Miracle-dz/UniFAR-FTUs huggingface dataset:
Decision-theoretic robot guidance for active cooperative perception

We consider the problem of sensor-aware path planning for a robot in a Networked Robot System, in particular in urban environments equipped with a network of surveillance cameras. A robot can use observations from the camera network to improve its own localization performance, but also needs to take into account the specifics of its local sensors. We model our problem in the Markov Decision Process framework, which forms a natural way to express concurrent and possibly conflicting objectives - such as reaching a goal quickly, keeping the robot localized, keeping the target in sight - each with their own priority. We show how we can successfully prioritize the different objectives in a flexible way by changing the reward function, based on the sensory needs of the system.
Design analysis, optimization and identification of optimum single-phase linear PM generator using different magnet shape for wave energy conversion

This paper presents the analysis, design optimization and identification of optimum linear permanent magnet (PM) generator for marine wave energy conversion using finite element analysis (FEA). The proposed linear generator is analyzed using different shape of magnet such as; trapezoid, triangular, and parallelogram and compared to the conventional linear PM generator. Eventually, it is identified by FEA that magnet shape augments the characteristics and overall performance of linear PM generator. Time-stepping finite element method (FEM) is employed in order to determine the electromagnetic characteristic of proposed design with all magnet shapes. The optimization has been carried out based on leading or principal dimensional ratios and parameters such as; angle of magnets θ, Φ, and β, ratio of Tmr/Tp, Tp/Tmz and ratio of Rm/Re, which have significant effect on the performance of linear PM generator. The induced-EMF, flux-linkage and magnetic flux density produced in winding and in air-gap, respectively are given and linear PM generator identified by FEA with high performance and superior characteristics is presented with its optimal values for aforementioned principal dimensional ratios and parameters.
"Web Personalization: User"s Future Request Prediction": A Survey

The web mining is very interesting research topic which supports two of the activated research areas namely Data Mining and World Wide Web. The process of extracting knowledge and information from World Wide Web is defined as web mining. This paper is a survey based on recent work in the field of Web Usage Mining, an important type of web mining. It extracts required information from web log files. The essence of user future request prediction using web log record emphasizes on current evaluation and update in web usage mining. This article views comparison and differentiation of various methods focusing on user future request prediction. Analyzing these request predictions will help the organizations to realize user's navigational behavior. We therefore present a survey of most recent work in the field of users future request predictions focusing on the overview of the development in the research.
UNIMELB at SemEval-2016 Tasks 4A and 4B: An Ensemble of Neural Networks and a Word2Vec Based Model for Sentiment Classification

This paper describes our sentiment classification system for microblog-sized documents, and documents where a topic is present. The system consists of a softvoting ensemble of a word2vec language model adapted to classification, a convolutional neural network (CNN), and a longshort term memory network (LSTM). Our main contribution consists of a way to introduce topic information into this model, by concatenating a topic embedding, consisting of the averaged word embedding for that topic, to each word embedding vector in our neural networks. When we apply our models to SemEval 2016 Task 4 subtasks A and B, we demonstrate that the ensemble performed better than any single classifier, and our method of including topic information achieves a substantial performance gain. According to results on the official test sets, our model ranked 3rd for �� PN in the message-only
Transfer of stylistic phonetic variables indexing sexuality in second language contexts

This paper reports on a study that analyzes how a sequential bilingual speaker (L1 Mexican Spanish, L2 American English) uses stylistic phonetic variation in different speech types during an interview (short answer, spontaneous speech, dramatic anecdote, reading) to construct a dynamic gay persona. There are many stylistic variables that can interact when an individual is creating a persona in an interaction, and this becomes even more complex when analyzing L1 speech as well as L2 speech as there are two collections of stylistic phonetic variables (indexical fields) interacting from two different cultural ideologies available to the interlocutors. It is problematic to assign one distinct variable to an identity, such as gay, as it homogenizes a diverse social group of individuals and underestimates members’ ability to manage perceptual salience of their identity as a gay individual based on context and social pressure(s). While the field of Lavender Linguistics (language use associated with the LGBTQ community) has shown that there are many resources that can be used to “sound gay,” this case study focuses on how a speaker stylistically creates a gay persona throughout the interview through stylistic variation of two principle variables: 1) word-final /s/ duration, and 2) center of gravity of word-final /s/.
Glucocorticoid Receptor Expression in the Spinal Cord after Traumatic Injury in Adult Rats

Methylprednisolone (MP), a glucocorticoid, is the only effective therapeutic agent used in the clinical treatment of acute spinal cord injury (SCI). MP given within 8 hr after SCI significantly improves neurological function. Although the glucocorticoid receptor (GR) is suggested to mediate MP actions, limited knowledge is available on its expression and possible function after SCI. Presently, the expression of GR was studied in a weight-drop SCI model in adult rats. Immunohistochemistry and Western blot analysis revealed an increase in GR protein expression as early as 15 min after injury. GR expression sharply increased at 4 hr (22-fold), peaked at 8 hr (56-fold), rapidly declined at 1 d, and returned to the baseline level at and after 3 d. During its peak expression, GR was localized in neural somata and dendrites but not in axons and their terminals. GR immunoreactivity was also found in oligodendrocytes and astrocytes. Interestingly, other cell types, such as endothelial cells, were GR-negative. An increase in the binding activity of nuclear proteins to the glucocorticoid responsive element was also observed after SCI, demonstrating a functional element of GR activation. Finally, colocalization of GR and tumor necrosis factor α (TNF-α), an inflammatory cytokine, was observed in neurons and glial cells, consistent with MP regulation of TNF-α in this model. Thus, the transient expression of high levels of GR after SCI may provide new insights into the anti-inflammatory action of MP.
GLUTATHIONE AS A PREDICTOR OF NEUROPSYCHOLOGICAL IMPAIRMENT IN PATIENTS WITH RELAPSING REMITTING, SECONDARY PROGRESSIVE, AND PRIMARY PROGRESSIVE MULTIPLE SCLEROSIS

iii Abstract Multiple sclerosis (MS) has long been characterized as an inflammatory disease of the central nervous system (CNS); however, recent research has suggested that neurodegenerative processes such as oxidative stress may be the primary force driving disease progression and associated neuropsychological impairment in this population. Recent work by our research group identified GSH, an important cerebral antioxidant, as a marker of oxidative stress-mediated neurodegeneration in patients with secondary progressive (SP) MS. However, the present study featured the first comparison of cerebral GSH concentrations among patients with RR, PP, and SP subtypes of MS and healthy controls. The primary aims of this study were to examine differences in GSH concentrations among subtypes of MS and to investigate whether reductions in GSH concentrations occurred in conjunction with neuropsychological impairments in processing speed, memory, and executive function. Results indicated that relative to RR patients, progressive (PP and SP) patients exhibited the largest reductions in GSH concentrations, with no significant differences between PP and SP patients. A similar pattern of outcomes was observed on the neuropsychological measures, with reductions in GSH being accompanied by a worsening of impairment in processing speed and a broadening of impairment to include deficits in learning and memory. These results support the hypothesis that even in the absence of inflammatory processes underlying acute clinical exacerbations, diffuse oxidative stress signals an ongoing neurodegenerative process that likely contributes to disease progression and cognitive decline over the course of the disease.
Using Graph Grammer to Implement Global Layout for a Visual Programming Language Generation System

VisPro is a general-purpose visual language generation system based on Reserved Graph Grammar (RGG). It can express a wide range of diagrammatic visual programming languages (VPLs). This paper presents a global layout approach used in the VisPro system. Our approach is grammar-based graph drawing, in which layout rules are embedded in the productions of RGG. Thus, the RGG formalism serves both the visual language grammar and the layout grammar. This approach is appropriate and feasible enough for graph drawing in the area of visual programming languages based on reserved graph grammars.
From lexis to syntax : the use of multi-word units in grammatical description

We describe an approach to the description of sentence struc tures based on a linear model. The sentence is segmented using automatically identified multi-word uni ts from a large corpus; recurrent elements from the corpus are matched up with fragments of the sentence . Aft r positioning the current work in relation to recent related research we present two sample an alyses and discuss the usefulness of this approach to syntactic description and possible applicatio ns.
Cigarette Smoke Induced Airway Inflammation Is Independent of NF-κB Signalling

Rationale COPD is an inflammatory lung disease largely associated with exposure to cigarette smoke (CS). The mechanism by which CS leads to the pathogenesis of COPD is currently unclear; it is known however that many of the inflammatory mediators present in the COPD lung can be produced via the actions of the transcription factor Nuclear Factor-kappaB (NF-κB) and its upstream signalling kinase, Inhibitor of κB kinase-2 (IKK-2). Therefore the NF-κB/IKK-2 signalling pathway may represent a therapeutic target to attenuate the inflammation associated with COPD. Aim To use a range of assays, genetically modified animals and pharmacological tools to determine the role of NF-κB in CS-induced airway inflammation. Methods NF-κB pathway activation was measured in pre-clinical models of CS-induced airway inflammation and in human lung tissue from COPD patients. This data was complemented by employing mice missing a functional NF-κB pathway in specific cell types (epithelial and myeloid cells) and with systemic inhibitors of IKK-2. Results We showed in an airway inflammation model known to be NF-κB-dependent that the NF-κB pathway activity assays and modulators were functional in the mouse lung. Then, using the same methods, we demonstrated that the NF-κB pathway appears not to play an important role in the inflammation observed after exposure to CS. Furthermore, assaying human lung tissue revealed that in the clinical samples there was also no increase in NF-κB pathway activation in the COPD lung, suggesting that our pre-clinical data is translational to human disease. Conclusions In this study we present compelling evidence that the IKK-2/NF-κB signalling pathway does not play a prominent role in the inflammatory response to CS exposure and that this pathway may not be important in COPD pathogenesis.
Going Underground: Bootlegging and Individual Innovative Performance

To develop innovations in large, mature organizations, individuals often have to resort to underground, "bootleg" research and development RD we argue and demonstrate empirically that the benefits of an individual's bootlegging efforts are enhanced in work units with high levels of innovative performance and which include members who are also engaged in bootlegging. However, during periods of organizational change involving formalization of the R&D process, individuals who increase their bootlegging activities are less likely to innovate. We explore the implications of these findings for our understanding of proactive and deviant creativity.
Static Relationship of Cycle Length to Reentrant Circuit Geometry

Background—Knowledge of the pathway common to both wave fronts in figure-8 reentrant circuits (ie, the isthmus) is of importance for catheter ablation to stop reentrant ventricular tachycardia. It was hypothesized that quantitative measures of reentry isthmus geometry were interrelated and could be correlated with tachycardia cycle length. Methods and Results—A canine infarct model of reentrant ventricular tachycardia in the epicardial border zone with a figure-8 pattern of conduction was used for initial analysis (experiments in 20 canine hearts with monomorphic reentry). Sinus-rhythm and reentry activation maps were constructed, and quantitative (skeletonized) geometric parameters of the isthmus and border zone were measured from the maps. Regression equations were used to determine significant correlation relationships between skeletonized variables, which can be described as follows. Tachycardia cycle length, measured from the ECG R-R interval, increases with increasing isthmus length, width, narrowest width, angle with respect to muscle fibers, and circuit path length determined by use of sinus-rhythm measurements. After this procedure, in 5 test-set experiments, tachycardia cycle length measured from the R-R interval, in combination with regression coefficients calculated from initial experiments, correctly predicted isthmus geometry (mean estimated/actual isthmus overlap 70.5%). Also, the circuit path length determined with sinus-rhythm measurements correctly estimated the tachycardia cycle length (mean error 6.2±2.5 ms). Conclusions—Correlation relationships derived from measurements using reentry and sinus-rhythm activation maps are useful to assess isthmus geometry on the basis of tachycardia cycle length. Such estimates may improve catheter ablation site targeting during clinical electrophysiological study.
HAND MOVEMENT IMPROVEMENT ON VISUAL TARGET TRACKING BY MODEL-BASED COMPENSATOR

Abstract Brain dysfunction in the cerebral cortex, cerebellum and/or basal ganglia causes serious movement disorders such as cerebellar ataxia, Parkinson disease and so on. Compensation of hand movement by adding an external force will recover the motor function and will be helpful for improving the quality of patients' daily life. This paper proposes a method for compensating human hand movement on visual target tracking by adding an assistant force. Mathematical model was obtained from the measurement data of visual target tracking for each subject, and the compensator was constructed based on the model. Effectiveness of the compensation method was investigated through the experiment.
Subqueries in SPARQL

Subqueries are a poweful feature which allows to enforce reuse, composition, rewriting and optimization in a query language. In this paper we perform a comprehensive study of the incorporation of subqueries into SPARQL. We consider the many possible choices as suggested by the experience of similar languages, as well as features that developers are incorporating and/or experimenting with. Our study includes the discussion in the SPARQL case of common design issues concerning subqueries (i.e., query correlation, scope of datasets, and optimization), show the interplay among them, and study their implications in terms of expressive power. Based on this study, we present an extension of SPARQL, with syntax and formal semantics, which incorporates all knwon types of subqueries in a modular fashion and preserving the original semantics.
Studies on cell adhesion and recognition. I. Extent and specificity of cell adhesion triggered by carbohydrate-reactive proteins (glycosidases and lectins) and by fibronectin

The extent and the specificity of the initial cell attachment induced by various proteins coated on plastic surfaces have been studied with the following results: (a) Cell adhesion on the surfaces coated with sialidase and beta-galactosidase was as strong as on concanavalin A and limulus lectin-coated surfaces and the reactions were strongly inhibited by glycosidase inhibitors or by competitive substrates. The adhesion on sialidase was inhibited by 2-deoxy-2,3-dehydro-N- acetylneuraminic acid and by polysialoganglioside (GT1b) at low concentration (0.05-0.1 mM). The cell adhesion on beta-galactosidase coat was inhibited by 1,4-D-galactonolactone and beta-methylgalactoside but not by alpha-methylgalactoside. Thus, the initiation of cell adhesion on glycosidase surfaces could be mediated through the interactions of the specific binding sites of the enzyme surface with the cell surface substrates under physiological conditions. (b) Cell adhesion on various lectins could be blocked by various competing monosaccharides at the concentrations similar to the inhibitory concentrations for binding of lectins from solution to the cells. (c) Cell adhesion on fibronectin surfaces as well as on gelatin-coated surfaces was equally inhibited by GT1b at relatively high concentrations (0.25-0.5 mM). Lower concentrations of GT1b (0.05-0.1 mM) inhibited the cell adhesion on surfaces of Limulus lectin and sialidase. It is suggested that the cell adhesion mediated by fibronectin is based on yet unknown interactions in contrast to a specific cell adhesion through glycosidases and lectins.
A feasibility study for developing an emotional control system through brain computer interface

A Brain Computer Interface (BCI) is a direct communication channel between a human brain and an outside environment. Through this interface, users' can send their messages or commands without any muscle movement, but through the thought process. Electroencephalogram (EEG) is used to measure the brain response which is generated by billions of nerve cells called neurons. This EEG activity is recorded through electrodes placed on the scalp. EEG signals are conventionally categorized into different rhythms based on their frequencies ranging from less than 0.5 Hz to above 30 Hz categorized as Delta, Theta, Alpha, Beta and Gamma waves. The main objectives of BCI systems are to translate the brain signals into control signals and use them to control activities on particular application domain. The objective of this paper is to study the feasibility of developing a BCI system for recognizing and controlling the stress level of a person. The emotional level of the subject will be recognized based on the brain EEG signals captured and analyzed through the Valence-Arousal model. Further, based on the emotional status of the person, corresponding music shall be played to reduce the stress level of a person, thereby controlling the emotional level of the subject. Experiments have been carried out in the Brain Computer Interface Research Lab and the results show a significant feasibility in developing an emotional control system.
Turning the tortoise to the hare: an alternative perspective on event handling in SDN

OpenFlow, the most popular software-defined networking proposal, decouples control from data path, and pushes control functionality to a software-based controller with a centralized view of the network. Such a design enables change and innovation by simplifying the implementation of control applications. A historically narrow interpretation of control and data planes, however, has led to unnecessary limitations on network applications that can be supported by OpenFlow. More specifically, applications handling frequent events are pushed outside the scope of SDN as: i) the controller cannot tolerate the high load; and ii) changing data path ASIC is an extremely costly and long process. In this paper, we present our perspective on this challenge. We believe these are non-intrinsic limitations that can simply be viewed as design challenges in areas such as state abstraction, event propagation, parallelism, and placement of network applications. We show how a consolidated software platform can be used to address these challenges, and how this design leads to a cohesive framework capable of accommodating applications with frequent events.
Methodology for guaranteed and robust high level fusion performance: a literature study

Abstract (not more than 200 words) A currently hot topic in Information Fusion research is fusion performance, including relevance, reliability, robustness, and trustworthiness, in particular for higher level fusion methods such as situation and impact refinement. Unless methodologies ar e found and generally applied which enable us to achieve and demonstrate trustworthiness, chances are slim that future commanders would be willing to trust high-level fusion systems. On the other hand, quite extensive work has been performed in other fields during the last two decades, in particular in risk a nalysis and robust Bayesian analysis, which indicates that robust and trustworthy behaviour may in principle be achieved from probabili stic simulations and therefore from information fusion methods in decision support systems. It is likely, however, that complex syst ems which were not designed from the outset to satisfy specified trustworthiness and robustness criteria will be hard or impossible to validate later using this methodology. Thus we believe that this partly formal research needs to be evaluated and, if found appropriate, adapted for use in informatio n fusion systems design. Since it is not yet known for certain if or how these new approaches can be applied to information fusio n algorithms and systems, we perceive an urgent need to start serious research and education in this area. We know that the answe rto questions of reliability and trustworthiness will not be simple; instead, they will to a large degree have to evolve over ti me through scientific debate. We also know many situations where computer-supported military decision making works well, but we do not know how to deal with problems near the fluid boundary between those situations we know how to automate and those we believe must be reserved for human decision-making.