Miracle-dz/UniFAR-FTUs huggingface dataset:
Bayesian Inference of Species Trees from Multilocus Data

Until recently, it has been common practice for a phylogenetic analysis to use a single gene sequence from a single individual organism as a proxy for an entire species. With technological advances, it is now becoming more common to collect data sets containing multiple gene loci and multiple individuals per species. These data sets often reveal the need to directly model intraspecies polymorphism and incomplete lineage sorting in phylogenetic estimation procedures. For a single species, coalescent theory is widely used in contemporary population genetics to model intraspecific gene trees. Here, we present a Bayesian Markov chain Monte Carlo method for the multispecies coalescent. Our method coestimates multiple gene trees embedded in a shared species tree along with the effective population size of both extant and ancestral species. The inference is made possible by multilocus data from multiple individuals per species. Using a multiindividual data set and a series of simulations of rapid species radiations, we demonstrate the efficacy of our new method. These simulations give some insight into the behavior of the method as a function of sampled individuals, sampled loci, and sequence length. Finally, we compare our new method to both an existing method (BEST 2.2) with similar goals and the supermatrix (concatenation) method. We demonstrate that both BEST and our method have much better estimation accuracy for species tree topology than concatenation, and our method outperforms BEST in divergence time and population size estimation.
Coseismic and Postseismic Deformation of the 2016 MW 6.2 Lampa Earthquake, Southern Peru, Constrained by Interferometric Synthetic Aperture Radar

We use Sentinel‐1 radar imagery to explore the coseismic and postseismic surface displacements associated with the 2016 MW 6.2 Lampa earthquake in southern Peru. Based on coseismic interferograms, the preferred slip model links to a blind south southeast striking, south southwest dipping normal fault with a shallow dip (45.2°) and a peak slip of 0.71 m at depth ~5.3 km, which is consistent with seismic solutions. Postseismic interferograms, derived from two tracks of the Sentinel‐1A/B satellites using a small baseline subset method, show subsidence up to ~3 cm in the first year after the mainshock. The kinematic inversions of interferometric synthetic aperture radar (InSAR) observations imply that the postseismic surface displacements observed in 1 year after the earthquake are governed by afterslip occurring along the updip extension of the coseismic slip patches. To further improve the data fitting, we generate a fault with variable strike to refine the kinematic afterslip model. The stress‐driven afterslip forward modeling shows that the postseismic deformation is controlled by afterslip distributed at the edge of the compact coseismic slip area. The surface displacement predictions of the poroelastic rebound show subsidence of the hanging wall, but the magnitude of the displacements is small compared to the observed signal. We as well test a collection of viscoelastic relaxation models and find that the predicted surface displacements are not consistent with the observations. The InSAR results show that the strike of the seismogenic fault is quasi‐parallel to the Vilcanota normal fault system and both the fault associated with earthquake and Vilcanota normal fault dip in the same direction. Therefore, we suspect that the causative fault of this 2016 event may be a normal fault belonging to a “domino” faulting system.
amiB, a novel gene required for the growth/differentiation transition in Dictyostelium

The differentiation programme of Dictyostelium discoideum is initiated by starvation. Nutrient depletion triggers the differentiation of Dictyostelium cells through the transcriptional inactivation of some growth‐phase genes, as well as through the transcriptional activation of essential genes required for the aggregation of the cells. The adenylyl cyclase (ACA) gene, acaA, is one of the earliest genes expressed following starvation. ACA produces intracellular and extracellular cAMP that drives further differentiation by inducing chemotaxis, developmental gene expression and morphogenesis of Dictyostelium cells. Although several genes have been identified as being essential for the initiation of differentiation process, such as the transcriptional activation of ACA expression, the molecular mechanisms of the growth/differentiation transition remain to be explored.
Multiscale analysis of nitrogen adsorption and desorption isotherms in soils with contrasting pedogenesis and texture

Abstract. The specific surface area (SSA) of a soil is commonly estimated from adsorption isotherms determined in a limited range of relative pressures (p/p0), admitting a non fractal model. Nitrogen adsorption (NAI) and desorption (NDI) isotherms determined over the full range of p/p0 have been described using the multifractal approach. This study aimed to assess effects of soil texture on the multifractality of NAIs and NDIs, and to analyze the association between multifractal parameters and soil properties. Six soil profiles were taken to get two groups of samples with contrasting pedogenetic origin, texture (medium or clayey), susceptibility to water erosion and quality for agricultural uses. These two soil groups also were significant differences in SSA and cation exchange capacity (CEC), but not in organic matter content (OMC). Consistent with previous studies, the scaling properties of both NAIs and NDIs from all the soil horizons studied could be fitted reasonably well with multifractal models. Values of parameters D−5, D1, D2 and D5, extracted from the generalized dimension function, Dq, were higher for clayey soils during adsorption, but during desorption all of them were higher for medium textured soils. Therefore, the measure was more evenly distributed for clayey soils during adsorption and for medium textured soils during desorption. Width of Dq function given by parameter (D−5–D5) was significantly higher clayey soils for NAIs, but not significant differences were detected for NDIs; subsequently scaling heterogeneity of NAIs was higher for clayey than for medium textured soil. Differences in multifractal behaviour of NAIs and NDIs were consistent with a wider hysteresis loop of the medium texture soils compared to that of the clayey soils. Linear correlations were found between parameters D−5 and (D−5–D5) and clay content or SSA, which were positive and negative for NAIs and NDIs, respectively. Agronomical and environmental characterization of these soil groups with contrasting properties be enhanced by evaluating SSA and by inspecting NAIs and NDIs for multifractality.
Evidence Estimation for Bayesian Partially Observed MRFs

Bayesian estimation in Markov random fields is very hard due to the intractability of the partition function. The introduction of hidden units makes the situation even worse due to the presence of potentially very many modes in the posterior distribution. For the first time we propose a comprehensive procedure to address one of the Bayesian estimation problems, approximating the evidence of partially observed MRFs based on the Laplace approximation. We also introduce a number of approximate MCMC-based methods for comparison but find that the Laplace approximation significantly outperforms these.
Modeling Fixed Priority Non-Preemptive Scheduling with Real-Time Calculus

Modern real-time embedded systems are highly heterogeneous and distributed. As a result, compositional methods play an important role in the design and analysis of such complex systems. One such compositional analysis method is based on real-time calculus. In this paper, we present an analysis of fixed priority non-preemptive scheduling with the real-time calculus. Although fixed priority non-preemptive scheduling was modeled with the real-time calculus previously, we show that the model gives overly pessimistic results. We also compare our analysis with the existing holistic scheduling analysis through an example of a system using a controller area network (CAN) bus. The proposed method can be automated by incorporating it in the RTC toolbox.
Exploiting the Human Computational Effort Dedicated to Message Reply Formatting for Training Discursive Email Segmenters

In the context of multi-domain and multimodal online asynchronous discussion analysis, we propose an innovative strategy for manual annotation of dialog act (DA) segments. The process aims at supporting the analysis of messages in terms of DA. Our objective is to train a sequence labelling system to detect the segment boundaries. The originality of the proposed approach is to avoid manually annotating the training data and instead exploit the human computational efforts dedicated to message reply formatting when the writer replies to a message by inserting his response just after the quoted text appropriate to his intervention. We describe the approach, propose a new electronic mail corpus and report the evaluation of segmentation models we built.
Global Interactions in Random Field Models: A Potential Function Ensuring Connectedness

Markov random field (MRF) models, including conditional random field models, are popular in computer vision. However, in order to be computationally tractable, they are limited to incorporating only local interactions and cannot model global properties such as connectedness, which is a potentially useful high-level prior for object segmentation. In this work, we overcome this limitation by deriving a potential function that forces the output labeling to be connected and that can naturally be used in the framework of recent maximum a posteriori (MAP)-MRF linear program (LP) relaxations. Using techniques from polyhedral combinatorics, we show that a provably strong approximation to the MAP solution of the resulting MRF can still be found efficiently by solving a sequence of max-flow problems. The efficiency of the inference procedure also allows us to learn the parameters of an MRF with global connectivity potentials by means of a cutting plane algorithm. We experimentally evaluate our algorithm on both synthetic data and on the challenging image segmentation task of the PASCAL Visual Object Classes 2008 data set. We show that in both cases the addition of a connectedness prior significantly reduces the segmentation error.
Modelling Requirements for Content Recommendation Systems

This paper addresses the modelling of requirements for a content Recommendation System (RS) for Online Social Networks (OSNs). On OSNs, a user switches roles constantly between content generator and content receiver. The goals and softgoals are different when the user is generating a post, as opposed as replying to a post. In other words, the user is generating instances of different entities, depending on the role she has: a generator generates instances of a "post", while the receiver generates instances of a "reply". Therefore, we believe that when addressing Requirements Engineering (RE) for RS, it is necessary to distinguish these roles clearly. We aim to model an essential dynamic on OSN, namely that when a user creates (posts) content, other users can ignore that content, or themselves start generating new content in reply, or react to the initial posting. This dynamic is key to designing OSNs, because it influences how active users are, and how attractive the OSN is for existing, and to new users. We apply a well-known Goal Oriented RE (GORE) technique, namely i-star, and show that this language fails to capture this dynamic, and thus cannot be used alone to model the problem domain. Hence, in order to represent this dynamic, its relationships to other OSNs' requirements, and to capture all relevant information, we suggest using another modelling language, namely Petri Nets, on top of i-star for the modelling of the problem domain. We use Petri Nets because it is a tool that is used to simulate the dynamic and concurrent activities of a system and can be used by both practitioners and theoreticians.
Learning Systems of Concepts with an Infinite Relational Model

Relationships between concepts account for a large proportion of semantic knowledge. We present a nonparametric Bayesian model that discovers systems of related concepts. Given data involving several sets of entities, our model discovers the kinds of entities in each set and the relations between kinds that are possible or likely. We apply our approach to four problems: clustering objects and features, learning ontologies, discovering kinship systems, and discovering structure in political data.
Distributed autonomous multi-hop vehicle-to-vehicle communications over TV white space

This paper presents design and experimental evaluation of a distributed autonomous multi-hop vehicle-to-vehicle (V2V) communication system over TV white space performed in Japan. We propose the two-layer control channel model, which consists of the Zone Aware Control Channel (ZACC) and the Swarm Aware Control Channel (SACC), to establish the multi-hop network. Several vehicles construct a swarm using location and direction information shared through ZACC, and share route and channel information, and available white space information through SACC. To evaluate the system we carried out field experiments with swarm made of three vehicles in a convoy. As the test case application, the leading vehicle sends real-time speed and sudden break information to the rear vehicle, while the vehicle in between acts as the relay. The vehicles observe channel occupancy via energy detection and agree on the control and the data channels autonomously. For coarse synchronization of quiet periods for sensing we use GPS driven oscillators, and introduce a time margin to accommodate for remaining drift. When a primary user is detected in any of the borrowed channels, the vehicles switch to a vacant channel without disrupting the ongoing multi-hop communication. We present results of the experiments in terms of the time to establish control channel, channel switching time, and throughput.
Automatic Web News Content Extraction Based on Similar Pages

Today most news pages are generated from some underlying structured source, so we think that template-dependent wrappers should be more suitable for them than template-independent wrappers. In this paper, we propose a novel automatic template-dependent Web news content extraction approach based on similar pages. Firstly, We choose two similar pages as training samples and represent them as two HTML DOM trees. Secondly, we create the maximum matching tree between the DOM trees using our simple tree matching and backtracking algorithm. Then, by analyzing the characteristics of nodes in the maximum matching tree, we eliminate the noise nodes to generate an extraction template. Finally, we build a template-dependent wrapper for target news pages whose structures are similar to the samples. Experimental results indicate that our approach is effective and efficient for Web news content extraction, and the average harmonic mean of precision and recall reaches 98.3% .
Spectral Subspace Clustering for Graphs with Feature Vectors

Clustering graphs annotated with feature vectors has recently gained much attention. The goal is to detect groups of vertices that are densely connected in the graph as well as similar with respect to their feature values. While early approaches treated all dimensions of the feature space as equally important, more advanced techniques consider the varying relevance of dimensions for different groups. In this work, we propose a novel clustering method for graphs with feature vectors based on the principle of spectral clustering. Following the idea of subspace clustering, our method detects for each cluster an individual set of relevant features. Since spectral clustering is based on the eigendecomposition of the affinity matrix, which strongly depends on the choice of features, our method simultaneously learns the grouping of vertices and the affinity matrix. To tackle the fundamental challenge of comparing the clustering structures for different feature subsets, we define an objective function that is unbiased regarding the number of relevant features. We develop the algorithm SSCG and we show its application for multiple real-world datasets.
On-line Handwritten Character Recognition Selectively Employing Hierarchical Spatial Relationships among Subpatterns

This paper proposes an on-line handwritten character pattern recognition method that examines spatial relationships among subpatterns which are components of a character pattern. Conventional methods evaluating spatial relationships among subpatterns have not considered characteristics of deformed handwritings and evaluate all the spatial relationships equally. However, the deformations of spatial features are different within a character pattern. In our approach, we assume that the distortions of spatial features are dependent on the hierarchy of character patterns so that we selectively evaluate hierarchical spatial relationships of subpatterns by employing Bayesian network as a post-processor of our sub-stroke based HMM recognition system. Experiments on on-line handwritten Kanji character recognition with a lexicon of 1,016 elementary characters revealed that the approach we propose improves the recognition accuracy for different types of deformations.
Grammar-based Procedural Content Generation from Designer-provided Difficulty Curves

In experience-driven procedural content generation (EDPCG) [15], the challenge of (parts of) a level are often subject to player-adaptive optimisation. However, this may interfere with the design goals of the game designer with respect to the diculty build-up of the entire level, e.g., the designer may have specic ideas about where the climax of a level ought to be. This can be a reason for designers to not adopt experience-driven procedural techniques. In this paper we mitigate this, by meeting the designers half-way: the designers provide a set of allowed diculty curves for a level, and decide where the AI is allowed to switch between these, e.g., after each or certain segments or only between levels. This way, the designer is in control of the tension levels and ‘feel’ of the level, while still allowing player adaptivity. This paper describes how to generate level(s) (segments) using diculty curves, and how this can be applied to experience-driven procedural content generation. Experiments that validate our approach in an actual, open-source action-adventure game, reveal that it is consistently able to generate entire game levels that closely approximate distinct diculty curves. Also, the adopted generative grammar approach ensures that the generated content will never be unplayable, as it results strictly from (presumably adequate) designer-provided grammars. Finally, the obtained experimental results show that the procedural generation of game levels consistently takes place in a reasonably computationally ecient manner. Given these obtained results, we conclude that our enhanced procedural approach provides an eective basis for generating game levels according to designer specications, yielding new options for PCG.
Power-Constrained Secrecy Rate Maximization for Joint Relay and Jammer Selection Assisted Wireless Networks

In this paper, we examine the physical layer security for cooperative wireless networks with multiple intermediate nodes, where the decode-and-forward protocol is considered. We propose a new joint relay and jammer selection (JRJS) scheme for protecting wireless communications against eavesdropping, where an intermediate node is selected as the relay for the sake of forwarding the source signal to the destination and meanwhile, the remaining intermediate nodes are employed to act as friendly jammers, which broadcast the artificial noise for disturbing the eavesdropper. We further investigate the power allocation among the source, relay and friendly jammers for maximizing the secrecy rate of proposed JRJS scheme, and derive a closed-form sub-optimal solution. Specifically, all the intermediate nodes, which successfully decode the source signal, are considered as relay candidates. For each candidate, we derive the sub-optimal closed-form power allocation solution and obtain the secrecy rate result of the corresponding JRJS scheme. Then, the candidate, which is capable of achieving the highest secrecy rate, is selected as the relay. Two assumptions about the channel state information (CSI), namely the full CSI (FCSI) and partial CSI (PCSI), are considered. Simulation results show that the proposed JRJS scheme outperforms the conventional pure relay selection, pure jamming, and generalized singular-value-decomposition-based beamforming schemes in terms of secrecy rate. Additionally, the proposed FCSI-based power allocation and PCSI-based power allocation schemes both achieve higher secrecy rates than the equal power allocation scheme.
The Social Life of Psychiatric Practice: Trauma in Postwar Kosova

This article traces the social life of psychiatric practice in the context of war and postwar societies. It is argued that although psychiatric knowledge and practice is situated and grounded in particular cultural, social, and political contexts, it is important to examine how transnational networks situate local systems of meaning in much larger settings. I illustrate this claim by examining discourses and observations concerning health-seeking behaviors of Kosovar Albanian women and ways in which Kosovar health practitioners help them by employing, adapting, and changing the psychiatric tools and lessons learned during (trauma) training provided by international health professionals during the Yugoslav war and postwar eras. Thereby, I hope to contribute to a better understanding of how local health beliefs and practices are nested in the processes involved in international health policymaking and, thereby, relate to higher level structures such as international political economy, regional history, and development ideology.
FE modelling of phenolic resin impregnated aramid paper adopted in foldcore sandwich cores

The adaption and validation of an elastic-damage material model for aramid paper used in foldcore structures is presented. Aramid paper structures under compression fail in a complex buckling mode combined with face cracking at the buckle peaks. The constitutive modelling was adapted to shell elements in the explicit solver PAMCRASH with consideration of this particular compressive behaviour. The model was compared to test data of tensile tests, cylinder crushing tests and different loads on foldcore structures. The numerical results showed consistency with the experimental data in particular during foldcore collapse. However the material model slightly underestimated the foldcore residual strength in case of foldcore compaction.
Baseline Assessment of Petroleum Contamination and Soil Properties at Contaminated Sites in Utqiagvik, Alaska

Abstract : Elevated contamination levels persisted for decades at the former Naval Arctic Research Station at two sites in particular, the Airstrip and Powerhouse sites. Because of the challenging environmental conditions at these sites, physical and chemical remediation technologies have not been effective at reducing petroleum contamination levels. Therefore, the continued presence of the contamination warranted a deeper investigation of petroleum chemistry, soil attributes, and biological activity at these sites. Petroleum chemistry analysis revealed the heterogeneous contamination at each site, with higher levels observed at the upgradient sites, which were situated further from the nearby freshwater Imikpuk Lake. Additionally, soil biological data tests showed an active microbial community, including high bacterial numbers in these soils. The results from this baseline study indicate that stimulating biodegradation processes in petroleum-contaminated soils is a promising technology for bioremediation.