Miracle-dz/UniFAR-FTUs huggingface dataset:
A software modeling capability proxy metric

Software engineering-the art of building software-has become a crucial skill in a global economy increasingly affected by IT. This paper tries to indicate where a specific advanced software engineering activity takes place, and how different countries compare. We propose a proxy metric for the activity, and analyze the corresponding data set by location and economic performance. Main findings: Europe does more advanced software engineering than the Americas; Northern and Eastern European countries are hotspots; the US is 41st in activity per gross domestic product (GDP), while India is 10th; Belgium and Switzerland have a high dispersion of their activity over their cities. The results are subject to the validity of the proxy measure used. Additional tools will be analyzed to provide a comprehensive software engineering capability map.
Impaired neutralizing activity by transplacental measles antibodies in infants born to HIV‐1‐infected mothers

Aim: Growing numbers of newborns are saved from HIV infection through increased access to mother‐to‐child transmission prevention programmes. The maternally derived humoral immunity of these children might be impaired, both in terms of quantity and in terms of quality, with consequences for the timing of immunization against measles.
Near capacity LDPC coded MU-BICM-ID for 5G

In 5th generation (5G) wireless communication networks, non-orthogonal multiple access (NOMA) is a key technique for supporting massive connectivity and high spectral efficiency. In NOMA systems, the signals sent by multiple users are superimposed at the receiver, which is a multiple access channel (MAC) in information-theoretic perspective. In this paper, we propose near-capacity multi-user bit-interleaved coded modulation with iterative demapping (MU-BICM-ID) scheme for two-user Gaussian multiple-access channel (GMAC), especially for high spectral efficiency scenarios. To retrieve the shaping loss, we suggest to use amplitude phase shift keying (APSK) constellation instead of conventional quadrature amplitude modulation (QAM) constellation. Furthermore, we disclose the fact that the low-density parity-check (LDPC) code optimized for point-to-point is not suitable for GMAC, and therefore we propose and optimize Raptor-like LDPC code for GMAC. Via extrinsic information transfer (EXIT) chart analysis as well as bit-error rate (BER) simulation, we illustrate the near-capacity performance of the proposed scheme.
Long-term outcome with first-line bosentan therapy in idiopathic pulmonary arterial hypertension.

AIMS Data on long-term efficacy of bosentan in unselected idiopathic pulmonary arterial hypertension (IPAH) patients are lacking. We aimed to describe the long-term outcome of consecutive IPAH patients treated first-line with bosentan. METHODS AND RESULTS A retrospective analysis of 103 consecutive New York Heart Association functional class III/IV IPAH patients treated with bosentan at our centre between November 1999 and May 2004 was performed. The 6-minute walk distance (6MWD) and haemodynamics were assessed at baseline and after 4 and 12 months. Mean follow-up was 24+/-15 months. At 4 months, significant improvements in exercise capacity and haemodynamics were observed and persisted up to 1 year. Overall survival estimates were 90 and 87% and event-free status (survival without transplantation, prostanoid initiation, or hospitalization for right heart failure) estimates were 61 and 44% at 1 and 2 years, respectively. Forty-five (44%) patients required prostanoid therapy during follow-up. The 6MWD and the right atrial pressure at baseline and the 6MWD, the increase in 6MWD, and the decrease in pulmonary resistance after 4 months of treatment were associated with long-term outcomes. CONCLUSION In our series of consecutive IPAH patients treated with bosentan, improvements in exercise capacity and haemodynamics were similar to those observed in previous randomized trials. However, on the basis of local criteria, many patients required the addition of prostanoid therapy during follow-up.
Resolving Visual Uncertainty and Occlusion through Probabilistic Reasoning

Tracking interacting human body parts from a single two-dimensional view is difficult due to occlusion, ambiguity and spatio-temporal discontinuities. We present a Bayesian network method for this task. The method is not reliant upon spatio-temporal continuity, but exploits it when present. Our inferencebased tracking model is compared with a CONDENSATION model augmented with a probabilistic exclusion mechanism. We show that the Bayesian network has the advantages of fully modelling the state space, explicitly representing domain knowledge, and handling complex interactions between variables in a globally consistent and computationally effective manner.
Probabilistic analysis of success and failure rates of candidates generation algorithms for the frequent itemsets mining problem

is paper consider the success and failure probability of candidate generation algorithms for the frequent itemsets mining problem under several probability model. Results for one of the models had been obtained previously, but with a complex derivation. Our re-derivation of these results is simpler and employed a concentration inequality for the sum of independent Bernoulli random variables. Our results for the other models employed concentration inequalities formartingales and is applicable tomodels where there is dependence between the transactions. From the success and failure probability we can estimate the size of the maximum frequent itemset.
Learning the Multilingual Translation Representations for Question Retrieval in Community Question Answering via Non-Negative Matrix Factorization

Community question answering (CQA) has become an increasingly popular research topic. In this paper, we focus on the problem of question retrieval. Question retrieval in CQA can automatically find the most relevant and recent questions that have been solved by other users. However, the word ambiguity and word mismatch problems bring about new challenges for question retrieval in CQA. State-of-the-art approaches address these issues by implicitly expanding the queried questions with additional words or phrases using monolingual translation models. While useful, the effectiveness of these models is highly dependent on the availability of quality parallel monolingual corpora (e.g., question-answer pairs) in the absence of which they are troubled by noise issues. In this work, we propose an alternative way to address the word ambiguity and word mismatch problems by taking advantage of potentially rich semantic information drawn from other languages. Our proposed method employs statistical machine translation to improve question retrieval and enriches the question representation with the translated words from other languages via non-negative matrix factorization. Experiments conducted on real CQA data sets show that our proposed approach is promising.
Early life determinants of physical activity in 11 to 12 year olds: cohort study

Objective To examine factors in early life (up to age 5 years) that are associated with objectively measured physical activity in 11-12 year olds. Design Prospective cohort study. Setting Avon longitudinal study of parents and children, United Kingdom. Participants Children aged 11-12 years from the Avon longitudinal study of parents and children. Main outcome measure Physical activity levels in counts per minute (cpm) and minutes of moderate to vigorous physical activity for seven days measured with a uniaxial actigraph accelerometer. Results Valid actigraph data, defined as at least three days of physical activity for at least 10 hours a day, were collected from 5451 children. Several factors were associated with physical activity at ages 11-12 years. Regression coefficients are compared with the baseline of “none” for categorical variables: maternal brisk walking during pregnancy (regression coefficient 5.0, 95% confidence interval −8.5 to 18.5; cpm for <1 h/wk and ≥2 h/wk of physical activity 17.7, 5.3 to 30.1), maternal swimming during pregnancy (21.5, 10.9 to 32.1 and cpm for <1 h/wk and ≥2 h/wk of physical activity 24.2, 7.8 to 40.7), parents’ physical activity when the child was aged 21 months (28.5, 15.2 to 41.8 and cpm of physical activity for either parent active and both parents active 33.5, 17.8 to 49.3), and parity assessed during pregnancy (2.9, −7.6 to 13.4 and cpm of physical activity for 1 and ≥2 parity 21.2, 7.1 to 35.3). Conclusions Few factors in early life predicted later physical activity in 11-12 year olds. Parents’ physical activity during pregnancy and early in the child’s life showed a modest association with physical activity of the child at age 11-12 years, suggesting that active parents tend to raise active children. Helping parents to increase their physical activity therefore may promote children’s activity.
Allometric scaling and taxonomic variation in nutrient utilization traits and maximum growth rate of phytoplankton

Nutrient utilization traits can be used to link the ecophysiology of phytoplankton to population dynamic models and the structure of communities across environmental gradients. Here we analyze a comprehensive literature compilation of four traits: maximum nutrient uptake rate; the half‐saturation constant for nutrient uptake; the minimum subsistence quota, measured for nitrate and phosphate; and maximum growth rate. We also use these traits to analyze two composite traits, uptake affinity and scaled uptake affinity. All traits tend to increase with cell volume, except for scaled uptake affinity and maximum growth rate, which tend to decline with cell volume. Most scaling relationships are the same for freshwater and marine species, although important differences exist. Most traits differ on average between major taxa, but between‐taxon variation is nearly always due to between‐taxon variation in volume. There is some evidence for between‐trait correlations that could constrain trait evolution, but these correlations are difficult to disentangle from correlation driven by cell volume. These results should enhance the parameterization of models that use size or taxonomic group to structure physiological variation in phytoplankton communities.
SpyAvidin Hubs Enable Precise and Ultrastable Orthogonal Nanoassembly

The capture of biotin by streptavidin is an inspiration for supramolecular chemistry and a central tool for biological chemistry and nanotechnology, because of the rapid and exceptionally stable interaction. However, there is no robust orthogonal interaction to this hub, limiting the size and complexity of molecular assemblies that can be created. Here we combined traptavidin (a streptavidin variant maximizing biotin binding strength) with an orthogonal irreversible interaction. SpyTag is a peptide engineered to form a spontaneous isopeptide bond to its protein partner SpyCatcher. SpyTag or SpyCatcher was successfully fused to the C-terminus of Dead streptavidin subunits. We were able to generate chimeric tetramers with n (0 ≤ n ≤ 4) biotin binding sites and 4-n SpyTag or SpyCatcher binding sites. Chimeric SpyAvidin tetramers bound precise numbers of ligands fused to biotin or SpyTag/SpyCatcher. Mixing chimeric tetramers enabled assembly of SpyAvidin octamers (8 subunits) or eicosamers (20 subunits). We validated assemblies using electrophoresis and native mass spectrometry. Eicosameric SpyAvidin was used to cluster trimeric major histocompatibility complex (MHC) class I:β2-microglobulin:peptide complexes, generating an assembly with up to 56 components. MHC eicosamers surpassed the conventional MHC tetramers in acting as a powerful stimulus to T cell signaling. Combining ultrastable noncovalent with irreversible covalent interaction, SpyAvidins enable a simple route to create robust nanoarchitectures.
Finite abstractions of networked control systems

In networked control systems (NCS), the communication between sensors, controllers, and actuators is supported by a shared communication channel that is subject to variable communication delays, limited bandwidth, packet losses, quantization errors, and other practical non-idealities. This work investigates the problem of constructively deriving symbolic models of NCS by simultaneously considering the mentioned network non-idealities. By employing the obtained symbolic models, one can completely automate the design of controllers enforcing rich logical specifications, e.g. formulae in linear temporal logic, over NCS.
Visual gesture recognition for human robot interaction using dynamic movement primitives

In this paper a method to address the efficiency and robustness of dynamic hand gesture recognition for human robot interaction is proposed. By using on-board monocular camera and specialized gesture detection algorithms, the humanoid robot is able to detect gestures fast. To model the dynamics of gestures, the dynamic movement primitives (DMP) model is employed, which well characterizes both spatial and temporal evolutions of gestures. The invariance properties of the DMP model against different spatiotemporal scales also offer expected robustness to handle the variances in gestures. To cope with the diversity and noise of gestures, an efficient adaptive DMP learning method is further proposed. Since the learnt weights of the DMP compactly represent the original gestures, they serve as ideal feature vectors for building a classifier to recognize new gestures. To evaluate the proposed method, a nine-class human gestures recognition task on a real humanoid robot is performed and 98.06% accuracy is obtained. Experimental results demonstrate the effectiveness of our method.
New current controller for inverter fed medium voltage drives with LC filter

In high power medium voltage drives, the switching frequency of power semiconductor devices is restricted because of high switching losses. Such drives often include an LC output filter, introducing a resonant circuit that may be excited for instance by fast control transients. One way to avoid such oscillations is using damping control schemes, which in turn usually require switching frequencies well above the filter resonance. This paper proposes a new predictive stator current controller that avoids the excitation of the filter resonance, performs active damping and allows fast current control while maintaining low switching frequency. Simulation results of a 2.4 kV induction motor drive and experimental results obtained from a 55 kW prototype a.c. drive demonstrate feasibility and good dynamic performance of the proposed control approach.
Requirement of myomaker-mediated stem cell fusion for skeletal muscle hypertrophy

Fusion of skeletal muscle stem/progenitor cells is required for proper development and regeneration, however the significance of this process during adult muscle hypertrophy has not been explored. In response to muscle overload after synergist ablation in mice, we show that myomaker, a muscle specific membrane protein essential for myoblast fusion, is activated mainly in muscle progenitors and not myofibers. We rendered muscle progenitors fusion-incompetent through genetic deletion of myomaker in muscle stem cells and observed a complete reduction of overload-induced hypertrophy. This blunted hypertrophic response was associated with a reduction in Akt and p70s6k signaling and protein synthesis, suggesting a link between myonuclear accretion and activation of pro-hypertrophic pathways. Furthermore, fusion-incompetent muscle exhibited increased fibrosis after muscle overload, indicating a protective role for normal stem cell activity in reducing myofiber strain associated with hypertrophy. These findings reveal an essential contribution of myomaker-mediated stem cell fusion during physiological adult muscle hypertrophy. DOI: http://dx.doi. org/10.7554/eLife.20007. 001
Efficient expression of the yeast metallothionein gene in Escherichia coli

The yeast metallothionein gene CUP1 was cloned into a bacterial expression system to achieve efficient, controlled expression of the stable, unprocessed protein product. The Escherichia coli-synthesized yeast metallothionein bound copper, cadmium, and zinc, indicating that the protein was functional. Furthermore, E. coli cells expressing CUP1 acquired a new, inducible ability to selectively sequester heavy metal ions from the growth medium.
Damping control of variable damping compliant actuators

The development of variable impedance actuators (VIAs) has highlighted the need for proper control of passive impedance to attain suitable interaction performance. Until recently the regulation of the intrinsic impedance in VIAs is achieved in an open-loop model-based manner, mainly due to the lack of physical sensors capable of measuring impedance components such as stiffness and damping. Hence, the estimation of variable stiffness and damping has been explored, with the target to provide monitoring and feedback for potential closed loop control schemes. However, the use of the output of these estimators in the feedback control of variable impedance actuators has never been implemented/demonstrated in practice. This work contributes to the field with the development and experimental evaluation of a novel damping feedback control for a class of variable impedance compliant actuators able to realize a variable physical damping principle. The scheme is based on non-model-based damping estimation feedback to compensate model uncertainties in the action of an inner controller that uses a model-based friction estimator. Experimental results demonstrate the ability of the proposed scheme to replicate with good fidelity constant and time-varying damping levels.
The influence of gender on the incorporation of the Internet in Spanish schools’ educational programmes

This article reveals the results of a research study that was carried out in Spain in 2012 with the purpose of discovering the influence of the gender variable on the incorporation of the Internet in the educational programmes of primary and secondary public education centres. By using a multiple case study carried out in situ, the research team has gathered information from the teaching staff entrusted with the process of incorporating the Internet into the educational programme at each school. It has also studied the way in which the use of the Internet in the classroom is specified. These sources have been subjected to triangulation techniques in order to increase the reliability of the results, which has enabled us to define the extent to which the gender of those running the educational implementation of the Internet in Spanish centres is influential. The results show that there are no significant differences between men and women as regards the introduction of the Internet into the educational programmes at the centres used in this study.
Causality and the ontology of disease

The goal of this paper is two-fold: first, to emphasize causality in disease ontology and knowledge representation, presenting a general and cursory discussion of causality and causal chains; and second, to clarify and develop the River Flow Model of Diseases (RFM). The RFM is an ontological account of disease, representing the causal structure of pathology. It applies general knowledge of causality using the concept of causal chains. The river analogy of disease is explained, formal descriptions are offered, and the RFM disease definition is refined by describing causal chains in terms of causal relations. The definition is updated to coincide with the actual RFM classes found in its upper-level ontology, YAMATO, which brings to light some challenges in developing both YAMATO and the RFM. The RFM is also discussed in relation to another ontological account of disease. Strategies are offered toward interoperability between these theories.
Genome-Scale Identification of Legionella pneumophila Effectors Using a Machine Learning Approach

A large number of highly pathogenic bacteria utilize secretion systems to translocate effector proteins into host cells. Using these effectors, the bacteria subvert host cell processes during infection. Legionella pneumophila translocates effectors via the Icm/Dot type-IV secretion system and to date, approximately 100 effectors have been identified by various experimental and computational techniques. Effector identification is a critical first step towards the understanding of the pathogenesis system in L. pneumophila as well as in other bacterial pathogens. Here, we formulate the task of effector identification as a classification problem: each L. pneumophila open reading frame (ORF) was classified as either effector or not. We computationally defined a set of features that best distinguish effectors from non-effectors. These features cover a wide range of characteristics including taxonomical dispersion, regulatory data, genomic organization, similarity to eukaryotic proteomes and more. Machine learning algorithms utilizing these features were then applied to classify all the ORFs within the L. pneumophila genome. Using this approach we were able to predict and experimentally validate 40 new effectors, reaching a success rate of above 90%. Increasing the number of validated effectors to around 140, we were able to gain novel insights into their characteristics. Effectors were found to have low G+C content, supporting the hypothesis that a large number of effectors originate via horizontal gene transfer, probably from their protozoan host. In addition, effectors were found to cluster in specific genomic regions. Finally, we were able to provide a novel description of the C-terminal translocation signal required for effector translocation by the Icm/Dot secretion system. To conclude, we have discovered 40 novel L. pneumophila effectors, predicted over a hundred additional highly probable effectors, and shown the applicability of machine learning algorithms for the identification and characterization of bacterial pathogenesis determinants.
Sliding mode control with gain-scheduled and improved boundary layer for nonholonomic multi-robot formation

In this paper, we have proposed a sliding mode control law with gain-scheduled and improved boundary layer for leader-follower based formation control. The switching gains of sliding mode controller are required to change with the absolute value of sliding mode function. Specifically, a larger switching gain should be adopted in order to ensure rapid convergence, while a smaller one should be adopted to suppress the chattering. In addition, an improved boundary layer method is applied such that the chattering can be further eliminated. Both of the simulation and experimental results show that the proposed control law weakens the chattering of the system, reduces the system steady-state error and guarantees the response speed of the system.