Miracle-dz/UniFAR-FTUs huggingface dataset:
Evolutionary Analysis of Genes for S-RNase-based Self-incompatibility Reveals S Locus Duplications in the Ancestral Rosaceae

Flowering plants have developed a genetically determined self-incompatibility (SI) system to maintain genetic diversity within a species. The Solanaceae, the Rosaceae, and the Plantaginaceae have the S-RNase-based gametophytic SI (GSI) system, which uses S-RNase and F-box proteins as the pistil S and pollen S determinants, respectively. SI is associated with culture and breeding difficulties in rosaceous fruit trees, such as apple, pear, and stone fruit species; therefore, researchers in the pomology field have long studied the mechanism and genetics of SI in order to obtain clues to overcome these difficulties. Here, we investigated the evolutionary paths of the S-RNase genes by tracking their duplication patterns. Phylogenetic analysis and estimation of proxy ages for the establishment of S-RNase and its homologs in several rosaceous species showed that the divergence of S-RNase in the subtribe Malinae and the genus Prunus predated the gene in most recent common ancestors of Rosaceae species. Furthermore, the duplicated S-RNase-like genes were accompanied by duplicated pollen S-like F-box genes, suggesting segmental duplications of the S locus. Analysis of the expression patterns and evolutionary speeds of duplicated S-RNase-like genes in Prunus suggested that these genes have lost the SI recognition function, resulting in a single S locus. Furthermore, the S loci in the current Rosaceae species might have evolved independently from the duplicated S loci, which could explain the presence of genus-specific SI recognition mechanisms in the Rosaceae. The results of the present study should be valuable for the future development of artificial SI control and for self-compatible breeding in rosaceous horticultural plant species.
Automating test oracles generation

Software systems play a more and more important role in our everyday life. Many relevant human activities nowadays involve the execution of a piece of software. Software has to be reliable to deliver the expected behavior, and assessing the quality of software is of primary importance to reduce the risk of runtime errors. Software testing is the most common quality assessing technique for software. Testing consists in running the system under test (SUT) on a finite set of inputs, and checking the correctness of the results. Thoroughly testing a software system is expensive and requires a lot of manual work to define test inputs (stimuli used to trigger different software behaviors) and test oracles (the decision procedures checking the correctness of the results). Researchers have addressed the cost of testing by proposing techniques to automatically generate test inputs. While the generation of test inputs is well supported, there is no way to generate cost-effective test oracles: Existing techniques to produce test oracles are either too expensive to be applied in practice, or produce oracles with limited effectiveness that can only identify blatant failures like system crashes. Our intuition is that cost-effective test oracles can be generated using information produced as a byproduct of the normal development activities. The goal of this thesis is to create test oracles that can detect faults leading to semantic and non-trivial errors, and that are characterized by a reasonable generation cost. We propose two ways to generate test oracles, one derives oracles from the software redundancy and the other from the natural language comments that document the source code of software systems. We present a technique that exploits redundant sequences of method calls encoding the software redundancy to automatically generate test oracles named cross-checking oracles (CCOracles). We describe how CCOracles are automatically generated, deployed, and executed. We prove the effectiveness of CCOracles by measuring their fault-finding effectiveness when combined with both automatically generated and hand-written test inputs. We also present Toradocu, a technique that derives executable specifications from Javadoc comments of Java constructors and methods. From such specifications, Toradocu generates test oracles that are then deployed into existing test suites to assess the outputs of given test inputs. We empirically evaluate Toradocu, showing that Toradocu accurately translates Javadoc comments into procedure specifications. We also show that Toradocu oracles effectively identify semantic faults in the SUT. CCOracles and Toradocu oracles stem from independent information sources and are complementary in the sense that they check different aspects of the SUTs.
Effectiveness of classification approach in recovering pairwise causal relations from data.

Causal structure discovery is a much-studied topic and a fundamental problem in Machine Learning. Causal inference is the process of recovering cause-effect relationships between the variables in a dataset. In general, causal inference problem is to decide whether X causes Y, Y causes X, or there exists an indirect relationship between X and Y via a confounder. Even under very stringent assumptions, causal structure discovery problems are challenging. Much work has been done on causal discovery methods with two variables in recent years. This thesis extends the bivariate case to the possibility of having at least one confounder between X and Y. Attempts have been made to extend the causal inference process to recover the structure of Bayesian networks from data. The contributions of this thesis include (a) extending causal discovery methods to the networks with exactly one confounder (third variable) ; (b) an algorithm to recover the causal graph between every pair of variables with the presence of a confounder in a large dataset; (c) employing a search algorithm to find the best Bayesian network structure that fits the data . Improved results have been achieved after the introduction of confounders in the bivariate causal graphs. Further attempts have been made to improve the Bayesian network scores for the network structures of some medium to large-sized networks using the standard ordering based search algorithms such as OBS and WINASOBS. Performance of the methods proposed have been tested on the benchmark datasets for cause-effect pairs and from the BLIP library.
Motivated Learning in Human-Machine Improvisation

This paper describes a machine learning approach in the context of non-idiomatic human-machine improvisation. In an attempt to avoid explicit mapping of user actions to machine responses, an experimental machine learning strategy is suggested where rewards are derived from the implied motivation of the human interactor – two motivations are at work: integration (aiming to connect with machine generated material) and expression (independent activity). By tracking consecutive changes in musical distance (i.e. melodic similarity) between human and machine, such motivations can be inferred. A variation of Q-learning is used featuring a self-optimizing variable length state-action-reward list. The system (called Pock) is tunable into particular behavioral niches by means of a limited number of parameters. Pock is designed as a recursive structure and behaves as a complex dynamical system. When tracking systems variables over time, emergent non-trivial patterns reveal experimental evidence of attractors demonstrating successful adaptation.
Variation in the DRD2 gene affects impulsivity in intertemporal choice

Introduction: Impulsivity in intertemporal choice has been operationalized as “delay discounting,” referring to the preference for a sooner, smaller reward in neuroeconomics. It is reportedly associated with the dopaminergic systems. Dopamine receptor D2 (DRD2) is the D2 subtype of the dopamine receptor of the G-protein coupled receptor family. The aim of this study was to explore the effect of single nucleotide polymorphisms (SNPs) in DRD2 gene on delay discounting. Methods: The participants consisted of 91 healthy Japanese people (66 males and 25 females with a mean age of 40.9 ± 6.9 years). Each participant completed the Kirby’s monetary choice questionnaire (MCQ) for delayed gain and donated a whole blood sample. Two SNPs (C957T (rs6277) and TaqI A (rs1800497)) in DRD2 were genotyped by using the DigiTag2 assay. SNP linear regression analyses with 100,000 permutations were conducted for the hyperbolic time-discount rate (k). Results: The SNP C957T showed a significant association; participants with more minor alleles (T) were more impulsive in intertemporal choice for delayed gain (multiplicity-corrected P = 0.041 with a small effect size). Conclusion: The variation in the DRD2 gene is associated with impulsive decision-making. This is the first study to demonstrate an association between DRD2 and impulsivity in intertemporal choice with a multiplicity-corrected significance.
Breeding and Cereal Yield Progress

This paper reviews recent progress in wheat (Triticum aestivum L.), rice (Oryza sativa L.), and maize (Zea mays L.) yields resulting from substantial breeding efforts in mostly favorable environments and examines its physiological basis. Breeding and improved agronomy lift potential yield (PY), namely yield with the best variety and management in the absence of manageable abiotic and biotic stresses, and PY increase is a key component of progress in farm yield (FY), the other component being closure of the PY to FY gap. Changes in PY and FY are reviewed for several key production regions, namely the United Kingdom and the Yaqui Valley of Mexico for wheat, Japan and Central Luzon in the Philippines for rice, and Iowa and briefl y sub-Saharan Africa for maize. The PY growth rates have fallen and are currently generally no more than 1% per annum and usually much less. The trajectory of FY with time often closely parallels PY, but, especially in developing countries, there remain large yield gaps. In at least one instance (maize in Iowa) the gap between PY and FY appears to be closing rapidly. Current genetic progress is linked to increased biomass accumulation, and this will remain the way forward in the future given the limits to increased harvest index (HI). There is evidence that recent progress is related to increased photosynthesis (e.g., greater radiation use effi ciency (RUE) at the canopy level and/or maximum photosynthetic rate P max at saturating irradiance at the leaf level) before and around anthesis. There is no theoretical reason why this trend cannot continue, especially given the vast genetic resources already found within each crop species. However, it will not be easily or cheaply accomplished, so prospects for higher rates of potential yield growth appear to be limited, notwithstanding new molecular tools and claims to the contrary. Closing the yield gap, therefore, becomes more important. Many factors are involved, but breeding can also help farmers achieve this through, for example, improved host plant resistance.
robotcowboy: 10 Years of Wearable Computer Rock

This paper covers the technical and aesthetic development of robotcowboy, the author’s ongoing human-computer wearable performance project. Conceived as an idiosyncratic manifesto on the embodiment of computational sound, the original robotcowboy system was built in 2006-2007 using an belt-mounted industrial wearable computer running GNU/ Linux and Pure Data, external stereo USB audio/MIDI interfaces, HID gamepads, and guitar. Influenced by roadworthy analog gear, chief system requirements were mobility, plug-and-play, reliability, and low cost. From 2007 to 2011, this first iteration “Cabled Madness” melded rock music with realtime algorithmic composition and revolved around cyborg human/system tension, aspects of improvisation, audience feedback, and an inherent capability of failure. The second iteration “Onward to Mars” explored storytelling from 2012-2015 through the one-way journey of the first human on Mars with the computing system adapted into a self-contained spacesuit backpack. Now 10 years on, a new “robotcowboy 2.0” system powers a third iteration with only an iPhone and PdParty, the author’s open-source iOS application which runs Pure Data patches and provides full duplex stereo audio, MIDI, HID game controller support, and Open Sound Control communication. The future is bright, do you have room to wiggle?
An Inf-Convolution BV type model for dynamic reconstruction

We are interested in a spatial temporal variational model for image sequences. The model involves a fitting data term to be adapted to different modalities such as denoising, debluring or emission tomography. The regularizing term acts as an infimal-convolution type operator that takes into account the respective influence of time and space variables. We give existence and uniqueness results and provide optimality conditions via duality analysis. In a forthcoming paper, see [5], we deal with the numerical realisation of the proposed model and focus on dynamic Positron Emission Tomography (PET) reconstruction. 1. Introduction. In this paper, we are interested in describing a variational model for denoising/debluring and/or emission tomography (ET) reconstruction of vector-valued images. What we call vector-valued images are usually color images, muti-spectral images, images acquired at different time intervals as videos. We focus on dynamic medical imaging as PET or functional MR images. There are many methods that handle videos or dyna-mical processes and the majority of them focus on the numerics. Here we aim to describe a variational model in an infinite dimensional setting, which, to our knowledge, has not been done yet. In a the dynamical setting, spatial and temporal components contribute differently, therefore we proceed with a non global description for both of them. Though, we have in mind a specific application to dynamic PET, we present a model flexible enough to address many applications. We cannot quote the numerous papers on videos, since there is a huge literature, even if we restrict ourselves to variational methods. Let us mention however the paper by Holler and Kunisch [15], where the authors consider the model we investigate in a semi-discrete setting. In addition, for dynamical PET applications, an active contour method with gradient vector flow has been developped in [17, 18] but the underlying variational model has not been explored. In this work, we do not address numerical issues since our concern is purely theoretical: we aim to describe a powerful variational model and perform mathematical analysis (well-posedness and optimality conditions). We will present numerical tests together with comparison with classical semi-discrete models/methods in the PET context in a forthcoming paper [5]. Let us denote u : (0, T) × Ω → R, the dynamic image with respect to the space domain Ω ⊂ R d with d ≥ 1 and with T > 0. In the following, we write Q ⊂ R d+1 instead of (0, T) × Ω. We focus on variational methods applied on a spatial-temporal domain and more precisely we
Image Reconstruction when Encoding with Nonlinear Gradients

Introduction In recent years there has been considerable interest in moving away from the restriction that the imaging gradients must create a uniform gradient along each of the principal Cartesian axes (x, y and z). In the case of small deviations from these ‘ideal’ linear forms, images reconstructed which do not account for these nonlinearities will be distorted, but typically remain unaffected by additional reconstruction artefacts. Indeed, most manufacturers have some degree of distortion-correction ‘built-in’ to their standard reconstructions, as the true linearity of the imaging gradients will always deteriorate with increasing distance from isocenter.
Explicit Error Estimates for Courant, Crouzeix-Raviart and Raviart-Thomas Finite Element Methods

The elementary analysis of this paper presents explicit expressions of the constants in the a priori error estimates for the lowest-order Courant, Crouzeix-Raviart nonconforming and Raviart-Thomas mixed finite element methods in the Poisson model problem. The three constants and their dependences on some maximal angle in the triangulation are indeed all comparable and allow accurate a priori error control.
Saharan versus local influence on atmospheric aerosol deposition in the southern Iberian Peninsula: Significance for N and P inputs

A novel methodology was used to evaluate the contribution of Saharan dust to the atmospheric deposition of particulate material (PM), total phosphorus (TP), and total nitrogen (TN) in the southeastern Iberian Peninsula. Dry and wet aerosol depositions were measured weekly during two 1 year periods at one site and simultaneously during spring‐summer of the same years at two other sites (intersite distance of ~ 40 km). Statistical relationships among depositions at the different sites permitted differentiation of Saharan dust inputs from locally derived dust. PM and TP depositions were synchronous among the three study sites; the synchrony was elevated during periods of Saharan intrusions (evaluated by air mass retrotrajectories analyses), but no temporal correlation was observed during periods without Saharan intrusions. According to analysis of variance results, PM and TP depositions were both significantly affected by Saharan intrusions. During weeks with Saharan intrusions, PM deposition increased around 85% above background levels, with no differences among the three sites, while TP deposition increased by 1.1 µmol TP m−2 d−1, i.e., 29% to 81% above background levels depending on the site. There were no correlations or differences in TN deposition among sites or as a function of Saharan intrusion periods. The annual contribution of PM and TP from Saharan dust was 75 kg ha−1 and 0.07 kg P ha−1, respectively, which can be considered a genuine input for the ecosystems in this area. This novel approach is likely to be valid in any area in the world under atmospheric deposition of long‐range transported material.
LARS for reconstructing damaged intra-articular cruciate knee ligaments

The LARS (ligament augmentation and reconstruction system) is a synthetic scaffold indicated for the repair and reconstruction of damaged ligaments. Comparative studies show no statistically significant differences in the majority of outcomes for people undergoing LARS procedures compared with people treated with an autograft at a follow-up of 4 years. One study reported statistically significantly less laxity for LARs procedures. Each LARS costs £1391.
Swarm of UAVs: Search a Rescue Operationin Chaotic Ship Wakes

A person falling of a ship can be difficult to locate since the wake behind the ship forms achaotic field, making it extremely difficult to predict the location of the victim even if thetime when they fell overboard is known. Survivability for humans immersed at sea is verydependent on the time spent in the water, and varies significantly with sea temperature; thismakes it imperative that the victim is retrieved rapidly. Our current research is aimed atreducing this time using several UAV's searching the ships wake simultaneously, as a swarm.Since the wake is chaotic, a simulation was developed to model different random motions of avictim based on a chaotic equation. Our current research is making use of an establishedsimulator environment and developing it further to investigate how different platforms mayaffect rescue time, varying on the size of the ship, the weather conditions and whether thesearch is operated during day or night. Two different search strategies were implemented inthe developed simulator; these are Expanding Square search and Parallel search. An overallconclusion based on the results obtained is that the expanding square search tends to be amore rigid and reliable search strategy. Also the results show that for any scenario, the soughtperson is detected within minutes.
MR Physics for Physicists : Electromagnetic Fields in MRI : From Theory to Practice

This lecture will address the concept of magnetic susceptibility and its interaction with strong static magnetic fields the demagnetizing field. In the context of magnetic resonance imaging the demagnetizing field, depending on its strength and MR imaging parameters, can cause: image distortions, signal attenuation through intravoxel dephasing or variation of the voxel mean magnetic field that can be observed in the phase of gradient echo images. To benefit from this lecture it is important to be familiar with image formation and encoding using gradients as well as the basic Bloch Equation describing the signal evolution under a static magnetic field. The lecture will focus on the information observed in gradient echo phase images, and on the methods developed over recent years to (having measured local variations of the static magnetic field) recover the information from the underlying magnetic susceptibility. The lecture will also cover some of the lessons learned regarding the magnetic properties of tissues in the human brain using susceptibility mapping and some of the limitations of these techniques. At the end of the course the concept of demagnetizing fields should be clear and the potentials and pitfalls of quantitative susceptibility mapping should be understood.
The Labor Rights and the Impact on Equity Returns : A Cross-Country Analysis 1

There is ample evidence that financial market development leads to economic growth. If improving labor rights can be shown to positively influence equity markets, then that, in turn, will lead to economic growth. The finance literature has examined the impact of a broader metric, namely, the Economic Freedom Index, on equity returns worldwide and the evidence is mixed. This study focuses on one dimension of economic freedom: labor rights. Specifically, the study analyzes the impact of labor rights on national equity market indexes, using the Labor Rights Index developed by the Organization for Economic Co-operation and Development (OECD) and the Fraser Institute (FI). Using panel regression analysis for 49 countries (for the OECD Index) and 76 countries (for the FI Index) over the period 1985 through 2014, the study finds that changes in labor rights have a statistically significant positive impact on equity returns, after controlling for business-cycle effects and time fixed effects. The study also finds significant differences in the Labor-Rights-Equity Returns relationship between developed and less developed economies.