Miracle-dz/UniFAR-FTUs huggingface dataset:
Tales of the unexpected: Phylogeography of the arctic‐alpine model plant Saxifraga oppositifolia (Saxifragaceae) revisited

Arctic‐alpine biota occupy enormous areas in the Arctic and the northern hemisphere mountain ranges and have undergone major range shifts during their comparatively short history. The origins of individual arctic‐alpine species remain largely unknown. In the case of the Purple saxifrage, Saxifraga oppositifolia, an important model for arctic‐alpine plants, phylogeographic studies have remained inconclusive about early stages of the species’ spatiotemporal diversification but have provided evidence for long‐range colonization out of a presumed Beringian origin to cover today’s circumpolar range. We re‐evaluated the species’ large‐scale range dynamics based on a geographically extended sampling including crucial areas such as Central Asia and the (south‐)eastern European mountain ranges and employing up‐to‐date phylogeographic analyses of a plastid sequence data set and a more restricted AFLP data set. In accordance with previous studies, we detected two major plastid DNA lineages also reflected in AFLP divergence, suggesting a long and independent vicariant history. Although we were unable to determine the species’ area of origin, our results point to Europe (probably the Alps) and Central Asia, respectively, as the likely ancestral areas of the two main lineages. AFLP data suggested that contact areas between the two clades in the Carpathians, Northern Siberia and western Greenland were secondary. In marked contrast to high levels of diversity revealed in previous studies, populations from the major arctic refugium Beringia did not exhibit any plastid sequence polymorphism. Our study shows that adequate sampling of the southern, refugial populations is crucial for understanding the range dynamics of arctic‐alpine species.
Static Analysis of Two-Fingered Grips

In the paper a static analysis of two-fingered grips is presented. Importance of grasp analysis in human performance engineering and hand therapy is discussed and assessment methods are proposed. Two precision grips were examined in the study: nippers pinch and tip pinch. We have built a grip-measuring device assessing the endpoint forces of two-oppositional grips. The instrument developed is based on a robotic force-wrist sensor and designed to suit human fingers. Through the simultaneous use of an optical measuring system and the grip-measuring device, the finger positions and the grip force acting on the object were obtained. A static model of the hand was also developed. A recursive computational method was used to calculate the joint torques of the fingers from the measured coordinates and the endpoint force vector. The estimated joint torque corresponds to the amount of load on the tendon during isometric muscle contraction. The force output of the two grips considered is presented and compared in two healthy individuals. The calculated joint torques for the index finger and thumb are presented and the maximal values of the finger joint torques acquired in the study are shown.
Introducing domain-specific language implementation using web service-oriented technologies

Several advantages have been documented that suggest Domain-Specific Languages DSLs have the potential to improve productivity, reliability, maintainability and portability in some specialized domains. However, several key challenges still remain. In particular, the extension and evolution of both DSL syntax and semantics still suffer due to the limitations related to the current state-of-the-art implementation techniques. Such techniques also lack interoperable capabilities among base languages and limited tool support. As changes of domain concepts are omnipresent and more base languages may support DSL implementation, the aforementioned limitations may be no longer tolerable, and hence a new implementation technique to DSL development is desired. This paper implements six DSL case studies representing imperative, declarative and hybrid categories to validate the feasibility of utilizing Service-Oriented Architecture SOA for DSL implementation. Such case studies also highlight that the advantages of SOA i.e., ease of evolution/extension, interoperability and tool support can be retained under the context of DSL development. The paper concludes with the discussion of additional findings, both positive and negative: the SOA-based approach improves modularization at the lexical, syntactical and semantic levels and delegates tokenization/parsing to the underlying WS-BPEL engine; yet, the usability, resource utilization, security, and flexibility of the SOA-based DSLs are degraded, which requires more future work in this unique area that spans SOA and DSLs.
Biomarker discovery, high performance and cloud computing: A comprehensive review

The analysis of biological markers (biomarkers) have the ability to improve clinical outcomes of a disease through prediction and early detection. The constant improvement of next generation sequencing (NGS) technologies coupled with falling equipment price are driving research and application especially in the medical domain. NGS technology is being applied to cancer research promising greater understanding of carcinogenesis. However, as sequence capacity grows, algorithmic speed is becoming an important bottleneck. To understand these challenges we present a review on difficulties currently faced in discovering biomarkers. The review places the spotlight on sequencing technologies and the bottlenecks encountered in these pipelines. Cloud computing and high performance computing technologies such as Grid are summarized in tackling computational challenges presented by technologies and algorithms used in biomarker research.
Using REMBRANDT to Paint in the Details of Glioma Biology: Applications for Future Immunotherapy

Microarray technology developed in the late 1990’s allows one to simultaneously analyze the entire transcriptome of a given population of cells at a single time. It is essentially a microchip with each spot containing about a picogram of DNA immobilized at defined locations. This DNA captures mRNA or cDNA from defined cell populations (tissue, cell line, etc) in a quantitative manner. This technique allows complex patterns of global gene expressions to be quickly and easily detected between two specimens. Microarrays were initially used to describe cell cycle patterns of Saccharomyces cerevisiae [1]. Its powerful potential was quickly recognized and applied towards cancer. The first successful application of this technology was to show that diffuse large cell B lymphomas had two different subtypes. One subset of this cancer was easily treatable with chemotherapy; whereas, the second phenotype required a more aggressive therapy [2].
Procedures for solving spectral/hp stabilized incompressible flow problems

In this paper we implement the element-by-element preconditioner and inexact Newton-Krylov methods (developed in the past) for solving stabilized computational fluid dynamics (CFD) problems with spectral methods. Two different approaches are implemented for speeding up the process of solving both steady and unsteady incompressible Navier-Stokes equations. The first approach concerns the application of a scalable preconditioner namely the element by element LU preconditioner, while the second concerns the application of Newton-Krylov (NK) methods for solving non-linear problems. We obtain good agreement with benchmark results on standard CFD problems for various Reynolds numbers. We solve the Kovasznay flow and flow past a cylinder at Re-100 with this approach. We also utilize the Newton-Krylov algorithm to solve (in parallel) important model problems such as flow past a circular obstacle in a Newtonian flow field, three dimensional driven cavity, flow past a three dimensional cylinder with different immersion lengths. We explore the scalability and robustness of the formulations for both approaches and obtain very good speedup. Effective implementations of these procedures demonstrate for relatively coarse macro-meshes the power of higher order methods in obtaining highly accurate results in CFD. While the procedures adopted in the paper have been explored in the past the novelty lies with applications with higher order methods which have been known to be computationally intensive.
UUITP-19 / 06 T-duality and Generalized Complex Geometry

We find the explicit T-duality transformation in the phase space formulation of the N = (1, 1) sigma model. We also show that the T-duality transformation is a symplectomorphism and it is an element of O(d, d). Further, we find the explicit T-duality transformation of a generalized complex structure. We also show that the extended supersymmetry of the sigma model is preserved under the T-duality.
Neural correlates of grasping

Prehension, the capacity to reach and grasp objects, comprises two main components: reaching, i.e., moving the hand towards an object, and grasping, i.e., shaping the hand with respect to its properties. Knowledge of this topic has gained a huge advance in recent years, dramatically changing our view on how prehension is represented within the dorsal stream. While our understanding of the various nodes coding the grasp component is rapidly progressing, little is known of the integration between grasping and reaching. With this Mini Review we aim to provide an up-to-date overview of the recent developments on the coding of prehension. We will start with a description of the regions coding various aspects of grasping in humans and monkeys, delineating where it might be integrated with reaching. To gain insights into the causal role of these nodes in the coding of prehension, we will link this functional description to lesion studies. Finally, we will discuss future directions that might be promising to unveil new insights on the coding of prehension movements.
An Architectural Design of a Job Management System Leveraging Software Defined Network

Whether to be able to efficiently utilize the interconnect in a cluster system is a key factor in deciding the computational performance especially for a class of jobs that require intensive communications between processes. However, most of Job Management Systems (JMSs), which are deployed on cluster systems for load-balancing, do not have any mechanism that takes the pattern and requirements of communication occurred in a job into consideration, regardless of potential large impact on its performance. In this research, we explore a novel JMS that can assign computing resources to jobs submitted to the JMS from a standpoint of efficient use of both network and processor resource. More technically, in this paper, a JMS that integrates the network programming functionality of OpenFlow as Software Defined Network is proposed and discussed towards better and more efficient allocation of computing and network resources.
Deferrable Load Scheduling in a Stand-alone Power System with Renewable Energy Sources and a Perfect Battery

Renewable energy resources are environmentally friendly and have received a lot of attention lately. In this paper, we consider a stand-alone power system with renewable energy sources and a perfect battery. We assume that the loads to the system are deferrable so that they can be scheduled to balance the power supply and demand. The main objective of a scheduling policy in such a system is to effectively utilize renewable energy sources so that the loads can be served as quickly as possible and the amount of wasted energy can be minimized. For such a purpose, we consider three classes of scheduling policies: (i) no lookahead policies, (ii) 1-period lookahead policies, and (iii) 1-period prediction policies. By using a sample path argument, we prove a comparison theorem between a maximal 1-period lookahead policy and a maximal no lookahead policy. We also prove an invariant theorem for the battery capacity of a maximal 1-period lookahead policy. Our simulation results reveal two interesting findings: (i) increasing the battery capacity is very effective in improving the performance of a maximal no lookahead policy, and (ii) prediction can be very effective in improving the system performance without needing to increase battery capacity.
Performance Analysis of WMN-SA: Node Placement Problem Using Simulated Annealing Algorithm for Different Replacement Methods

In this work, we consider the replacement methods in WMN-SA simulation system for 4 different distributions of mesh clients. We want to find the optimal distribution of mesh router nodes in order to provide the best network connectivity and coverage in various distributed clients. We implemented a simulation system based on Simulated Annealing (SA) algorithm, called WMN-SA, to calculate the size of Giant Component (GC) and number of covered mesh clients (NCMC) with different instance of simulation size. The simulation results show that the performance depends on distribution of mesh clients. For Uniform distribution of mesh clients, the system achieves better results when the replacement method is Radius method. For Normal distribution of mesh clients, for the GC of 3 methods is almost the same except Random method. For NCMC, Swap method is good when the distribution of mesh clients is Normal. For Exponential distribution, the best performance is achieved for Radius method. For Weibull distribution of mesh clients, the best performance is achieved for Combination method.
Imagine All the Plants: Evaluation of a Light-Field Camera for On-Site Crop Growth Monitoring

The desire to obtain a better understanding of ecosystems and process dynamics in nature accentuates the need for observing these processes in higher temporal and spatial resolutions. Linked to this, the measurement of changes in the external structure and phytomorphology of plants is of particular interest. In the fields of environmental research and agriculture, an inexpensive and field-applicable on-site imaging technique to derive three-dimensional information about plants and vegetation would represent a considerable improvement upon existing monitoring strategies. This is particularly true for the monitoring of plant growth dynamics, due to the often cited lack of morphological information. To this end, an innovative low-cost light-field camera, the Lytro LF (Light-Field), was evaluated in a long-term field experiment. The experiment showed that the camera is suitable for monitoring plant growth dynamics and plant traits while being immune to ambient conditions. This represents a decisive contribution for a variety of monitoring and modeling applications, as well as for the validation of remote sensing data. This strongly confirms and endorses the assumption that the light-field camera presented in this study has the potential to be a light-weight and easy to use measurement tool for on-site environmental monitoring and remote sensing purposes.
Generalized Non-Orthogonal Joint Diagonalization With LU Decomposition and Successive Rotations

Non-orthogonal joint diagonalization (NJD) free of prewhitening has been widely studied in the context of blind source separation (BSS) and array signal processing, etc. However, NJD is used to retrieve the jointly diagonalizable structure for a single set of target matrices which are mostly formulized with a single dataset, and thus is insufficient to handle multiple datasets with inter-set dependences, a scenario often encountered in joint BSS (J-BSS) applications. As such, we present a generalized NJD (GNJD) algorithm to simultaneously perform asymmetric NJD upon multiple sets of target matrices with mutually linked loading matrices, by using LU decomposition and successive rotations, to enable J-BSS over multiple datasets with indication/exploitation of their mutual dependences. Experiments with synthetic and real-world datasets are provided to illustrate the performance of the proposed algorithm.
Phase transition of the largest eigenvalue for nonnull complex sample covariance matrices

AbstractWe compute the limiting distributions of the largest eigenvalue of a complex Gaussian samplecovariance matrix when both the number of samples and the number of variables in each samplebecome large. When all but ﬁnitely many, say r, eigenvalues of the covariance matrix arethe same, the dependence of the limiting distribution of the largest eigenvalue of the samplecovariance matrix on those distinguished r eigenvalues of the covariance matrix is completelycharacterized in terms of an inﬁnite sequence of new distribution functions that generalizethe Tracy-Widom distributions of the random matrix theory. Especially a phase transitionphenomena is observed. Our results also apply to a last passage percolation model and aqueuing model. 1 Introduction Consider M independent, identically distributed samples y 1 ,. ,~y M , all of which are N ×1 columnvectors. We further assume that the sample vectors ~y k are Gaussian with mean µ and covarianceΣ, where Σ is a ﬁxed N ×N positive matrix; the density of a sample ~y isp(~y) =1(2π)
An XMM-Newton study of the environments, particle content and impact of low-power radio galaxies

We present a detailed study of the environments of a sample of nine low-power (Fanaroff & Riley type I) radio galaxies, based on new and archival XMM-Newtonobservations. We report new detections of group-scale environments around three radio galaxies, 3C 296, NGC 1044 and 3C 76.1. As with previous studies, we find that FR- I radio galaxies inhabit group environments ranging over nearly two orders of magnitude in bolometric X-ray luminosity; however, we find no evidence for a tight relationship between large-scale X-ray environment and radio-source properties such as size, radio luminosity, and axial ratio. This leads us to conclude that radio-source evolution cannot be determined entirely by the global properties of the hot gas. We confirm earlier work showing that equ ipartition internal pressures are typically lower than the external pressures acting on the ra dio lobes, so that additional nonradiating particles must be present or the lobes must be magnetically dominated. We present the first direct observational evidence that entrainment ma y provide this missing pressure, in the form of a relationship between radio-source structure and apparent pressure imbalance. Finally, our study provides further support for the presenc e of an apparent temperature excess in radio-loud groups compared to the group population as a whole. For five of eight temperature excesses, the energy required to inflate the radio l obes is comparable to the energy required to produce this excess by heating of the group gas; however, in three cases the current radio source appears too weak to produce the temperature excess. It remains unclear whether the temperature excess can be directly associated with the current phase of AGN activity, or whether it is instead either a signature of previous AGN activity or simply an indicator of the particular set of group properties most conducive to the growth of an FR-I radio galaxy.
Tag-Aware Spectral Clustering of Music Items

Socialtaggingis anincreasingly popularphenomenon with substantial impact on Music Information Retrieval (MIR). Tags express the personal perspectives of the user on the music items (such as songs, artists, or albums) they tagged. These personal perspectives should be taken into account inMIRtasksthatassessthesimilaritybetweenmusicitems. In this paper, we propose an novel approach for clustering music items represented in social tagging systems. Its characteristic is that it determines similarity between items by preserving the 3-way relationships among the inherent dimensions of the data, i.e., users, items, and tags. Conversely to existing approaches that use reductions to 2way relationships (between items-users or items-tags), this characteristic allows the proposed algorithm to consider the personal perspectives of tags and to improve the clustering quality. Due to the complexity of social tagging data, we focus on spectral clustering that has been proven effective in addressing complex data. However, existing spectral clustering algorithms work with 2-way relationships. To overcome this problem, we develop a novel data-modeling scheme and a tag-aware spectral clustering procedure that uses tensors (high-dimensional arrays) to store the multigraph structures that capture the personalised aspects of similarity. Experimental results with data from Last.fm indicate the superiority of the proposed method in terms of clustering quality over conventional spectral clustering approaches that consider only 2-way relationships.
Domain-Speci(cid:12)c Synonym Expansion and Validation for Biomedical Information Retrieval (MultiText Experiments for TREC 2004)

In the domain of biomedical publications, synonyms and homonyms are omnipresent and pose a great challenge for document retrieval systems. For this year’s TREC Genomics Ad hoc Retrieval Task, we mainly addressed the problem of dealing with synonyms. We examined the impact of domain-speci(cid:12)c knowledge on the e(cid:11)ectiveness of query expansion and analyzed the quality of Google as a source of query expansion terms based on pseudo-relevance feedback. Our results show that automatic acronym expansion, realized by querying the AcroMed database of biomedical acronyms, almost always improves the performance of our document retrieval system. Google, on the other hand, produced results that were worse than the other, corpus-based feedback techniques we used as well in our experiments. We believe that the primary reason for Google’s bad performance in this task is its highly restricted query language.
Worst-Case Execution Time Test Generation for Augmenting Path Maximum Flow Algorithms Using Genetic Algorithms

Worst-case execution time tests can be tricky to create for various computer science algorithms. To reduce the amount of human effort, authors suggest using search-based optimization techniques, such as genetic algorithms. This paper addresses difficult test generation for several maximum flow algorithms from the augmenting path family. The presented results show that the genetic approach is reasonably good for the well-studied algorithms and superior for the capacity scaling algorithms. Moreover, tests which are generated against one algorithm seem to be hard for other algorithms of this family.
An SDN-based architecture for Network-as-a-Service

Network-as-a-Service (NaaS) is a cloud-based service model that offers on-demand network connectivity and the provisioning and management of network services. However, the actual orchestration of dynamically allocating underlying resources to customer requirements is not trivial. In this paper, we propose an SDN-based approach to support the NaaS model. We implement a proof-of-concept (PoC) on a physical testbed and validate it through experimental performance evaluation.