Miracle-dz/UniFAR-FTUs huggingface dataset:
Continuous mobility of mobile robots with a special ability for overcoming driving failure on rough terrain

SUMMARY For wheeled mobile robots moving in rough terrains or uncertain environments, driving failure will be encountered when trafficability failure occurs. Continuous mobility of mobile robots with special ability for overcoming driving failure on rough terrain has rarely been considered. This study was conducted using a four-wheel-steering and four-wheel-driving mobile robot equipped with a binocular visual system. First, quasi-static force analysis is carried out to understand the effects of different driving-failure modes on the mobile robot while moving on rough terrain. Secondly, to make the best of the rest of the driving force, robot configuration transformation is employed to select the optimal configuration that can overcome the driving failure. Thirdly, sliding mode control based on back-stepping is adopted to enable the robot achieve continuous trajectory tracking with visual feedback. Finally, the efficacy of the presented approach is verified by simulations and experiments.
CD4 T-lymphocyte recovery in individuals with advanced HIV-1 infection receiving potent antiretroviral therapy for 4 years: the Swiss HIV Cohort Study.

BACKGROUND Highly active antiretroviral therapy (HAART) for human immunodeficiency virus (HIV)-1 infection allows recovery of CD4 T lymphocytes. Few studies have explored the long-term T-lymphocyte responses to HAART. METHODS Plasma HIV-1 RNA levels and CD4 and CD8 T-lymphocyte counts were longitudinally analyzed over 4 years in 2235 participants of the Swiss HIV Cohort, commencing HAART between 1996 and 1997. The CD4 T-lymphocyte count increase, the percentage of individuals with a CD4 T-lymphocyte count of 500/microL or greater and less than 200/microL, and the determinants of CD4 T-lymphocyte recovery were evaluated in individuals treated with continuous (CONT; n = 985) and discontinuous (DISCONT; n = 1250) HAART. RESULTS At 4 years, 69.5% of subjects (CONT, 84.5%; DISCONT, 53.6%; P<.001) showed HIV-1 RNA levels below 400 copies/mL, while the median CD4 T-lymphocyte count increased from 190/microL to 423/microL (CONT, 486/microL; DISCONT, 343/microL; P<.001). Of the 2235 participants, 38.8% (CONT, 47.7%; DISCONT, 29.4%; P<.001) reached a CD4 T-lymphocyte count of 500/microL or greater, but in 15.6%, CD4 T-lymphocyte count remained below 200/microL (CONT, 5.9%; DISCONT, 25.9%; P<.001). Larger increases in CD4 T-lymphocyte count were associated with higher baseline HIV-1 RNA, a larger percentage of undetectable HIV-1 RNA levels, lower baseline CD8 T-lymphocyte count, and younger age. Individuals reaching a CD4 T-lymphocyte count of 500/microL or greater at 4 years were characterized by higher nadir and baseline CD4 T-lymphocyte counts and a more sustained reduction of HIV-1 RNA levels. CONCLUSIONS At 4 years, only 39% of individuals treated with HAART reached a CD4 T-lymphocyte count of 500/microL or greater, and 16% with CD4 T-lymphocyte counts less than 200/microL remained susceptible to opportunistic infections. Treatment interruptions, a poor virologic response, and older age were the major factors negatively affecting the recovery of CD4 T lymphocytes.
Subspace Projection Approaches to Classification and Visualization of Neural Network-Level Encoding Patterns

Recent advances in large-scale ensemble recordings allow monitoring of activity patterns of several hundreds of neurons in freely behaving animals. The emergence of such high-dimensional datasets poses challenges for the identification and analysis of dynamical network patterns. While several types of multivariate statistical methods have been used for integrating responses from multiple neurons, their effectiveness in pattern classification and predictive power has not been compared in a direct and systematic manner. Here we systematically employed a series of projection methods, such as Multiple Discriminant Analysis (MDA), Principal Components Analysis (PCA) and Artificial Neural Networks (ANN), and compared them with non-projection multivariate statistical methods such as Multivariate Gaussian Distributions (MGD). Our analyses of hippocampal data recorded during episodic memory events and cortical data simulated during face perception or arm movements illustrate how low-dimensional encoding subspaces can reveal the existence of network-level ensemble representations. We show how the use of regularization methods can prevent these statistical methods from over-fitting of training data sets when the trial numbers are much smaller than the number of recorded units. Moreover, we investigated the extent to which the computations implemented by the projection methods reflect the underlying hierarchical properties of the neural populations. Based on their ability to extract the essential features for pattern classification, we conclude that the typical performance ranking of these methods on under-sampled neural data of large dimension is MDA>PCA>ANN>MGD.
Rationality in Collective Action

Collective action is interpreted as a matter of people doing something together, and it is assumed that this involves their having a collective intention to do that thing together. The account of collective intention for which the author has argued elsewhere is presented. In terms that are explained, the parties are jointly committed to intend as a body that such-and-such. Collective action problems in the sense of rational choice theory—problems such as the various forms of coordination problem and the prisoner’s dilemma—are then considered. An explanation is given of how, when such a problem is interpreted in terms of the parties’ inclinations, a suitable collective intention resolves the problem for agents who are rational in a broad sense other than the technical sense of game theory.
Performance Measures of Stream-Oriented Power Consumption for Asymmetrical Communication in Wireless Ad-Hoc Networks

Power consumption control in mobile ad-hoc networks is one of the most important issues for enabling a guaranteed quality of service in end-to-end transmissions. However recent power consumption control techniques have not yet associated the power control of a wireless device with the content delivery. This means that all transmissions are treated in the same way, which is disastrous in the case of delay sensitive contents in end-to-end connections. In this work the packet stream of a delay sensitive content is modeled and associated with the prioritization of the packets and their spatiotemporal delays. Depending on each stream's characteristics at a certain time, a nonlinear communication model is proposed. Adjacent-neighboring nodes with certain transmission power associate their data delay with nodes' capacity measures during data revocation. Following a real time scenario each node has fading characteristics in an entirely asymmetric communication. Performance evaluation results show the efficiency of the proposed model as well as its capabilities under different fading conditions
Management responsable et PME : une relecture du concept de « responsabilité sociétale de l'entreprise

La responsabilite societale de l'entreprise ( RSE) n'est que tres faiblement integree dans les strategies des PME en depit des nombreux discours sur les avantages de la RSE et en depit des nombreuses propositions de nouveaux outils adaptes aux PME. L'objectif de cette communication est d'analyser les determinants et les freins au processus d'integration de la RSE dans les decisions strategiques des PME et de contribuer ainsi a une meilleure comprehension de la RSE en general.En plus des obstacles traditionnellement cites, notamment la faiblesse des ressources et la vulnerabilite economique, les grilles de lecture theoriques et les entretiens realises ont permis de mettre en lumiere l'importance des reseaux qui peuvent servir de relais au changement de culture du chef d'entreprise, l'absence d'institutionnalisation de la responsabilite sociale des entreprises au sein des champs organisationnels des PME et donc l'absence de contraintes mimetiques ou normatives qui inflechiraient leur comportement. Les determinants actuels (pression des clients et des donneurs d'ordre, contraintes liees a la reglementation) et les leviers emergents (role des banques, marches publics) conduisent a des strategies de conformite apparente, au mieux a un apprentissage en simple boucle. Une integration plus effective des objectifs environnementaux ou sociaux dans le management depend d'une modification du systeme cognitif du dirigeant (deuxieme boucle de l'apprentissage) portee par les valeurs institutionnalisees dans les reseaux ou il est insere (notamment l'ancrage territorial).
DCU System Report on the WMT 2017 Multi-modal Machine Translation Task

We report experiments with multi-modal neural machine translation models that incorporate global visual features in different parts of the encoder and decoder, and use the VGG19 network to extract features for all images. In our experiments, we explore both different strategies to include global image features and also how ensembling different models at inference time impact translations. Our submissions ranked 3rd best for translating from English into French, always improving considerably over an neural machine translation baseline across all language pair evaluated, e.g. an increase of 7.0–9.2 METEOR points.
“Committed as Near Neighbors”: The Halifax Explosion and Border-Crossing People and Ideas

Popular accounts of the Halifax Explosion of 1917 have placed it in a resolutely nationalist context. But starting from the international ownerships and destinations of the ships that sparked it, the explosion was a transnational event. This article explores how people, money, and ideas crossed and recrossed the border. First, in-kind and monetary relief flowed quickly from the United States, Britain, and Newfoundland. Second, Halifax became a destination for a growing international community of experts in disaster response, as relief experts from New York, Boston, Winnipeg, and elsewhere in North America converged on the city. Finally, survivors used their transnational community of friends and relatives to build political power over the relief process. Migrants living in “the Boston States” created a transnational polity that pressured relief authorities to give more money to their kin still in Halifax. These transnational communities—of international experts and migrant families—helped create a Canada–US relationship from the bottom.
A Decade of Hardware/Software Codesign

The term hardware/software codesign, coined about 10 years ago, describes a confluence of problems in integrated circuit design. By the 1990s, it became clear that microprocessor-based systems would be an important design discipline for IC designers as well. Large 16- and 32-bit microprocessors had already been used in board-level designs, and Moore's law ensured that chips would soon be large enough to include both a CPU and other subsystems. Multiple disciplines inform hardware/software codesign. Computer architecture tells us about the performance and energy consumption of single CPUs and multiprocessors. Real-time system theory helps analyze the deadline-driven performance of embedded systems. Computer-aided design assists hardware cost evaluation and design space exploration.
A novel immunotherapy for superficial bladder cancer by intravesical immobilization of GM-CSF

In situ gene therapy with granulocyte‐macrophage colony‐stimulating factor (GM‐CSF) was demonstrated to successfully inhibit tumour cell growth in a mouse orthotopic bladder cancer model, but suffered from several disadvantages, such as limited efficiency for gene delivery, low expression efficiency of the transgene and the safety concern resulting from viral vector. In order to address the limits, a novel immunotherapy was developed attentively through immobilization of streptavidin‐tagged bioactive GM‐CSF on the biotinylated mucosal surface of bladder wall on the basis of both the unique property of streptavidin (SA) to bind rapidly and almost irreversibly to any biotin‐linked molecule and the outstanding ability of biotin to be incorporated easily into the proteins on the cell surface. The mouse orthotopic model of MB49 bladder cancer was used to evaluate the feasibility and efficacy of the novel immunotherapy performed twice a week for 3 weeks. Briefly, 1 day after intravesical implantation of 1 × 106 MB49 tumour cells in C57BL/6 mouse, 100 μl of 1 mg/ml NHS‐PEO4‐biotin was instilled and allowed to incubate in the bladder for 30 min., followed by intravesical instillation of 100 μl of 0.15 mg/ml SA‐GM‐CSF bifunctional fusion protein and incubation for 1 hr. SA‐GM‐CSF fusion protein was shown to be immobilized efficiently and durably on the biotinylated mucosal surface of bladder wall. The bladder cancer incidence was dramatically decreased from 100% in the control group to 37.5% in the SA‐GM‐CSF group. Importantly, 70% of the SA‐GM‐CSF‐cured mice were protected against a second intravesical wild‐type MB49 tumour challenge, indicating that an effective anti‐tumour immunity was generated against MB49 bladder cancer. Thus, the novel immunotherapy may be an attractive therapeutic alternative and should be evaluated in bladder cancer patients.
Task and Stimulation Paradigm Effects in a P300 Brain Computer Interface Exploitable in a Virtual Environment: A Pilot Study

The aim of the present study is to compare different visual elicitation paradigms exploitable in a Virtual Environment in order to establish whether the BCI is affected by the structure of the elicitation paradigm, the modalities of stimulus presentation, and the complexity of stimulus recognition and semantic processing. We have developed a device which can control the motion of a cursor on a computer graphical interface, using ERPs (Piccione et al., 2006). Subsequently, we tested different visual elicitation paradigms which evoked P300 waves to control the movement of an object in a virtual environment. Visual stimuli, consisting of four arrows (forward, right, back, left), were randomly presented in peripheral positions of a virtual environment. Users were instructed to recognize only the stimulus related to the preferred object movement direction (target). The sum of the absolute differences between target and non-target traces (ra index) was compared in the different elicitation paradigms. Results showed a significant reduction of ra index with the use of more semantically complex paradigms. Therefore, the P300 BCI system seems to be affected by the structure of the elicitation paradigm, the modalities of stimulus presentation, and the complexity of stimulus recognition and semantic processing.
A PRELIMINARY DESCRIPTION AND FACTOR ANALYSIS OF A BROAD SPECTRUM BATTERY FOR ASSESSING ‘PROGRESS TOWARD READING MATURITY’

The study of reading behavior is presumed to be arrested by low‐risk instrumentation. A battery is described which was assembled to advance study and definition of reading maturity. The battery is shown, by factor analysis, to have greater implicit construct similarity to a popular taxonomy and diagnostic system than conventional measures typically address. Suggestion for the wider use of such paradigms for assessment are shown to yield qualitatively richer data for use in research than current conventions tend to provide.
Differential Diagnosis of Alterations in Arterial Flow and Tissue Oxygenation on Venoarterial Extracorporeal Membrane Oxygenation

Background Venoarterial extracorporeal membrane oxygenation (VA-ECMO) may be life-saving in several clinical situations, but it is also one of the most invasive therapeutic procedures, with significant potential for life-threatening complications. Pulse pressure waves are typically very small or even absent at the onset of ECMO therapy, and will reappear with the improvement of cardiac function. A low pulse pressure may indicate low cardiac output due to heart failure during sustained ECMO support. A sudden loss of pulse pressure during ECMO therapy, however, may reveal complications like pericardial tamponade, hemothorax or pneumothorax. Near infrared spectroscopy (NIRS) has been shown to be useful in detecting cerebral and lower limb ischemic events during ECMO therapy and could furthermore improve differential diagnosis in the event pulsatility of the arterial pressure trace is lost. Methods We are reporting on 3 different complications of ECMO and their impact on arterial pulse pressure, arterial oxygen tension and regional tissue oxygenation measured by NIRS. Results Pericardial hematoma, overinflation of the lung, and tension pneumothorax may impede cardiac output during VA-ECMO and cause a loss of pulse pressure. Monitoring of regional tissue oxygenation using NIRS, in addition to arterial and mixed venous oxygen tension, may allow early recognition and treatment of ECMO complications. Conclusions Together with the appearance of a flat, non pulsatile arterial pressure trace as well as a reduction in mixed venous oxygen saturation the improvement of upper body rSO2 measured by NIRS enables timely recognition of complications that interfere with natural cardiac output during VA-ECMO.
Machine Learning for Sequences and Structured Data : Tools for Non-Experts

Project Summary This project proposes to dramatically improve the ability of people who are not experts in machine learning to design and automatically train models for analyzing and transforming sequences and other structured data such as text, signals, handwriting, and biological sequences. Working in the context of recent successes with conditional random fields (CRFs) and other conditional models of structured data, the proposed work will achieve its goals through scientific advances in model definition and combination, robust parameter estimation, and data-efficient training procedures, supported by an innovative compositional software architecture. Intellectual merit: Automatic classification and function fitting (regression) are mature techniques used in many scientific, engineering, and national security applications. Free and commercial software packages allow novice users to train with reasonable confidence of attaining useful results, and to use these results in sophisticated predictive and decision-making systems. However, for sequence and structured data problems, while task-specific machine-learning software has become increasingly available (e.g., speech recognition and genomics software tools), there are no modular, easy-to-use packages for domain experts working in science and engineering problems such as predictive data modeling of spatio-temporal patterns of brain activity or extraction of conceptual and citation networks from the scientific literature, or applications in national and homeland security such as the extraction of social networks from the open Web, or dynamically recognizing suspicious temporal patterns in network logs. The proposed work will make available for the first time a user-oriented software toolkit for integrated analysis and transformation of sequential and graph-structured data, which will be a major innovation in the data, models, and communications technical focus area. What makes this possible is the convergence of three scientific innovations in learning from structured data. First, powerful, trainable analyzers and transformers for sequences and other structured data can be built by combining simpler conditional models with general composition and product operations based on the theory of weighted automata. Second, a range of capacity-control techniques (feature induction, margin maximization, Bayesian automatic relevance determination) can be generalized to these complex models to control overfitting without the need for extensive hyperparameter adjustments. Third, the need for fully annotated training data can be reduced by combining partial evidence for multiple sequences into a single graph labeling problem. Together, these ideas provide a framework for flexibly specifying and learning parameters for multistep probabilistic transformations from complex data to their structured representations, and for designing and documenting efficient and usable software for …
Increased Resting-State Functional Connectivity in the Cingulo-Opercular Cognitive-Control Network after Intervention in Children with Reading Difficulties

Dyslexia, or reading difficulty, is characterized by slow, inaccurate reading accompanied by executive dysfunction. Reading training using the Reading Acceleration Program improves reading and executive functions in both children with dyslexia and typical readers. This improvement is associated with increased activation in and functional connectivity between the anterior cingulate cortex, part of the cingulo-opercular cognitive-control network, and the fusiform gyrus during a reading task after training. The objective of the current study was to determine whether the training also has an effect on functional connectivity of the cingulo-opercular and fronto-parietal cognitive-control networks during rest in children with dyslexia and typical readers. Fifteen children with reading difficulty and 17 typical readers (8-12 years old) were included in the study. Reading and executive functions behavioral measures and resting-state functional magnetic resonance imaging data were collected before and after reading training. Imaging data were analyzed using a graphical network-modeling tool. Both reading groups had increased reading and executive-functions scores after training, with greater gains among the dyslexia group. Training may have less effect on cognitive control in typical readers and a more direct effect on the visual area, as previously reported. Statistical analysis revealed that compared to typical readers, children with reading difficulty had significantly greater functional connectivity in the cingulo-opercular network after training, which may demonstrate the importance of cognitive control during reading in this population. These results support previous findings of increased error-monitoring activation after reading training in children with dyslexia and confirm greater gains with training in this group.
Doherty power amplifiers for handset applications

The efficiency and linearity are enhanced by a direct input dividing and an uneven power drive. An optimized envelope tracking (ET) operation of Doherty power amplifier (PA) is presented. The PA and the supply modulator are realized using a 2 μm InGaP/GaAs HBT and 0.13 μm CMOS processes, respectively. For WiMAX application, it shows a PAE of 38.6% and an EVM of 3.64% at an output power of 24.22 dBm with a gain of 24.62 dB.