Eurovis

/ T Höllt

W Aigner

M Agus

L Liu

R Vuillemot

GROUPSET: A Set-Based Technique to Explore Time-Varying Data

Keywords:

We introduce GroupSet, a technique to facilitate the exploration of temporal charts using a set-based approach. GroupSet operates in a twofold way: first it classifies temporal data into categories (sets) for each time point, second it enables to explore such membership to categories (sets) over time. This approach enables to reveal temporal similarities of elements by categories (sets) memberships, usually hidden by overplot. We demonstrate the applicability of the technique to two case studies (traffic data and sport data) and report on usability feedback of an interactive prototype implementing the technique. Our code and datasets are published as an open-source project and we expect further research towards efficient set creation and temporal manipulation, which remain under-explored areas in the domain of set visualization and interaction.

Introduction

Making sense of time-varying data is frequent in many domains, as data are continuously recorded and analyzed. For instance, road operators monitor the traffic density of road segments every day in cities. In soccer field, analysts check teams' ranking weekly to understand their performance during a season. For those domains, a temporal chart-such as a line chart-usually is the goto representation as few assumptions can be made on the data attributes, volume and their distribution. However, such a chart usually generates overplot and hides patterns as datasets get increasingly large.

We introduce GROUPSET, a visualization technique to explore changes within large temporal datasets using line charts. The technique relies on set-based tasks [AMA * 14] to understand the relationships between lines, using partial memberships and changerelated metrics. GROUPSET workflow is summarized and operates as follows: 1) users manually categorize temporal elements (lines) based on their value at each time point, 2) the aggregation of elements generates set intersections listed by partial sets membership, and 3) the details of each set intersection are provided with partial membership distributions and other attributes (e. g., change, cardinality). Our contributions are as follows:

• a partial membership visualization (using pie charts) to make sense of temporal elements grouped by similarities; • an interactive visualization technique, called GROUPSET, implementing the partial memberships visualizations and interactions; • two case studies demonstrating the applicability of the technique and preliminary usability feedback.

Related Work

Our work primarily relates to large time-based values exploration, where an independent variable (time) is plotted along with a dependant value (quantity). Such a research area has already been widely investigated [START_REF] Aigner | Visualization of Time-Oriented Data[END_REF]. Many line chart variations have been proposed such as slop charts [START_REF] Tufte | THE VISUAL DISPLAY OF QUANTI-TATIVE INFORMATION[END_REF] or temporal glyphs [FFM * 13] to plot a handful of elements at once.

The GROUPSET Technique

The core of the GROUPSET technique is a partial membership metric that captures temporal changes. Such changes are represented using pie charts where the black wedge encodes the % of membership (that we define it with set membership degree) to a category (that we now call set) which is one of the value intervals of the dependant quantity domain. If a temporal element is constant over time, and its value interval is divided into three categories, its membership is the following: Step 1: Sets are manually created by defining intervals over the Y-axis of the line chart (Fig. 1,x). By default, 3 sets are included, but users can add or remove sets, customize their value intervals, and name them. The interval customization uses direct manipulation of the Y-axis, so the intervals are not necessarily uniform.

Step 2: Aggregation exploration is achieved using the set permutation matrix and aggregate all elements in a similar way to the Step 3: Element exploration is enabled as a filtered line chart for each row (Fig. 2,z). It provides a less cluttered representation of an individual inspection of trends. Brushing the global line chart (Fig. 2,x) selects time range for the intersections visualizations, which helps analysts focus on specific time intervals. Fol- lowing with element view, it is the distribution view of other elements/groups attributes.

Prototype and Illustrative Case Studies

We now present 2 scenarios to illustrate the technique using representative tasks and datasets and the implementation of GROUPSET as web application https://llqsee.github. io/groupset/ using JavaScript and D3.js.

Traffic Density Analysis

With the development of a variety of sensors to collect the data in cities, traffic operators are able to efficiently monitor roads [CGW15] and eventually detect anomalies or unexpected traffic variations on an hourly basis. We loaded a traffic dataset from a public open data repository in Lyon, FR, for a single day of observation (Fig. 3). The datasets include 1334 road segments during a day (24h), monitored by sensors using inductive loops. The X-Axis represents 24 hours and the Y-Axis represents the traffic densities collected by the sensors. Generally, the traffic densities are low from 0:00 AM to 6:00 AM, and then start rising and reaching the morning peak around 8:00 AM. After the afternoon, it descends again to a lower traffic density. As [CGW15] mentioned, one of the challenges in visualizing the traffic data is that it has too many data items to track. A general line chart cannot handle too many road segments without overplot. Thus, for the traffic dataset, we aim at achieving the followings:

Detecting roads with low traffic. Finding the roads that are not busy (free flow) is critical work to help traffic planners optimize traffic load. These traffic flows can be re-planned from the roads where the traffic congestion always happens. Thus, assisting traffic operators find the roads that are always not busy (during 24h) is able to improve the traffic conditions. As shown in Fig. 3, we focus on the entire period (24h) and create two sets (Non-free flow and Free flow) (T1), with a low density threshold to identify the free flows. By using the filter panel, we keep only the Free flow roads which are characterized with a membership to this set only (T3). The result is shown in Fig. 3, and two groups exist (as we aggregated by change pattern): one contains 64 road segments and another one contains 50 road segments (T2). These road segments mostly have less traffic flow. Further investigations will be needed for their relevance to bear more traffic. Analyzing the traffic flow patterns with a specific time interval. Managing the traffic during peak time is very important for a traffic manager, usually during rush hours around 8:00 AM and 6:00 PM. To analyze this peak pattern of traffic density, we first brush the time interval to the period which we are interested in (7:00 AM to 9:00 AM) (T6). We then add Busy as shown in Fig. 4 to capture the busiest roads at peak time (T1). We observe there is an aggregated group (containing 5 subgroups) only belonging to Busy (T4). A first insight is that the largest group has roads with a clear increase and decrease change pattern (green and red bars), which means these roads are not stable being either rising up or falling down. A second insight is that a certain number of roads peak in the morning, but they do not have peak time in the evening, as shown in the global line chart (T5). These two patterns were difficult to identify in the full dataset, and the roads that match them can further be explored in the tool using the attribute panel of GROUPSET (e. g., road segments average length, etc.)

Soccer Rankings

Soccer data analysis is becoming increasingly important as a wealth of data is now available to data scientists. In particular, games outcomes are indicators of teams performance that can be aggregated and represented over a season. The standard representation usually is a ranking of usually around 20 teams (for European leagues) over time 19 × 2 games, i. e., 38 games. We created 3 sets {TOP5, NORMAL, BOTTOM3} which rank corresponds to the teams qualified for European competitions, the non-qualified teams, and teams relegated to the inferior division (T1). The NORMAL group usually is not the aim of the top-performing teams, but it is for lessperforming teams (which usually never get to the TOP5 group).

Discarding early ranking variability. An essential property of permutations in soccer championships is that at the beginning, teams may change rank with a higher probability than later in the championship (when there are high points differences). So it is essential to discard the first days as shown in Fig. 5 by selecting the time interval from e. g., day 11 to the end as an analyzed period (T6). Once the beginning period is discarded, we sort the soccer teams by a trend to find the most stable soccer teams. We notice that three sets are being more stable than other sets, which contain four teams (Fig. 5): Paris, Troyes, Toulouse, and Monaco (T2). The most important thing is that these 4 teams are either stable at the top or bottom levels. Especially for Paris and Troyes, they did not change their rank from 11 to 38, and they are ranked first and last (T5).

Identifying best and worst performing teams. The next step is to answer basic performance questions such as which teams are the best or worst, which can immediately be seen on the championship's last day. However, we may dig a little bit into the analysis to check if this has been the case for the whole season. The rank by set membership degree shows teams that do not change group, so they have always performed very well or very poorly (Fig. 6). We aggregate the soccer teams by Degree and then sort them by Degree-Bottom 3 so as to get the soccer teams with the highest membership to the Bottom 3 on top (and the ones with partial membership to this group below) (T5). The team Troyes is the only one always being in the Bottom 3 from 11 to 38, even though its rank raised at the very beginning of the season (but got discarded with our initial temporal selection).

Feedback and Perspectives

We conducted a preliminary study to validate the usability of GROUPSET with 4 researchers that frequently use data visualization tools, to validate the tool's usability and detect any major design issues. We presented them with the tool loaded with the Soccer dataset as it is the easiest one to understand as all researchers were familiar with soccer. We then demonstrated the standard workflow from categorization to detailed view exploration. We then asked them to use the tool and follow a think-aloud protocol to capture their thoughts and understand their intentions. We first asked them to reproduce the demonstrated workflow and then they conducted an open-ended exploration with any dataset of their choice regarding the tasks. All participants found the flow of the tool relevant to explore such a dataset and logical from the exploratory chart to the detailed view. The main remark we collected was preserving the sequence of events we will discuss as a tool's limit. They also noticed some performance issues we will discuss in the next section.

Performance and scalability. The first feedback we collected during the usability study was the performance, especially when many elements and sets were presented. For some application domains, it may be needed to include more than 3 sets either because it is semantically relevant or because a finer grain of analysis of changes is needed. Currently, GROUPSET supports up to 5 sets which potentially generates an important number of intersections. However, as we only focus on analyzing a subset of the data (due to sorting and aggregation), we argue there is no need to calculate and visualize all the set intersections.

Applicability to other datasets and beyond line charts. Our tool is generic to support any temporal dataset (e. g., University rankings) without any change in the design. Regarding the type of chart it supports, it is applicable beyond line charts to all charts with a single dependent variable (time points) plotted on the Y-axis to visualize the distribution of elements values in each time point among different sets (Normal, Top 5, Bottom 5, etc), such as histograms, density plots, or bar charts. 2D temporal charts, such as scatterplots or geo-map, will require some significant change in the design but GROUPSET could be used as a marginal plot to filter and group such charts over time.

Limits and perspectives. GROUPSET currently does not capture intra-group variations and temporal changes in the pie chart: thus some temporal elements may be included in the same set intersection, despite having different patterns (e. g., one is increasing, the other decreasing). This issue could be addressed by adding a second level of aggregation to the intersections using a global trend indicator to group elements by either globally increasing or decreasing value. But this may generate additional intersections and slow performances. Another perspective of our work is to investigate alternative designs to the pie charts to encode intersections and memberships. While circles and pie charts are already used in [LGS * 14, YEB16b] for such encoding, there currently is no formal evidence they are the best-suited representation. We plan to implement and formally evaluate alternatives using other statistical charts (e. g., bar charts, box plots). Finally, the traffic density case only helps us analyze how traffic flows change over time. However, spatial information should be taken into account. In the next step, we will consider connecting GROUPSET with map to analyze the spatio-temporal information.

Acknowledgements

We thank Alexander Lex and the SICAL LIRIS team for their valuable feedback on an early version of the technique.

Figure 1 :

 1 Figure 1: GROUPSET technique overview. Sets are created from time-varying data (line chart) in x. The same sets are organized as columns to indicate partial membership as pie charts in y and set intersections are listed as rows to represent groups of similar lines (along with their partial membership representation) in z.

Figure 2 :

 2 Figure 2: GROUPSET to explore 20 soccer teams rank in France during a season (38 games). In x teams are categorized by rank into 4 sets (Top 5, Top 10, Bottom 10, and Bottom 5). Users can then explore the teams based on their memberships to those sets over a season and identify temporal patterns by manipulating a combination matrix of set intersections y. The final view provided by GROUPSET is a filtered line chart corresponding to each set intersection showing teams with similar patterns z along with other attributes (e. g., change). ite visualization [JE12] or Timecurves [BSH * 16] provide further comparison by similarities intra or inter temporal events. However, those techniques do not address scalability issues. RankExplorer [SCL * 12] and RankEvo [LXG * 16] are scalable trends detection and interpretation using glyphs, but they rely on visual aggregation hiding individual patterns within each group. Our work is also based on aggregation, but it introduces an approach to avoid sacrificing the representation of individual details. Our work is also closely related to categories exploration, where parallel coordinates charts [Ins85] are the flagship example. Building on this approach, ParallelSets [KBH06] displays groups of elements to reveal trends by cohorts. In [vLBA * 12], temporal categories are presented using a flow chart that emphasizes changes across pairs of categories. But both approaches aggregate elements. Sets are a natural way to analyze categories [AMA * 14] using setbased data models. TimeSet [NXWW16] shows groups changes over time using contours shapes. AggreSet [YEB16b] uses aggregation of elements to show their global membership to a category. PowerSet [AR17] is a scalable technique that enumerates all set intersections as a treemap and UpSet [LGS * 14] uses a matrix approach. Our work is deeply connected to those scalable techniques such as [ATWB20], which conveys set dynamics over time. Finally, our work is also connected to interactive set creation [LV21] which remains an under-explored area in the visualization community [AMA * 14].

  [ , , ] (black circle indicating 100% membership to a single set, gray circles 0% membership to the two others). If the membership is spread across multiple sets, the representation can be as follows e. g., [ , , ]. Total membership across sets is always 100%. GROUPSET addresses the following set-based tasks [AMA * 14]: T1: Create new sets. T2: Find elements with their set memberships and specific time intervals. T3: Find intersections with specific time intervals. T4: Analyze intersection relations with time intervals. T5: Analyze elements distribution with time intervals. T6: Filter time intervals.

  UpSet matrix [LGS * 14]. Each column is a set and each row encodes a single type of intersection, where the pie chart shows the intersection's partial membership inspired by AggrSet [YEB16a]. It aggregates the elements if they have the same distribution among sets. Such as shown in Fig.1, R1 and R3 both have 2/4 time points in High traffic, 1/4 time points in Medium traffic and 1/4 time points in Low traffic respectively. Moreover, GROUPSET also allows users sorting and filtering the aggregated groups to change the vertical resolution. Finally, a horizontal bar chart encodes the intersection's cardinality (i. e., number of elements). Each set intersection embeds a stacked chart encoding a change across two sets (Fig.2 y), which present the average change values of all elements in each set intersection, where green indicates ups, red downs, and orange stable slopes. The stack height (horizontal) shows the most frequent changes for each category of change.

Figure 3 :

 3 Figure 3: Road segments that are always not busy. An aggregated group with two subgroups contains 64 and 50 road segments that only belong to Free flow during 24 hours.

Figure 4 :

 4 Figure 4: The traffic flow patterns during morning peak. An aggregated group with 5 subgroups reaches the peak time in the morning, but some do not reach the peak in the evening.

Figure 5 :

 5 Figure 5: Discarded time interval in soccer data using the brush feature on the line chart (to keep time points between day 11 and day 38). Groups are then ranked by teams with less changes of sets (resulting in both the best and worst teams).

Figure 6 :

 6 Figure 6: Understanding the less performing team. They are the ones that had the worst rank for most of the season, except for Toulouse whose rank increased during the last games.

© 2022 The Author(s) Eurographics Proceedings © 2022 The Eurographics Association.


Romain Levayer
email: romain.levayer@pasteur.fr

Cell competition: bridging the scales through cell-based modeling

Cell competition is a context-dependent cell elimination process which has been proposed to rely on several overlapping mechanisms. A new study combining cell-based modeling and quantitative microscopy data help to sort out the main contributors of mutant cell elimination.

Main text

Despite the high frequency of deleterious mutations which appear in adult epithelia, the initiation of tumours remains relatively rare [START_REF] Kakiuchi | Clonal expansion in non-cancer tissues[END_REF] . This relies on the multiple mechanisms of intrinsic tumour suppression which prevents uncontrolled proliferation of pretumoural clones. One important mechanism which attracted a lot of attention in the past ten years is cell competition: a context-dependent cell elimination process which excludes miss-specified and abnormal cells from growing and homeostatic tissues. Cell competition is a widespread phenomenon occurring during early development and in adult tissues from Drosophila to Vertebrates 2 .

Several mechanisms have been proposed to participate to cell recognition and elimination [START_REF] Merino | Survival of the Fittest: Essential Roles of Cell Competition in Development, Aging, and Cancer[END_REF][START_REF] Matamoro-Vidal | Multiple Influences of Mechanical Forces on Cell Competition[END_REF] .

Thus, one challenge of the field is to sort-out the relative contribution of each mechanism which often co-exist. For instance, cells mutant for the apico-basal polarity gene scribble are eliminated by apoptosis from Drosophila imaginal tissues and from MDCK cell layer (Madin-Darby Canine Kidney cell) when surrounded by wild type (WT) cells [START_REF] Norman | Loss of Scribble causes cell competition in mammalian cells[END_REF][START_REF] Brumby | scribble mutants cooperate with oncogenic Ras or Notch to cause neoplastic overgrowth in Drosophila[END_REF] . This occurs through a combination of independent mechanisms: ligand-receptor interactions at the interfaces between the mutant and WT cells [START_REF] Yamamoto | The ligand Sas and its receptor PTP10D drive tumour-suppressive cell competition[END_REF] , secretion of factors inhibiting scribble mutants survival [START_REF] Katsukawa | Serpin Facilitates Tumor-Suppressive Cell Competition by Blocking Toll-Mediated Yki Activation in Drosophila[END_REF] or apoptosis induced by mutant cell compression [START_REF] Wagstaff | Mechanical cell competition kills cells via induction of lethal p53 levels[END_REF][START_REF] Bove | Local cellular neighborhood controls proliferation in cell competition[END_REF] . This illustrates the co-existence of multiple modes of elimination during competition despite similar genetic background. What is then the relative contribution of each phenomenon ? Our ability to sort them is actually limited by the gap that remains between the two main metrics of cell competition: on the one hand the short term description of the distribution of cell death (often based on staining of apoptotic cells), and on the other hand the long term effect of cell competition on population size and survival. To fill this gap, theoretical frameworks are required to assess how these cellular mechanisms can indeed affect the long-term survival of a cell population. These include continuous models based on differential equations and preypredator interactions [START_REF] Nishikawa | Mathematical model for cell competition: Predator-prey interactions at the interface between two groups of cells in monolayer tissue[END_REF][START_REF] Nishikawa | Effects of cell death-induced proliferation on a cell competition system[END_REF] , continuous models testing the effect of mechanical pressure on cell survival [START_REF] Shraiman | Mechanical feedback as a possible regulator of tissue growth[END_REF][START_REF] Basan | Homeostatic competition drives tumor growth and metastasis nucleation[END_REF][START_REF] Murphy | Mechanical Cell Competition in Heterogeneous Epithelial Tissues[END_REF] or cell-based model testing the role of compensatory growth [START_REF] Tsuboi | Competition for Space Is Controlled by Apoptosis-Induced Change of Local Epithelial Topology[END_REF] . However, these frameworks either fail to integrate cellular scale information (e.g.: cell death distribution, cell shape, cell movements, local pressure, tension) and/or were not confronted quantitively with experimental data, most likely because quantitative datasets are still very scarce. The assessment of the contribution of each competition mechanism to the persistence or elimination of one cell population remains therefore very challenging. This challenge has been elegantly tackle by Gradeci and colleagues in a recent article which bridges these gaps [START_REF] Gradeci | Cell-scale biophysical determinants of cell competition in epithelia[END_REF] . Focusing on the elimination of the scribble-silenced cells (Scribble KD ) in MDCK cells, the authors combined a new cell-based modeling framework with a highly quantitative dataset which was generated through long term live-imaging, segmentation and tracking [START_REF] Bove | Local cellular neighborhood controls proliferation in cell competition[END_REF] . Previously, the elimination of Scribble KD cells was suggested to be driven by their lower homeostatic density [START_REF] Wagstaff | Mechanical cell competition kills cells via induction of lethal p53 levels[END_REF][START_REF] Bove | Local cellular neighborhood controls proliferation in cell competition[END_REF] . The homeostatic density is the density at which cell proliferation is perfectly compensated by cell death [START_REF] Basan | Homeostatic competition drives tumor growth and metastasis nucleation[END_REF] . Above this value, death rate will be higher than proliferation, hence leading to population shrinkage, while below this value proliferation will be favored. Accordingly, Scribble KD cells have higher basal p53 levels (a pro-apoptotic factor) which set their homeostatic density lower than WT cells [START_REF] Wagstaff | Mechanical cell competition kills cells via induction of lethal p53 levels[END_REF] . Consequently, The WT cell population expands, brings Scribble KD cell density above its homeostatic value, hence forcing their progressive disappearance. Yet, experimental data outlined other mechanisms contributing to Scribble KD cell elimination, including active compaction of mutants cells through the convergent movements of WT cells toward them [START_REF] Wagstaff | Mechanical cell competition kills cells via induction of lethal p53 levels[END_REF] as well as a local boost of proliferation of the WT cells neighbouring Scribble KD cells [START_REF] Bove | Local cellular neighborhood controls proliferation in cell competition[END_REF] . As such, it remained unclear whether the difference in homeostatic density was sufficient to recapitulate the dynamics of Scribble KD cell elimination. To test this hypothesis, Gradeci and colleagues developed a cell-based modeling approach (so called Cellular Potts Model) which integrates mechanical inputs (relative affinity between cells, adhesion to substrate, cell velocity and cell compressibility) as well as celldecision automata controlling cell division and cell death (Figure 1). While the number of parameters are relatively large, many of them could be measured experimentally or constrained by the rich dataset previously generated by the authors, integrating data on cell shape, growth rate, number of neigbours and the relationship between density and death rate. Doing so, they could first recapitulate the dynamics of homogenous populations of WT or Scribble KD cells including the density reached at confluency. Using the same parameters, they then implemented competition between WT and Scribble KD cells. The model could recapitulate quantitatively the experimental evolution in time of cell number, death rate and division rate for the two populations. Altogether this suggested that the differences in mechanical properties and homeostatic density are sufficient to recapitulate the dynamics of Scribble KD cells elimination, independently of any sort of signaling between cells.

What are then the central regulators of this mechanical competition? Surprisingly, growth rate has little influence apart from delaying mutant cell elimination, in agreement with former predictions [START_REF] Basan | Homeostatic competition drives tumor growth and metastasis nucleation[END_REF] . The outcome of competition here is mostly controlled by two parameters: the difference in homeostatic density between the two populations and their relative stiffness/compressibility (Figure 1). The homeostatic density is an emerging property of the model which relies on two parameters: the relationship between density and cell death as well as contact inhibition (in other words, the reduction of proliferation by crowding). Interestingly, while contact inhibition dominates the dynamics of WT cells, this is rather neglectable in Scribble KD cells whose dynamics is dominated by apoptosis at high density. The second parameter, which was less expected, is the relative stiffness of cells. Scribble KD are eliminated provided that their stiffness is lower than WT cells. This can be intuitively understood by the fact that cells can be compressed by their neighbours provided they are more deformable/less stiff. Altogether, this demonstrated that the difference in homeostatic density and stiffness are sufficient to recapitulate quantitatively the elimination of Scribble KD cells.

To expand the application of their model, the authors implemented then another mode of competition which relies on the contact between the two cell types. Previously, it was shown that the elimination of cells with low Myc levels (an oncogene) correlated with the surface of contact shared with cells with high Myc levels [START_REF] Levayer | Cell mixing induced by myc is required for competitive tissue invasion and destruction[END_REF] . As such, the authors implemented a sigmoid increase of the death rate of the "loser" population as a function of the surface of contact shared with the other cell type. Interestingly, the dominant parameters that govern the outcome of competition are here completely different from the mechanical competition described above (Figure 1). As expected, the degree of initial mixing (from a salt-and-pepper pattern to a fully sorted condition with two large groups) dramatically changed the outcome of competition, where sorting promoted cell survival. Alternatively, cell elimination could also be accelerated by stabilizing heterotypic contacts, hence facilitating the mixing between the two populations.

These observations are in good agreement with experimental data showing the positive impact of cell mixing on cell competition [START_REF] Levayer | Cell mixing induced by myc is required for competitive tissue invasion and destruction[END_REF] . Since colony size has a strong impact on the time required to eliminate loser cells, this also suggests that contact-dependent competition impose a race for elimination: once the clone reach a critical size, a huge amount of time (incompatible with the characteristic time of development) would be required for its elimination. This might be even more relevant for competition occurring in Drosophila imaginal tissues which is constrained by the restricted time window of larval growth.

To conclude, the combination of a cell-based modeling approach with the rich quantitative dataset previously generated by the authors established one of the most realistic modeling framework of cell competition. This is the first clear demonstration that differences in homeostatic density are sufficient to recapitulate quantitatively the dynamics of Scribble KD cells elimination. Obviously, this does not exclude that other mechanisms may contribute to cell elimination. For instance, active compaction of mutant cells by directed migration of the WT cells toward the mutants was previously shown to accelerate compaction [START_REF] Wagstaff | Mechanical cell competition kills cells via induction of lethal p53 levels[END_REF] , and was more recently validated by the identification of a chemoattractant (FGF21) secreted by Scribble KD cells [START_REF] Ogawa | FGF21 Induced by the ASK1-p38 Pathway Promotes Mechanical Cell Competition by Attracting Cells[END_REF] . While relatively intuitive, the role of stiffness differences in mechanical competition is one the most unexpected prediction of the model. This nicely fits recent data showing how bacterial infection of epithelial cells can trigger mechanical-driven cell elimination through a reduction of infected cell stiffness [START_REF] Bastounis | Mechanical competition triggered by innate immune signaling drives the collective extrusion of bacterially infected epithelial cells[END_REF] . Given the increasing complexity of cell competition and the accumulation of pathways/mechanisms involved in cell elimination, such quantitative approaches will become more and more essential to comprehend the mechanisms that govern the long-term fate of cell populations. Left: Parameters of the cellular Potts Model, including mechanical parameters (J: surface energy, lower=stable junction), regulation of cell growth and division (progressive surface increase, division after a critical surface addition, so called "adder model", and contact inhibition) and regulation of cell death and extrusion. Right: two models of competition simulated in the Cellular Potts Model, mechanical competition on the top and contactdependent competition on the bottom. The conditions and the main parameters promoting "loser" cell elimination are outlined for each type of competition.

Figure legends

Figure1:

  Figure1: Cellular Potts Model and identification of the main parameters regulating mechanical competition and contact-dependent competition.

Cellular Potts Model

Mechanical competition

Contact-dependent competition

Cell mechanics:

Cell growth and division:

Cell death and extrusion:


Julien Tissot

Salma Yahiaoui

Peter Rosenbusch

Unique 700 m range extension of nacelle-lidars for modern offshore wind turbines

published or not. The documents may come   L'archive ouverte pluridisciplinaire

Lidar signal availability and rate of data collection are two key quantities for efficient power performance testing.

At all ranges, including 750m, the signal is more than 15dB above the system noise level. The CNR peaks near 220m, which is the chosen focal distance for this long range lidar.

▪ The observed Lidar signal availability drops by only 8%, from 95% at 50 m to 87% at 750 m distance. (Slight availability differences between the 4 Lidar beams are due to blocking from the turbine blades.) ▪ The number of data points in the infiltered set drops by only 12% at 750m when normalized to the first range gate (34 000 pts). The drop is quasi linear in range.

Results -Black Box comparisons Conclusion

▪

  operation costs of modern offshore wind turbines call for ever growing rotor diameters. 150 m diameter have been surpassed and 200 m are being tested. Future technology will no doubt tackle 250 m and more. Optimizing the operation of such turbines at any moment in time is absolutely primordial in order to meet the return-of-investment. Here nacelle-mounted Lidars provide the essential wind information and thereby warrant highest performance and efficient diagnostics including contractual power curve verification (PCV). IEC 61400-12-1 ed.2 is the current reference document and the suggested measurement 2.5 rotor diameters in front of the turbine is widely adopted. This poster presents measurements up to 750 m in front of a 8 MW, 167 m diameter wind turbine (WTG) using Leosphere's latest nacelle-mounted 4-beam Lidar. Wind speed measurements were compared to the ground based sensor, when wind direction and data filters allowed it. The figures below show the horizontal wind speed at hub height as measured by the WindCube Nacelle against the ground sensors. The data are very well fitted by linear regression. Nacelle, previously known as Wind Iris, installed on a 8 MW 167 m diameter 120 m hub height WTG is compared to one 120 m height IEC met mast and two ground-based WindCube Lidars placed respectively at 380 m, 395 m and 550 m from the WTG. Measurements were taken at DTU's Østerild wind turbine test field, a flat nearshore terrain, between June 2019 and February 2020 -9 months -and compared to the reference sensors on following wind sectors: ▪ Sensors at 380 m -Wind Direction from MM : 273°+-10°▪ Sensor at 550 m -Wind Direction from MM : 273°+-15°T he difference in sector size accounts for wake from the met mast at 380 m. and Data Rate This campaign proves that the new Leosphere long range WindCube Nacelle can measure wind fields up to 750 meters ahead with availabilities exceeding expectations and metrological performances equivalent to the previous 450 m range version. Horizontal windspeed measurements are consistent with the Lidar calibration best practices. Evaluation of other wind field characteristics was equally performed and results can be provided upon request. The carrier-to-noise ratio (CNR) indicates the strength of the Lidar return signal. The graph below shows the CNR for each beam and their average per range gate. Correlation between the WindCube Nacelle and both references, WindCube and met mast, are as expected. Slope and offset of the linear regressions are in agreement with the nacelle-lidar "white-box" calibration criteria, which is current industry best practice.


Since its introduction in the norm IEC 61400-12-1:2017 [1], the rotor equivalent wind speed (REWS) became a quantity of interest for wind turbine power performance testing (PPT). The REWS provides an accurate estimate of the kinetic flux passing through the rotor swept area as it accounts for the vertical shear and veer, which have significant impact on large WTG performances. This poster presents and evaluates the algorithm for calculating the REWS using the latest version of the WindCube Nacelle, previously known as Wind Iris.

REWS calculated from all lidars were compared when wind direction allowed it. Data was filtered so that the REWS from WindCube Nacelle was calculated with at least 4 heights. The data was fitted by linear regression. Nacelle operating system and the calculation volume will be configurable. ▪ Additional works will be carried out to assess the uncertainty reduction when using REWS measurements for PPT.

▪ The REWS from nacelle and ground based lidars agree very well and fit results are within the instrument calibration uncertainties. ▪ The effectiveness of averaging multiple sensing heights is demonstrated. ▪ Other components of the wind field were compared during this study [2] and could be discussed upon request.

The WindCube Nacelle, with its 2 pairs of beams, provides horizontal wind speeds (HWS) at two heights per range gate. As seen above, the standard requires at least three heights for the REWS computation. An algorithm was developed to fullfil this recommendation. The calculation at a given range gate uses the HWS within a configurable volume around this gate. This method benefits from the vertical beam opening, i.e. at each range gate the lidar is sensing a different height.

In the example above, the REWS is calculated using 12 HWS measurements at 12 different heights without any assumption on a vertical wind shear profile. Therefore, this implementation relies only on the hypothesis of horizontal flow homogeneity, which assumes that wind speed is homogeneous at a given height.

In simple terrain, outside the induction zone and wakes, this hypothesis is reliable and is already in use for both WindCube and WindCube Nacelle.

Campaign Results

International Electrotechnical Commission (IEC). Power Performance Measurements of Electricity Producing Wind

Turbines; IEC 61400-12-1 Ed. 2; International Electrotechnical Commission: Geneva, Switzerland, 2017

Conclusion

Where:

▪ n h is the number of available measurement heights (n h ≥ 3); ▪ v i is the wind speed measured at height i; ▪ A is the complete area swept by the rotor (i.e. πR 2 with radius R); ▪ A i is the area of the i th segment, i.e. the segment the wind speed v i ;" To account for the wind veer, an extended version of the equation is proposed in annex Q and defined as such:

Where φ i is the angle difference between the wind direction at hub height and in segment i. It is this extended version of the equation that we decided to implement in our system and evaluate during the campaign.

▪

  the second edition of the standard [1] : "The rotor equivalent wind speed is the wind speed corresponding to the kinetic energy flux through the swept rotor area, when accounting for the vertical wind shear. Where the wind speed for at least three measurement heights are available, the rotor equivalent wind speed is defined as: Our method to calculate REWS with WindCube Nacelle shows excellent correlation at both studied range gates (395 m & 550 m) with the IEC REWS calculated using the ground-based lidars. ▪ The algorithm will be a new feature in a future upgrade of the WindCube

A

  Leosphere WindCube Nacelle, installed on a 8 MW Wind Turbine with 167 m diameter (D) and 120 m hub height is compared to two ground-based WindCube Lidars placed respectively at 395 m and 550 m from the WTG. Measurements were taken at DTU's Østerild wind turbine test field, a flat nearshore terrain in Denmark, between June 2019 and February 2020 -9 months. The WindCube Nacelle was compared to the reference sensors on the following wind sectors : ▪ Sensors at 395 m -Wind Direction from : 273°+-10°▪ Sensors at 550 m -Wind Direction from : 273°+-15°T he difference in sector size accounts for wake from a met mast at 380 m.

  Note that the distances of measurement presented here are considered "long rage" for the current state of nacelle-based lidar technology. This study was part of a larger validation campaign of the new generation of WindCube Nacelle.


Keywords: Carpolepis, Metrosideros, Myrtaceae, Pacific, phylogeny, Tepualia

The genus Metrosideros (Myrtaceae) comprises 50-60 species found largely across the Pacific Islands. The relationships within this genus, including the circumscriptions of the subgenera Mearnsia and Metrosideros and their relationships with the other members of the tribe Metrosidereae (namely the New Caledonian endemic genus Carpolepis and the South American Tepualia), are poorly understood. Phylogenetic analyses were carried out using previously published ITS sequences, covering most species of the tribe, and new sequences of five single-copy nuclear genes with a reduced taxon sampling. The independent and combined analyses of the five nuclear genes using a range of approaches, including Bayesian single-gene, concatenated (MrBayes), concordance (BUCKy) and coalescent (*BEAST) analyses, yielded different topologies, indicating important conflicts among phylogenies based on individual genes. The deep relationships within the tribe Metrosidereae remain poorly resolved, but our results indicate that the species of Carpolepis and Tepualia are likely nested in the genus Metrosideros. A broad circumscription of the genus Metrosideros is therefore adopted, and the new combinations Metrosideros laurifolia var. demonstrans, Metrosideros tardiflora and Metrosideros vitiensis are here

Myrtaceae is a large family of predominantly tropical trees and shrubs with ca. 140 genera [START_REF] Wilson | in The families and genera of vascular plants[END_REF] and over 5000 species [START_REF] Govaerts | World checklist of Myrtaceae. Facilitated by the Royal Botanic Gardens[END_REF], including many economically important species used for timber, fruit, spices, and as ornamentals. Generic limits are still unresolved for some members of this family, e.g. Syzygium Gaertn. [START_REF] Biffin | Molecular systematics of Syzygium and allied genera (Myrtaceae): evidence from the chloroplast genome[END_REF], Rhodomyrtus (DC) Rchb. [START_REF] Snow | Morphological and Molecular Evidence of Polyphyly in Rhodomyrtus (Myrtaceae: Myrteae)[END_REF]. Recent molecular phylogenetic studies at the family level have delimited a number of tribes [START_REF] Wilson | Relationships within Myrtaceae sensu lato based on a matK phylogeny[END_REF][START_REF] Biffin | Evolution of exceptional species richness among lineages of fleshy-fruited Myrtaceae[END_REF][START_REF] Wilson | in The families and genera of vascular plants[END_REF] that allow more targeted follow-on studies at the tribal level to assess generic limits. Such approaches have already been applied to tribe Syzygieae [START_REF] Biffin | Molecular systematics of Syzygium and allied genera (Myrtaceae): evidence from the chloroplast genome[END_REF], Myrteae [START_REF] Lucas | Suprageneric phylogenetics of Myrteae, the generically richest tribe in Myrtaceae (Myrtales)[END_REF], Melaleuceae [START_REF] Edwards | Melaleuca revisited: cpDNA and morphological data confirm that Melaleuca L. (Myrtaceae) is not monophyletic[END_REF] and Backhousieae [START_REF] Harrington | Phylogenetic revision of Backhousieae (Myrtaceae): Neogene divergence, a revised circumscription of Backhousia and two new species[END_REF], leading to changes in generic boundaries, often broadening some genera to include other smaller ones.

Metrosideros Banks ex Gaertn. (tribe Metrosidereae) is a medium-sized genus (ca. 52 species) found primarily on the Pacific islands, including the Philippines and New Guinea, with an outlying species in South Africa [START_REF] Govaerts | World checklist of Myrtaceae. Facilitated by the Royal Botanic Gardens[END_REF]. The genus is interestingly absent from mainland Australia. Most species have potential as ornamentals, particularly pōhutukawa (Metrosideros excelsa Sol. ex Gaertn.) from New Zealand. Metrosideros is particularly ecologically important in Hawai'i, where the widespread and highly variable M. polymorpha Gaudich. dominates the canopies of most native forests. The genus is also emerging as a model for the study of speciation in trees, in particular sympatric speciation on Lord Howe Island [START_REF] Papadopulos | Speciation with gene flow on Lord Howe Island[END_REF] and incipient ecological speciation in Hawai'i [START_REF] Stacy | Incipient radiation within the dominant Hawaiian tree Metrosideros polymorpha[END_REF]. Despite a number of phylogenetic works published on Metrosideros, its relationships with other genera of Metrosidereae remain poorly understood. Besides Metrosideros, the tribe Metrosidereae also includes the New Caledonian endemic Carpolepis (J. W. Dawson) J. W. Dawson (three species) and the monotypic Tepualia Griseb. from southern Chile and Argentina. The genus Mearnsia Merr. sometimes is segregated from Metrosideros [START_REF] Wilson | in The families and genera of vascular plants[END_REF]), although regional monographs did not recognize this genus [START_REF] Allan | Flora of New Zealand[END_REF][START_REF] Dawson | Myrtaceae -Leptospermoideae[END_REF]. Besides recognizing Mearnsia, [START_REF] Briggs | Evolution in the Myrtaceae-evidence from inflorescence structure[END_REF] also suggested splitting Metrosideros in a number of smaller genera that have never been formally described with one exception. The species of Metrosideros subgenus Mearnsia section Adnatae J.W.

Dawson are now included in the genus Thaleropia Peter G. Wilson [START_REF] Wilson | Thaleropia, a New Genus for Metrosideros queenslandica (Myrtaceae) and its Allies[END_REF], which has been excluded from the tribe Metrosidereae and placed in the tribe Tristanieae [START_REF] Wilson | in The families and genera of vascular plants[END_REF].

Most phylogenetic studies carried out on the genus Metrosideros have not addressed taxonomic issues. For example, Wright (2000a) focused on dispersal of Metrosideros subgenus Metrosideros across the Pacific using ITS sequence data, whereas a later study [START_REF] Wright | Energy and the rate of evolution: inferences from plant rDNA substitution rates in the western Pacific[END_REF] focused on the rate of molecular evolution in ITS and ETS sequences within the subgenus Mearnsia. A phylogenetic study based on ITS data focusing on the New Caledonian Metrosideros [START_REF] Wright | [END_REF], including a single species from New Zealand, suggested that Carpolepis may be nested within Metrosideros, and that subgenus Mearnsia may not be monophyletic. The first comprehensive phylogeny of the genus Metrosideros not restricted to a subgenus or archipelago focused on dating the Cape endemic Metrosideros angustifolia (L.) Sm. [START_REF] Warren | The distribution of species diversity across a flora's component lineages: dating the Cape's 'relicts[END_REF] supplementary data, ITS sequence). Tepualia was included in a later molecular phylogenetic study using ITS, ETS matK, and psbA-trnH, and found to be close to Metrosideros [START_REF] Lucas | [END_REF]. More recently, Papadopulos et al. (2011, supplementary data) conducted a phylogenetic analysis of Metrosideros using ETS, ITS, 5S, rps16, and trnL-trnF with broad sampling across taxa that included Tepualia, but which focused primarily on the origin of the two species endemic to Lord Howe Island. No previous molecular phylogenetic study included comprehensive sampling of Metrosideros (subgenera Metrosideros and Mearnsia), as well as both Carpolepis and Tepualia. In addition, previous studies (Wright et al., 2000a;[START_REF] Wright | Stepping stones to Hawaii: a trans-equatorial dispersal pathway for Metrosideros (Myrtaceae) inferred from nrDNA (ITS plus ETS)[END_REF] revealed two distinct and distant clades within M. collina (J.R. Forst. & G.

Forst.) A. Gray, the only species of Metrosideros found on multiple archipelagoes. The taxonomic limits of this widespread species warrant further study.

In this study we re-analyzed ITS sequence data from GenBank available for most species of tribe Metrosidereae. We also sequenced five single-copy nuclear genes for a subset of taxa to address the monophyly of Metrosideros subgenus Metrosideros and subgenus Mearnsia, and the distinctiveness of Carpolepis and Tepualia. In addition, we aimed to assess the delimitation of M. collina, including its possible division into multiple species.

MATERIALS AND METHODS

ITS Sequence Analysis-We downloaded ITS sequences from GenBank for all species of tribe Metrosidereae (Metrosideros, Carpolepis, and Tepualia), including multiple accessions for M. collina (Appendix 1). Sequences were available for all species of the tribe currently recognized in the World checklist of Myrtaceae [START_REF] Govaerts | World checklist of Myrtaceae. Facilitated by the Royal Botanic Gardens[END_REF] with the exception of M. arfakensis Gibbs, M. parallelinervis C.T. White, and M. regelii F. Muell., all from New Guinea, which have never been included in any molecular phylogenetic analysis. In [START_REF] Wright | 9 Two ITS sequences labeled Metrosideros cf. salomonensis in GenGank are clearly distinct. We have inferred one, ascribed to subgenus Metrosideros, to correspond to M. salomonensis (AF172766). The other, DQ328801[END_REF] all species from New Guinea and the Philippines are part of a well-supported monophyletic group, and the three unsampled species may be expected to fall in this clade.

Samples of Thaleropia, Tristania R. Br. (tribe Tristanieae) and Cloezia Brongn. & Gris were included as outgroups and the tree was rooted with Syzygium.

ITS sequences were aligned with MUSCLE within MEGA6 [START_REF] Tamura | MEGA6: Molecular Evolutionary Genetics Analysis Version 6.0[END_REF], and the alignment was deposited in TreeBASE (study number TB2:S16972). The best-fit evolution model was GTR + I + γ according to jModeltest analysis [START_REF] Posada | jModelTest: phylogenetic model averaging[END_REF]. Phylogenetic analysis was conducted in MrBayes [START_REF] Ronquist | MrBayes 3: Bayesian phylogenetic inference under mixed models[END_REF] running one-million generations of Markov Chain Monte Carlo (MCMC), sampling one tree every 1,000 generations, using the gene-specific substitution model and default settings otherwise.

Convergence of runs and adequate MCMC sampling were checked using Tracer [START_REF] Rambaut | Tracer v.1.4[END_REF]. The burn-in period per run was then set to 250,000 generations, and the remaining trees were used to construct a half-compatible consensus tree and its associated estimated posterior probabilities.

Single-Copy Nuclear Genes-

SEQUENCING-As part of a larger study on the phylogenomics of Metrosideros, five single-copy nuclear genes (exon-primed intron crossing) were used here on a smaller sample of tribe Metrosidereae (Appendix 2). We included all genera of tribe Metrosidereae and both subgenera of genus Metrosideros; the same accessions were used for all five genes. Primers (Table 1) were designed following the protocols described in a previous study [START_REF] Pillon | Primers for low-copy nuclear genes in Metrosideros and cross-amplification in Myrtaceae[END_REF]. The loci were amplified using Fluidigm access arrays (48 × 48 well fluidigm chip) and sequenced on a quarter Miseq plate (sequencing v3, 600 cycles) at the Institute for Bioinformatics and Evolutionary Studies (IBEST, University of Idaho) as part of a larger study involving additional genes and accessions from the Hawaiian Islands. With this sequencing procedure, alleles of heterozygote accessions were readily separated (phased). DNA extracted from silica-dried leaves of Carpolepis laurifolia (Brongn. & Gris) J. W. Dawson and Metrosideros cacuminum J. W. Dawson was too degraded or diluted for successful sequencing with the above procedure, so was amplified and sequenced using standard Sanger sequencing (see [START_REF] Pillon | Primers for low-copy nuclear genes in Metrosideros and cross-amplification in Myrtaceae[END_REF], for full protocols for DNA extraction and PCR amplification). Those sequences were subsequently phased using DnaSP [START_REF] Librado | DnaSP v5. a software for comprehensive analysis of DNA polymorphism data[END_REF] using the default settings.

INDIVIDUAL-GENE BAYESIAN PHYLOGENETIC ANALYSIS-All analyses were executed with phased alleles. The best-fit evolution models for each locus were HKY (MeNu40), HKY + I (MeNu42), HKY (MeNu55), HKY +  (MeNu68), and HKY (MeNu74). Analyses in GARD [START_REF] Pond | GARD: a genetic algorithm for recombination detection[END_REF], assuming no site-to-site rate variation, did not reveal any sign of recombination in any of the individual alignments. We ran one-million generations of MCMC in MrBayes [START_REF] Ronquist | MrBayes 3: Bayesian phylogenetic inference under mixed models[END_REF], sampling one tree every 1,000 generations and using gene-specific substitution models for each locus. Convergence of runs and adequate MCMC sampling were checked using Tracer, and the burn-in period per run was then set to 250,000 generations.

CONCATENATED BAYESIAN PHYLOGENETIC ANALYSIS-Multiple alleles within individuals were combined into a single sequence using IUPAC nucleotide codes. We ran one-million generations of MCMC in MrBayes, sampling one tree every 1,000 generations using genespecific substitution models for all loci, unlinking substitution models, discarding a burn-in period of 250,000 generations, and default settings otherwise. CONCORDANCE ANALYSIS-We carried out a concordance analysis in BUCKy [START_REF] Ané | Bayesian estimation of concordance among gene trees[END_REF][START_REF] Larget | BUCKy: gene tree/species tree reconciliation with Bayesian concordance analysis[END_REF] to detect common phylogenetic signals among the different nuclear genes that may display some conflicts. Alleles in heterozygotes were combined using IUPAC codes for ambiguous bases. We ran phylogenetic analyses in MrBayes for each gene independently, running 1,200,000 generations, sampling every 100 generations and discarding the first 200,000 generations. We ran four parallel concordance analyses in BUCKy with 10-million generations with priors ( set to 2 for the analysis with four genes (MeNu40, MeNu42, MeNu68, and MeNu74) and 3 for the analysis with all five genes (as MeNu55 was missing for Carpolepis), and default settings otherwise. A number of preliminary analyses were run to determine the number of concordant trees present in each dataset. Optimal values for were determined as the ones yielding the highest prior probability for the actual numbers of trees observed using R code available from http://anewww.cs.wisc.edu/bucky/prior.html. *BEAST ANALYSIS-We ran a phylogenetic analysis using phased alleles for all five genes in *BEAST within BEAST 2 [START_REF] Bouckaert | BEAST 2: A software platform for Bayesian evolutionary analysis[END_REF]. The analysis was run twice using default settings (strict clock, population function constant, tree prior Yule), a chain of 200 million generations sampling every 20,000 generations, and a burn-in of 20 million generations.

Adequate sampling and convergence of the two runs were checked in Tracer, and the two runs were then combined.

NETWORK ANALYSIS-We measured the pairwise genetic distance (number of substitutions) between phased alleles for each of the five single-copy nuclear genes using MEGA6 [START_REF] Tamura | MEGA6: Molecular Evolutionary Genetics Analysis Version 6.0[END_REF]. A single pairwise standardized distance matrix between taxa accounting for all five genes was obtained using POFAD [START_REF] Joly | Incorporating allelic variation for reconstructing the evolutionary history of organisms from multiple genes: an example from Rosa in North America[END_REF], which was then used to build a network using the NeighborNet analysis in Splitstree [START_REF] Huson | Computing recombination networks from binary sequences[END_REF][START_REF] Huson | Application of phylogenetic networks in evolutionary studies[END_REF].

Taxonomic treatment-Type specimens were examined at K, and other type images were viewed online.

RESULTS

In the phylogenetic analysis based on ITS sequence data (Fig. 1), the tribe Metrosidereae is a well-supported monophyletic group with a deep polytomy. Carpolepis and subgenus Metrosideros (when including section Neocaledonica) are well-supported monophyletic groups, but subgenus Mearnsia (sections Mearnsia, Calyptropetala, and Crystalla) is not supported as a monophyletic group: taxa form multiple lineages that are unresolved with respect to the basal polytomy in the tribe, along with some samples grouped with weak support with Carpolepis (Fig. 1). Section Mearnsia (including M. albiflora Sol. ex Gaertn., M. halconensis (Merr.) J. W. Dawson, and M. porphyrea Schltr.) and section Calyptropetala J.W. Dawson (including M. operculata Labill. and M. perforata (J. R. Forst. & G. Forst.) Druce) sensu [START_REF] Dawson | Pacific capsular Myrtaceae XI. Redefinition of Metrosideros Banks ex Gartn. and definition of infra generic categories[END_REF] Despite conflicts in tree topology based on the individual-gene analyses, the concatenated analysis (Fig. 2) yielded an almost fully resolved tree with all nodes supported by strong posterior probabilities, with just two exceptions: the unresolved relationships between Hawaiian and Tahitian Metrosideros, and the weakly supported position of M. boninensis (Hayata ex Koidz.) Tuyama. The latter species appeared as sister to the rest of the tribe Metrosidereae, a relationship not recovered in any of the individual-gene analyses. The concatenated phylogenetic tree and primary concordance tree (Fig. 3) agreed at a number of nodes: a monophyletic group that includes species from Tahiti and the Hawaiian Islands

DISCUSSION

Our study reveals important conflicts among the tree topologies derived from different single-copy nuclear genes, thus illuminating the importance of careful analysis of such loci, particularly in combination. The blind concatenation of conflicting genes can yield an almost fully resolved topology that is not recovered in any single-gene analysis. The different total-evidence analyses yielded different topologies, and none of them appears clearly preferred over the others. Bayesian coalescent analyses tend to yield low posterior probabilities (see [START_REF] Arbizu | Phylogenomics of the carrot genus (Daucus, Apiaceae)[END_REF][START_REF] Folk | Phylogenetic relationships and character evolution in Heuchera (Saxifragaceae) on the basis of multiple nuclear loci[END_REF], for other case studies).

The concordance factor in Bayesian concordant analysis (BUCKy) tends to be well below 1 (see also [START_REF] Arbizu | Phylogenomics of the carrot genus (Daucus, Apiaceae)[END_REF], and it is not clear beyond what threshold a node can be considered well supported. The network analysis may be more conservative since it is not entirely dichotomous, but it does not provide measures of confidence. A high frequency of gene conflicts in Metrosideros suggests that a large number of genes will be necessary to fully understand phylogenetic relationships within this genus, possibly because of ancient hybridization events (see [START_REF] Pillon | Gene discordance in phylogenomics of recent plant radiations, an example from Hawaiian Cyrtandra (Gesneriaceae)[END_REF], for another similar case in Gesneriaceae).

Despite significant conflicts among the nuclear genes, some patterns are consistently recovered that are in agreement with, or at least not contradicted by, the ITSonly phylogenetic analysis. Carpolepis is nested within Metrosideros although its sister group differs between ITS, MeNu42, and MeNu74. [START_REF] Dawson | New species and combinations in New Caledonian Metrosideros and Carpolepis (Myrtaceae) with notes on other species[END_REF] segregated Carpolepis from Metrosideros because of its yellow flowers and sympodial growth, two characters occasionally found in Metrosideros [START_REF] Dawson | Myrtaceae -Leptospermoideae[END_REF]; and its winged seeds, a character that is quite homoplasious within Myrtaceae [START_REF] Wilson | in The families and genera of vascular plants[END_REF]. Tepualia is recovered as either sister to Metrosideros angustifolia with strong support in analyses based on MeNu40 and MeNu55, sister to Metrosideros angustifolia + Carpolepis with moderate support in analysis based on MeNu74, or as having an unresolved position within Metrosideros in analyses with other genes, including ITS. Tepualia was never recovered as sister to Metrosideros. The sister group relationship between Tepualia and M. angustifolia had previously been recovered in a cladistic analysis based on morphological characters [START_REF] Wilson | Myrtaceae in the Pacific, with special reference to Metrosideros[END_REF]. Both have indeed white flowers, but so does the New Caledonia M. operculata, which is is not closely related to these two species. The genus Tepualia was distinguished from Metrosideros due to the absence of broad protective scales in the vegetative bud, which are also missing in some species of subgenus Mearnsia (Dawson, 1972a[START_REF] Dawson | Pacific capsular Myrtaceae XI. Redefinition of Metrosideros Banks ex Gartn. and definition of infra generic categories[END_REF]. It is now known to also differ by its dicolporate pollen (Thornhill et al., 2012a), a character also found in the more distantly Acmena DC. (syn. Syzygium) and Pileanthus Labill. (Thornhill and Crisp, 2012); and the pairs of spherical vesicles flanking leaf bases (Dawson, 1972b), a character that is likely autapomorphic.

Maintaining Carpolepis and Tepualia as independent genera would likely require the splitting of Metrosideros into several smaller genera, some yet to be described, as has been recommended previously based on morphology [START_REF] Briggs | Evolution in the Myrtaceae-evidence from inflorescence structure[END_REF]. However, even in a narrow sense (Metrosideros subgen. Mearnsia sect. Mearnsia sensu [START_REF] Dawson | Pacific capsular Myrtaceae XI. Redefinition of Metrosideros Banks ex Gartn. and definition of infra generic categories[END_REF], Mearnsia is not monophyletic according to ITS data, and most other groups distinguished by [START_REF] Briggs | Evolution in the Myrtaceae-evidence from inflorescence structure[END_REF] are small if not monotypic, and have never been formally described taxonomically. Currently, little morphological or phylogenetic evidence supports the splitting of Metrosideros into numerous monophyletic groups, and the conflicts among the five nuclear genes examined here suggest that an improved understanding of evolutionary relationships with this genus will require data from a large number of loci.

Adopting a broad concept of Metrosideros on the other hand would have a number of advantages. The genus would be clearly defined as the equivalent of the well-circumscribed tribe Metrosidereae. In terms of nomenclatural stability, only two combinations for names in Carpolepis are needed since the name Metrosideros stipularis (Hook. & Arn.) Hook. already exists for the species of Tepualia. A broadly defined Metrosideros would still be of moderate size (50-60 species), whereas narrow generic concepts would require the recognition of many small genera (some monotypic, e.g. Tepualia), many of which remain undescribed (e.g., probably at least one to accommodate the South African M. angustifolia).

Proposed taxonomic changes associated with the expanded concept of Metrosideros are provided below.

Analyses of the single-copy nuclear genes also agree with the ITS analysis in the distinction of two components within the widespread Metrosideros collina. The plants from French Polynesia (where the type of the species was collected) and the Cook islands are close genetically to the plants from the Hawaiian Islands. Samples from Vanuatu, Fiji, and Samoa occur in a different part of the trees, although their closest relatives are yet unknown. The oldest name described for a plant in this area is Metrosideros collina var. vitiensis A. Gray (Smith, 1973), which is raised here to the species rank.

As newly circumscribed, Metrosideros includes ca. 60 species, mostly on the Pacific Islands, including New Guinea and the Philippines, with outlier species in South Africa and South America. The geographical origin of Metrosideros is difficult to determine with currently available data. Deep relationships within Metrosideros are poorly resolved, and the closest relatives of the African and American species are unknown. Relationships between Metrosidereae and the related tribes Backhousieae, Kanieae, Myrteae, Syzygieae and Tristaneae are also poorly resolved [START_REF] Biffin | Evolution of exceptional species richness among lineages of fleshy-fruited Myrtaceae[END_REF]. Metrosideros originated some time during the Cenozoic (Thornhill et al., 2012b), and its occurrence on most high Pacific islands, South Africa, and South America is likely explained by the capacity of its seeds to disperse by wind over long distances [START_REF] Drake | Seed dispersal of Metrosideros polymorpha (Myrtaceae): a pioneer tree of Hawaiian lava flows[END_REF][START_REF] Wilson | Myrtaceae in the Pacific, with special reference to Metrosideros[END_REF]. ("umbellata"). Ballardia Montrouz., Mém. Acad. Imp. Sci. Lyon, Sect. Sci., sér. 2, 10: 204 (1860).

non Balardia Cambess. ( 1829). -TYPE: Ballardia elegans Montrouz. Carpolepis (J.W.Dawson) J.W. Dawson, Bull. Mus. Natl. Hist. Nat., B, Adansonia 1984: 466 (1984publ. 1985).-TYPE: Carpolepis elegans (Montr.) J. W. Dawson. syn. nov. Mearnsia Merr., Philipp. J. Sci., C 2: 283 (1907).-TYPE: Mearnsia halconensis Merr. Baum.-Bod., Syst. Fl. Neu-Caledonien 5: 77 (1989), nom. inval. (no replaced synonym reference, [START_REF] Govaerts | World checklist of Myrtaceae. Facilitated by the Royal Botanic Gardens[END_REF]. Tepualia Griseb., Abh. Königl. Ges. Wiss. Göttingen 6: 119 (1854).-LECTOTYPE (designated here): Tepualia stipularis (Hook. & Arn.) Griseb. syn. nov.

Microsideros

Under this new circumscription, Metrosideros is the sole member of tribe Metrosidereae (see [START_REF] Wilson | Relationships within Myrtaceae sensu lato based on a matK phylogeny[END_REF][START_REF] Wilson | in The families and genera of vascular plants[END_REF], for a morphological description) and contains ca. 60 species. Apart from [START_REF] Dawson | Myrtaceae -Leptospermoideae[END_REF] revision for New Caledonia, recent revisions are unavailable for the Solomon Islands or New Guinea, the latter of which has the third-highest level of diversity after New Caledonia and New Zealand. Cuming 32 was chosen over Cuming 33 as the lectotype for Tepualia stipularis because more material is available (three specimens rather than two). Both gatherings are equally representative of the species and are highly similar morphologically; both are from Valdivia, Chile. Regarding lectotypification of P. philippiana, Taxonomic Literature 2 [START_REF] Stafleu | Taxonomic literature 2[END_REF] describes GOET as being a primary deposit for Philippi material and Grisebach worked mostly in Göttingen. We therefore select Philippi 89 at GOET as the lectotype for Tepualia philippiana as it likely to be the original material on which the taxon ).

Metrosideros laurifolia

  are not monophyletic. As anticipated, M. collina is composed of two distinct groups, one comprising accessions from French Polynesia and the Cook Islands that are closely related to all Hawaiian and some New Zealand species, and the other comprising accessions from Vanuatu, Fiji, and Samoa. All of the nuclear genes were successfully amplified and sequenced for our reduced taxon sampling, except MeNu55 for Carpolepis laurifolia. Individual-gene analyses yielded somewhat different topologies (Fig. 2), particularly with respect to the relative positions of Carpolepis, Tepualia, and Metrosideros angustifolia, and the relative positions of M. collina (Samoa), M. excelsa, and M. nervulosa C. Moore & F. Muell. The three Hawaiian species (M. macropus Hook. & Arn., M. polymorpha, and M. rugosa A. Gray) and the Tahitian M. collina (east Polynesian Metrosideros) have almost identical sequences for all five genes, thus leaving their relationships unresolved. The BUCKy analysis indicated that three different tree topologies (i.e. three different gene groups) were present in both of the four-genes analysis (mean number of groups = 3.1, standard deviation = 0.249) and the five-gene analysis (mean = 3.0, SD = 0.016). MeNu68 and MeNu74 yielded concordant topologies in both analyses. MeNu40 and MeNu55 (not included in the four-gene analysis) yielded concordant topologies in the five-gene analysis.

(

  east Polynesian Metrosideros), and a monophyletic group including Carpolepis, Tepualia, M. angustifolia, and M. cacuminum (Figs. 2, 3). The three analyses (those based on concatenation, *BEAST and BUCKy) yielded different topologies for the relationships among M. collina from Samoa, M. excelsa, M. nervulosa, and the East Polynesian Metrosideros, as well as for the relationships among Carpolepis, Tepualia, M. angustifolia, and M. cacuminum. Metrosideros boninensis was sister to the rest of the genus Metrosideros in the concatenated analysis, sister to the rest of the subgenus Metrosideros in the *BEAST analysis, and sister to the Samoan M. collina in the BUCKy analysis. The Splitstree network (Fig. 4) further supported the conflicts observed among the various phylogenetic analyses. Metrosideros boninensis has an intermediate position between the rest of the subgenus Metrosideros and the group composed of Carpolepis, Tepualia, M. angustifolia, and M. cacuminum. The relatively large loop observed in the network between the Samoan M. collina and M. excelsa indicates that there are conflicts regarding their relative positions. Carpolepis also branches on a loop of the network between M. angustifolia (sister group in the concordance analysis) and M. cacuminum (sister group in the *BEAST analysis).

  Gaertn., Fruct. Sem. Pl. 1: 170 (1788), nom. cons.-TYPE. Metrosideros spectabilis Sol. ex Gaertn. (typ. cons.). Agalmanthus (Endl.) Hombr. & Jacquinot in J. S. C. Dumont d'Urville, Voy. Pôle Sud, Atlas (Dicot.): t. 1 (1843).-TYPE: Agalmanthus umbellatus (Cav.) Hombr. & Jacquinot.

  was based. No type material was cited in the protolog of Tepualia philippii, only the locality 'Osorno Volcano.' No material with this name or locality has yet been located.Metrosideros tardiflora (J.W. Dawson) Pillon comb. nov. Basionym: Carpolepis tardifora J.W.Dawson, Bull. Mus. Natn. His. Nat., Paris, ser. 4, sect. B, Adansonia 6(4): 468 (1984, publ.

TABLE 1 .FIG. 1 .

 11 FIG. 1. Half-compatible Bayesian phylogenetic tree of the tribe Metrosidereae based

  Brongn. & Gris. var. demonstrans (Tison) Pillon comb. nov. Basionym: Metrosideros demonstrans Tison, Compt. Rend. Assoc. Franc. Avanc. Sci., STIPULARIS (Hook. & Arn.) Hook. f., Bot. Antarct. Voy. I. (Fl. Antarct.). 2: 275 (1846). Myrtus stipularis Hook. & Arn., Bot. Misc. 3: 316 (1833). Tepualia stipularis (Hook. & Arn.) Griseb., Sys. Bemerk. 31 (1854). Nani stipularis (Hook. & Arn.) Kuntze, Revis. Gen. Pl. 1: Tepualia patagonica Phil., Anales Univ. Chile 84: 755 (1893).

	242 (1891). -TYPE: CHILE. Chiloe, Cuming 32 (lectotype: designated here, K [000565021]!;
	isolectotypes: K!, E!; remaining syntypes: Cuming 33, K!, E!).
	Tepualia philippiana Griseb., Sys. Bemerk. 32 (1854). -TYPE: CHILE. March 1852,
	Philippi 89 (lectotype: designated here, GOET!; Isolectotypes: K! GOET!, P [P05235964,
	P05235947]!, S!, SGO!)
	Tepualia philippii Griseb. ex Phil., Linnaea 28: 637 (1857). -TYPE: "Ad radicales
	borealem vulcani de Osorno dicti Februario 1852 legi", collector unknown (location
	unknown).
	Clermont-Ferrand 5: 462 (1877). -TYPE: NEW CALEDONIA. Mt Humboldt, feb. 1972, Balansa
	3407 (lectotype: by Dawson 1992, P [P00057638]!; isolectotypes: P [00057639,
	P00057640]!). Carpolepis laurifolia (Brongn. & Gris. ) J. W. Dawson var. demonstrans (Tison)
	J. W. Dawson, Bull. Mus. Natn. His. Nat., Paris, ser. 4, sect. B, Adansonia 6(4): 468 (1984,
	publ. 1985).

METROSIDEROS


Matheus Teixeira
email: teixeirista@gmail.com

Victor Sarinho
email: vsarinho@uefs.br

Keywords: Higher education, Student retention, Serious game

de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

Nowadays, there are a lot of reasons why a student might drop out of university. Among the usual reasons for this phenomenon, some of them stand out, such as methodology disagreement, comprehension difficulty, monetary problems, bad college infrastructure, no adaptation to the academic environment, etc. They also come along with different types of personal problems, such as, diseases, home moving and psychological problems, for example [START_REF] Paredes | A evasão do terceiro grau em Curitiba[END_REF].

The lack of information during the first year, the student unsuitability with the university system, and the inability of create new friendships are also pointed as the main reasons of college evasion [START_REF] Cunha | Evasão do curso de química da Universidade de Brasília: a interpretação do aluno evadido[END_REF]. This is also attributed to the lack of communication and information faced by the university environment [START_REF] Da Silva | Aumento da Adesão e do Engajamento de Usuários do Campus Social com Uso de Mecanismos de Gamificação[END_REF], something that could be solved by appropriated information systems as a whole.

Undergraduates are deeply in touch with digital games, bringing the game play to a new purpose level, such as education and spread knowledge [START_REF] Da Silva | Ludicidade e matemática: Um novo olhar para aprendizagem[END_REF]. In this sense, this paper presents University Universe, a digital game that simulates the hard task of finishing semesters during a university course. It aims to represent the tension of a university student life, showing common problems found by them in a fun and casual way that must be solved during the game play.

The University Universe Game

Designed to be a mobile game that could be played with only one hand, the University Universe game dynamic is to balance the essential attributes of a university student: health, money, social life and grades (Fig. 1). These attributes are modified by the execution of campus activities according to the game map (Home, Library, Cafeteria and Academic Research Facility) (Fig. 2), which must be kept at a certain minimum value to continue playing. Each level represents a semester and the difficulty increases as the semesters advance, simulating what students face in a real course. By the usage of a game design canvas approach [START_REF] Sarinho | XVI Simpósio Brasileiro de Jogos e Entretenimento Digital[END_REF], important features were identified to develop an initial game prototype, such as:

-Initial menu and gameplay scenarios (Fig. 3); -HUD with the following attributes: health, grades, money, social life and the semester time indication (Fig. 1); -Automatic decrease of player attributes as the time goes during the semester; -Verification of the minimum attribute value required to go to the next semester; -Representation of the current scene the player is on; -Definition of which location affects the attributes in a certain way, during the time and as the player clicks the scene; -Change location according to the map selection; -Record of the semester reached by the player; and -End game when the player does not have the minimum attribute value required or if an attribute reaches zero. At the beginning of the game, the player has all attribute values maxed out (100 points). The player character starts at Home (Fig. 3), and, when the scene is touched, attributes are increased or decreased according to the context defined for the respective campus activity:

-Home increases health in 3 points, decreases grades in 2 points; -Library increases study in 4 points, decreases health in 2 points and social life in 1 point; -Cafeteria increases health and social life in 2 points, decreases money in 1 point; and -Academic Research Facility increases grade and money in 2 points, decreases health in 2 points and social in 1 points.

The location-based effects were defined by personal experiences during the academic life. For instance, it was verified that productivity decreased at home, due to the number of possible distractions. On the other hand, health increases, due to the rest and procrastination possibilities. Conversely, a long time procrastinating might cause the opposite effect. So, in the game, if the player stays in a location for a long time, it will be harmful.

The first semester introduces the player to the gameplay and mechanics, working as a game tutorial. It lasts 60 seconds while the following semesters are 100 seconds long. This game design decision was made during beta testing, where all semesters were 200 seconds long. This duration was considered too long by the initial players who tested the game.

When a semester ends, the attributes need to be more or equal to the minimum values required to keep playing. In the first semester, the minimum value of all attributes is 30 points and, as the following semesters advance, this value is increased by 5 points.

There are 4 ways to lose the game, one for each attribute to convey a message about academic reality. For example, when the health attribute ends, a funny message warning is displayed about the importance of mental and physical health care during college years. When the grade attribute reaches zero, the player is warned that he can not leave his academic life behind.

Conclusions and Future Work

This paper presented University Universe, a mobile game developed to the player faces the difficult task of finishing semesters in a university. It is a challenge that has a significant impact on the reality of student retention, which has been turned into a gamified activity that introduces a funny perspective on the current life status of most undergraduates.

As future work, new functionalities will be implemented, such as adding random events that could turn out to be beneficial or harmful for the university student (surprise tests, dating, etc). The correct balance between the attributes and scenes for new implemented events, resources and scenes will also be performed, together with an online ranking able to share obtained results in social networks as a viral marketing strategy for the game.

Finally, the University Universe arcade is under construction to be placed in a popular university environment, where students opinions and suggestions about the game, especially about how the game has changed their life prospects as an undergraduate student, will be collected by them.

Fig. 1 .

 1 Fig. 1. HUD displaying the current player status.

Fig. 2 .

 2 Fig. 2. Map of the University Universe game.

Fig. 3 .

 3 Fig. 3. General overview of the game scenes.