Head cluster node and a base station using AADL/OSATE.

To start the study, first you need to create a "ComponentType" system type that allows to gather all the different components needed to structure the architecture of the sensor network. In our case, we will create two nodes, a CH, and a BS. For example, specifying the subcomponents, connections, modes, devices, properties and the flow. To accomplish this task, it is necessary to model the implementation part "Componen-tImpl" of this "ComponentType" in order to refine and define its internal structure in terms of interactions between the different subcomponents (see Fig. 1).

Fig. 1. Iimplementation of the proposed system WSN

After modeling the internal architecture of the system, it is important to define the functions and processes to be executed for each component of the system. To achieve this part, you need to create a new "ComponentType" type process that defines the function to perform for each component using "ComponentImpl" to refine the behavior of the component with more detail and accuracy. In our case, it is necessary to determine the tasks that will be executed by the 2 nodes, the CH and the base station without forgetting to define the technique of access control to the wireless communication medium which will allow to transmit several flows of traffic on a single channel in real time (using TDMA).

Once the processes to be performed by the WSN system have been completed, the tasks to be performed for each network component are obtained. As shown in the following Figures: According to the study carried out, we can conclude that the developed model based on the extension of SysML using the AADL specifications has gathered all the features and details to model the WSN wireless sensor network system. As expected, many aspects of the SysML model required the use of AADL features because SysML proved to be insufficient and powerless.

Conclusion and Perspectives

The works presented in this article are "in progress". Our study of the state of the art makes it possible to show the pluridisciplinary and applied nature of the research that can be done within a framework of the modeling of the WSNs. The concrete development of an experimental platform will demonstrate the interest of the approach described and raise other questions both practical and theoretical on the development of hardware / software-based engineering models.

  Implementation of CH processes, b) implementation of BS processes