Miracle-dz/UniFAR-FTUs huggingface dataset:
Metabolic profiling of two maize (Zea mays L.) inbred lines inoculated with the nitrogen fixing plant-interacting bacteria Herbaspirillum seropedicae and Azospirillum brasilense

Maize roots can be colonized by free-living atmospheric nitrogen (N2)-fixing bacteria (diazotrophs). However, the agronomic potential of non-symbiotic N2-fixation in such an economically important species as maize, has still not been fully exploited. A preliminary approach to improve our understanding of the mechanisms controlling the establishment of such N2-fixing associations has been developed, using two maize inbred lines exhibiting different physiological characteristics. The bacterial-plant interaction has been characterized by means of a metabolomic approach. Two established model strains of Nif+ diazotrophic bacteria, Herbaspirillum seropedicae and Azospirillum brasilense and their Nif- couterparts defficient in nitrogenase activity, were used to evaluate the impact of the bacterial inoculation and of N2 fixation on the root and leaf metabolic profiles. The two N2-fixing bacteria have been used to inoculate two genetically distant maize lines (FV252 and FV2), already characterized for their contrasting physiological properties. Using a well-controlled gnotobiotic experimental system that allows inoculation of maize plants with the two diazotrophs in a N-free medium, we demonstrated that both maize lines were efficiently colonized by the two bacterial species. We also showed that in the early stages of plant development, both bacterial strains were able to reduce acetylene, suggesting that they contain functional nitrogenase activity and are able to efficiently fix atmospheric N2 (Fix+). The metabolomic approach allowed the identification of metabolites in the two maize lines that were representative of the N2 fixing plant-bacterial interaction, these included mannitol and to a lesser extend trehalose and isocitrate. Whilst other metabolites such as asparagine, although only exhibiting a small increase in maize roots following bacterial infection, were specific for the two Fix+ bacterial strains, in comparison to their Fix- counterparts. Moreover, a number of metabolites exhibited a maize-genotype specific pattern of accumulation, suggesting that the highly diverse maize genetic resources could be further exploited in terms of beneficial plant-bacterial interactions for optimizing maize growth, with reduced N fertilization inputs.
Discovering Topical Experts in Twitter Social Network

Finding topic experts on microblogging sites with millions of users, such as Twitter, is a hard and challenging problem. In this thesis, we propose and investigate a new methodology for inferring topical experts in the popular Twitter social network. Our methodology relies on the wisdom of the Twitter crowds – it leverages Twitter Lists, which are often carefully created by individual users to include experts on topics that interest them and whose meta-data (List names and descriptions) provide valuable semantic cues to experts’ domain of expertise. We mined List information to build Cognos, an expert search system for Twitter. Detailed experimental evaluation based on a real-world deployment shows that: (a) Cognos infers a user’s expertise more accurately and comprehensively than state-of-the-art systems that rely on the user’s bio or tweet content, (b) Cognos scales well due to built-in mechanisms to efficiently update its experts’ database with new users, and (c) Despite relying only on a single feature, namely crowdsourced Lists, Cognos yields comparable, if not better, results in user tests, as compared to the official Twitter experts search engine for a wide range of queries. Our study highlights Lists as a potentially valuable source of information for future content or expert search systems in Twitter.
Upper body tracking for human-machine interaction with a moving camera

This research presents an upper body tracking method with a monocular camera. The human model is defined in a high dimensional state space. We hereby propose a hierarchical structure model to solve the tracking problem by SIR (Sampling Importance Resampling) particle filter with partitioned sampling. The image spatial and temporal information is used to track the human body and estimate the human posture. When doing the human-machine interaction, a static monocular camera may not get plenty of information from 2D images, so we must move the camera platform to a better position for acquiring more enriched image information. The proposed upper body tracking technique will then adjust to estimating the human posture during the camera moving. To validate the effectiveness of the proposed tracking approach, extensive experiments have been performed, of which the result appear to be quite promising.
A cooperative jamming protocol for physical layer security in wireless networks

A cooperative jamming protocol is studied in this paper and its ability to protect the communications of a pair of users in the presence of an eavesdropper. Communication of users is assisted by many helping interferers, assuming knowledge of channel state information. Closed form expressions are given for the optimal weights and power allocation maximizing the difference in the SNR between destination and eavesdropper; these are determined under transmit, reliability, and security constraints. Simulations show that noticeable improvements, of more than 30dB, may be attained in the SNR difference compared to the non-cooperative case.
On the evaluation of recommender systems with recorded interactions

Recommender systems are Integrated Development Environment (IDE) extensions which assist developers in the task of coding. However, since they assist specific aspects of the general activity of programming, their impact is hard to assess. In previous work, we used with success an evaluation strategy using automated benchmarks to automatically and precisely evaluate several recommender systems, based on recording and replaying developer interactions. In this paper, we highlight the challenges we expect to encounter while applying this approach to other recommender systems.
Reproducing Kernel Banach Spaces with the ℓ1 Norm II: Error Analysis for Regularized Least Square Regression

A typical approach in estimating the learning rate of a regularized learning scheme is to bound the approximation error by the sum of the sampling error, the hypothesis error, and the regularization error. Using a reproducing kernel space that satisfies the linear representer theorem brings the advantage of discarding the hypothesis error from the sum automatically. Following this direction, we illustrate how reproducing kernel Banach spaces with the ℓ1 norm can be applied to improve the learning rate estimate of ℓ1-regularization in machine learning.
Teacher reform in Indonesia: can offshore programs create lasting pedagogical shift?

ABSTRACT Regional and national interest in reforming teaching in Indonesia has seen governments, NGOs and education specialists combine to drive pedagogical changes among school teachers there. Results of these programs have been indifferent at best. This paper reports on teacher reform programs in Provinsi Papua, one of the most marginal societies in Indonesia. The Papuan Provincial Government, AusAID and an Australian University focused on bringing cohorts of secondary teachers and Principals for professional development to Australia. An evaluative, survey inquiry was conducted into the effectiveness of a series of AusAID (now DFAT Australian Aid) Scholarship programs on changing capacities and approaches of teachers and Principals at least eighteen months after their off-shore experience. Findings revealed significant changes in teaching practices, improved quality of teacher-student relationships and improved interactions with colleagues. We argue that our findings demonstrate an appetite for student-centred approaches to teaching and that off-shore programs may have important outcomes that larger scale, in-country programs fail to realise. This has implications for DFAT Australian Aid-funded and similar Scholarship programs.
Model transformation generation a survey of the state-of-the-art

In the Model Driven Engineering (MDE), a model transformation occupies a very important place that it defines the automatic passing from one model to another. To generate this latter, several works are proposed, for example the model transformation by example (MTBE) and generation of metamodel-based model transformation (GMBMT). In this paper, we present an exhaustive review of the literature on the generation for model transformations. We also take the definition of different aspects that could be used to generate a model transformation and show how this can be done. Finally, we discuss the need of an endogenous or/and exogenous example for testing the model transformation generation.
Robust Design for Amplify-and-Forward MIMO Relay Systems With Direct Link and Imperfect Channel Information

In this paper, we propose statistically robust design for multiple-input multiple-output (MIMO) relay systems with the direct source-destination link and imperfect channel state information (CSI). The minimum mean-squared error (MMSE) of the signal waveform estimation at the destination node is adopted as the design criterion. We develop two iterative methods to solve the nonconvex joint source, relay, and receiver optimization problem. In particular, we derive the structure of the optimal relay precoding matrix and show the effect of CSI mismatch on the structure of the optimal robust source and relay matrices. The proposed algorithms generalize the transceiver design of MIMO relay systems with the direct link to the practical scenario of imperfect CSI knowledge. Simulation results demonstrate an improved performance of the proposed algorithms with respect to the conventional methods at various levels of CSI mismatch.
Pricing and Hedging Contingent Claims with Liquidity Costs and Market Impact

We study the influence of taking liquidity costs and market impact into account when hedging a contingent claim, first in the discrete time setting, then in continuous time. In the latter case and in a complete market, we derive a fully non-linear pricing partial differential equation, and characterizes its parabolic nature according to the value of a numerical parameter naturally interpreted as a relaxation coefficient for market impact. We then investigate the more challenging case of stochastic volatility models, and prove the parabolicity of the pricing equation in a particular case.
Unifying Textual and Visual Cues for Content-Based Image Retrieval on the World Wide Web

A system is proposed that combines textual and visual statistics in a single index vector for content-based search of a WWW image database. Textual statistics are captured in vector form using latent semantic indexing based on text in the containing HTML document. Visual statistics are captured in vector form using color and orientation histograms. By using an integrated approach, it becomes possible to take advantage of possible statistical couplings between the content of the document (latent semantic content) and the contents of images (visual statistics). The combined approach allows improved performance in conducting content-based search. Search performance experiments are reported for a database containing 350,000 images collected from the WWW.
Processing changes when listening to foreign-accented speech

This study investigates the mechanisms responsible for fast changes in processing foreign-accented speech. Event Related brain Potentials (ERPs) were obtained while native speakers of Spanish listened to native and foreign-accented speakers of Spanish. We observed a less positive P200 component for foreign-accented speech relative to native speech comprehension. This suggests that the extraction of spectral information and other important acoustic features was hampered during foreign-accented speech comprehension. However, the amplitude of the N400 component for foreign-accented speech comprehension decreased across the experiment, suggesting the use of a higher level, lexical mechanism. Furthermore, during native speech comprehension, semantic violations in the critical words elicited an N400 effect followed by a late positivity. During foreign-accented speech comprehension, semantic violations only elicited an N400 effect. Overall, our results suggest that, despite a lack of improvement in phonetic discrimination, native listeners experience changes at lexical-semantic levels of processing after brief exposure to foreign-accented speech. Moreover, these results suggest that lexical access, semantic integration and linguistic re-analysis processes are permeable to external factors, such as the accent of the speaker.
Towards pattern-based design recovery

A method and a corresponding tool is described which assist design recovery and program understanding by recognising instances of design patterns semi-automatically. The approach taken is specifically designed to overcome the existing scalability problems caused by many design and implementation variants of design pattern instances. Our approach is based on a new recognition algorithm which works incrementally rather than trying to analyse a possibly large software system in one pass without any human intervention. The new algorithm exploits domain and context knowledge given by a reverse engineer and by a special underlying data structure, namely a special form of an annotated abstract syntax graph. A comparative and quantitative evaluation of applying the approach to the Java AWT and JGL libraries is also given.
Kurtosis Constraints In Communication Over Fading Channels

The kurtosis of a signal is a quantitative measure of how `peaky' it is. In this paper we consider two scenarios of communication over fading channels with kurtosis constraints: in the first, we analyze a non-coherent Rayleigh fading channel where the input signal is required to satisfy a kurtosis constraint in addition to a power constraint. In the second, we find the `worst' fading process that satisfies a kurtosis constraint and has a given second moment, while the fading coefficients are assumed to be known at the receiver. In both cases the transmitter is assumed ignorant of the instantaneous fading realization. The technique that enables our analysis is based on bounding mutual information between random variables which satisfy kurtosis and second moment constraints; the bound is tight in the low second moment regime and can be extended to multi-antenna communications.
Novel Path Search Algorithm for Image Stitching and Advanced Texture Tiling

We propose a fast and adjustable sub-optimal path search algorithm for finding minimum error boundaries between overlapping images. The algorithm may serve as an efficient alternative to traditional slow path search algorithms like the dynamical programming. We use the algorithm in combination with novel adaptive blending to stitch image regions. The technique is then exploited in a framework for sampling-based texture synthesis where the learning phase is clearly separated and the synthesis phase is very simple and fast. The approach exploits the potential of tile-based texturing and produces good and realistic results for a wide range of textures.
Measuring the Semantic Similarity of Comments in Bug Reports

Bug-tracking systems, such as Bugzilla, contain a large amount of information about software defects, most of it stored in textual, rather than structured form. This information is used not only for locating and fixing the bugs, but also for detecting bug duplicates, triaging incoming bugs, automatically assigning bugs to developers, etc. Given the importance of the textual information in the bug reports, it is desirable that this text is highly coherent, such that the readers can easily understand it. The paper describes an approach to measuring the textual coherence of the user comments in bug reports. The coherence of bug reports from Eclipse was measured and the results are discussed in the paper.
Long-term influences of a preterm birth on movement organization and side specialization in children at 4-8 years of age.

This study explored upper-limb and head kinematics during unimanual goal-directed movements in children born preterm (PT) and full-term (FT) aged 4-8 years. Further, functional lateralization was investigated through side-specific kinematics and hand preference observations. Altogether, 141 children were included, divided into three sub-groups based on gestation week at birth (GW). Children born FT (38-41 GW) and moderately PT (33-35 GW) showed faster, smoother, and shorter movement trajectories than children born very PT (V-PT < 33 GW). Only children born FT expressed evident side differences that were characterized by smoother movements with the preferred side. Regarding hand preference, the children born V-PT showed increased rates of non-right-handedness compared with the other groups. Regardless of hand preference, the children born V-PT showed less well organized movements compared with the other groups. These findings suggest that spatio-temporal movement organization and side specialization at pre-/early school-age are affected by a PT birth, and more frequently so for children born before 33 GWs, indicating long-lasting influences on neuromotor development and specialization.
Comments on Mallow's C¦p statistics and multicollinearity effects on predictions

Selecting a subset of predictors by considering al1 possible combinations of variables with corresponding values of Mallows' C p , AIC and BIC is discussed. It is shown that when a model with the smallest C, is selected 16% of non-related predictors had the chance of being entered in the model. The effect of multicollinearity on the prediction errors is studied. When multicollinearity is not severe the fitted model can be used for prediction. When severe multicollinearity exists it is still safe to interpolate but not to extrapolate. 1 am extrernely grateful t o m y supervisor Professor Paul Corey fo r h i s e f f i c i en t guidance and constructive cri t icisms throughout the course of t h i s research, 1 am very happy t o find an occasion t o express m y gratitude to my family, though whatever 1 express m a y not f u l l y capture m y feelings of love and respect fo r thern. 1 dedicate t h i s work to m y wife and my childrenT a b l e of
A Dynamic, Lock free Data Dictionary for Parallel State Space Construction

We propose a novel algorithm for parallel state space construction based on an original data structure, called a localization table, that aims at better space and temporal balance. Our proposal is close in spirit to algorithms based on distributed hash tables with the distinction that states are dynamically assigned to processors; we do not rely on an a-priori static partition of the state space. Distribution of the states space and coordination between processes is made through the shared access to a localization table, that is designed to be a highly efficient, thread safe data structure. In our solution, every process keeps a share of the global state space. The localization table is used to dynamically assign newly discovered states and behaves as an associative array that returns the identity of the processor that owns a given state. With this approach, we are able to consolidate a network of local dictionaries into an (abstract) distributed data structure without sacrificing memory affinity – data that are ”logically connected” are physically close to each others – and without incurring performance costs associated to the heavy use of locks to ensure data integrity. We evaluate the performance of our algorithm based on experimental results obtained on different benchmarks and compare these results with other solutions proposed in the literature.
CourboSpark: Decision Tree for Time-series on Spark

With the deployment of smart meters across many countries, data are being collected at a large scale and volume. These data are collected for billing purposes but also to get analytical insights. Our main goal here is to build an understandable model able to explain the electric consumption patterns regarding several features. We chose to use decision tree models as they are easily comprehensible and have already been parallelized with success. In our industrial context, we often have to work on electrical time-series where the target to predict is neither a label (classification) nor a numerical value (regression) but a time-series representing a load curve. Therefore we use a different split criterion to separate time-series: the inertia. We also need a dedicated method for categorical features since the standard implementation would not work for time-series. This method is based on a hierarchical clustering in order to have a good trade-off between the computational complexity and the exploration of the possible bi-partition splits. We demonstrate the performance of our implementation on datasets with different sizes (up to a terabyte).
Physical and physiological profiles of youth elite handball players during training sessions and friendly matches according to playing positions

This study aimed to describe youth elite handball players’ performance during training sessions and friendly matches, according to specific playing positions. Seventeen male players from the Portuguese national team participated in this study (goalkeepers n=4, 1st line players n=6, 2nd line players n=7). The data was gathered during a one-week period (four training sessions) and two friendly matches using the following variables: training impulse (TRIMPMOD), countermovement jump, Abalakov jump and bodyload. The comparisons were made using percentages of variation from the match, considered as the baseline. The results showed that goalkeepers presented higher demands in training sessions. Comparatively to matches, the 1st line players presented higher Abalakov jump values after training sessions (≈8%). However, the high intensity zones of TRIMPMOD and bodyload per minute presented higher values during matches. The 2nd line players showed higher values of vertical jump after the training sessions. Additionally, the TRIMPMOD training presented values above 300% in low-intensity zones and ≈100% of variation in high-intensity zones from match. The amount of specific exercises performed by goalkeepers during the training sessions elicited a higher workload, and the lowest training stimuli for both 1st and 2nd line players suggested that training sessions do not replicate the match workload demands. Therefore, the identified match performance profiles among playing positions may help coaches to establish more specific and accurate training guidelines.
Mobile phone based AR scene assembly

In this paper we describe a mobile phone based Augmented Reality application for 3D scene assembly. Augmented Reality on mobile phones extends the interaction capabilities on such handheld devices. It adds a 6 DOF isomorphic interaction technique for manipulating 3D content. We give details of an application that we believe to be the first where 3D content can be manipulated using both the movement of a camera tracked mobile phone and a traditional button interface as input for transformations. By centering the scene in a tangible marker space in front of the phone we provide a mean for bimanual interaction. We describe the implementation, the interaction techniques we have developed and initial user response to trying the application.