Miracle-dz/UniFAR-FTUs huggingface dataset:
Opinion Dynamics Modeling for Movie Review Transcripts Classification with Hidden Conditional Random Fields

In this paper, the main goal is to detect a movie reviewer's opinion using hidden conditional random fields. This model allows us to capture the dynamics of the reviewer's opinion in the transcripts of long unsegmented audio reviews that are analyzed by our system. High level linguistic features are computed at the level of inter-pausal segments. The features include syntactic features, a statistical word embedding model and subjectivity lexicons. The proposed system is evaluated on the ICT-MMMO corpus. We obtain a F1-score of 82\%, which is better than logistic regression and recurrent neural network approaches. We also offer a discussion that sheds some light on the capacity of our system to adapt the word embedding model learned from general written texts data to spoken movie reviews and thus model the dynamics of the opinion.
A highly effective security model for privacy preserving on cloud storage

Cloud computing is presently one of the key technologies for most IT applications. However, it frequently suffers from various security threats on data retrieval from cloud storage due to the sharing of resources in the public domain. Though several attempts have been made to address those concerns by cloud service providers, they are either too complicated or too costly to implement in order to obtain those promising solutions. The present model provides a simple but effective working process for those stakeholders. It is implemented by applying OTP associated with SMS for timely system access and secured file decryption in combination. Users are required to gain access for secured files in cloud storage by strictly following the procedure in prescribed steps. When a hacking attempt is tried, unless the right code could be given within the right time, including the right key for decryption, it would end up in futility. We have verified our work with several experimental attempts, showing that the privacy security could be preserved in a quite promising manner.
Frequency-Domain Double-Talk Detection Based on the Gaussian Mixture Model

In this letter, we propose a novel frequency-domain approach to double-talk detection (DTD) based on the Gaussian mixture model (GMM). In contrast to a previous approach based on a simple and heuristic decision rule utilizing time-domain cross-correlations, GMM is applied to a set of feature vectors extracted from the frequency-domain cross-correlation coefficients. Performance of the proposed approach is evaluated through objective tests under various environments, and better results are obtained as compared to the time-domain method.
Circulating MicroRNA-223 Serum Levels Do Not Predict Sepsis or Survival in Patients with Critical Illness

Background and Aims. Dysregulation of miR-223 was recently linked to various diseases associated with systemic inflammatory responses such as type 2 diabetes, cancer, and bacterial infections. However, contradictory results are available on potential alterations of miR-223 serum levels during sepsis. We thus aimed to evaluate the diagnostic and prognostic value of miR-223 serum concentrations in patients with critical illness and sepsis. Methods. We used i.v. injection of lipopolysaccharide (LPS) as well as cecal pole ligation and puncture (CLP) for induction of polymicrobial sepsis in mice and measured alterations in serum levels of miR-223. These results from mice were translated into a large and well-characterized cohort of critically ill patients admitted to the medical intensive care unit (ICU). Finally, results from analysis in patients were correlated with clinical data and extensive sets of routine and experimental biomarkers. Results. Although LPS injection induced moderately elevated serum miR-223 levels in mice, no significant alterations in miR-223 serum levels were found in mice after CLP-induced sepsis. In accordance with these results from animal models, serum miR-223 levels did not differ between critically ill patients and healthy controls. However, ICU patients with more severe disease (APACHE-II score) showed moderately reduced circulating miR-223. Strikingly, no differences in miR-223 levels were found in critically ill patients with or without sepsis, and serum levels of miR-223 did not correlate with classical markers of inflammation or bacterial infection. Finally, low miR-223 serum levels were moderately associated with an unfavorable prognosis of patients during the ICU treatment but did not predict long-term mortality. Conclusion. Recent reports on alterations in miR-223 serum levels during sepsis revealed contradictory results, preventing a potential use of this miRNA in clinical routine. We clearly show that miR-223 serum levels do not reflect the presence of sepsis neither in mouse models nor in a large cohort of ICU patients and do not indicate clinical outcome of critically ill patients. Thus miR-223 serum levels should not be used as a biomarker in this setting.
Graph-based Rating Prediction using Eigenvector Centrality

The most of recommendation systems rely on the statistical correlations of the past explicitly given user rating for items (e.g. collaborative filtering). However, in conditions of insufficient data of past rating activities, these systems are facing difficulties in rating prediction, this situation is commonly known as the cold-start problem. This paper describes how graph-based represendation and Social Network Analysis can be used to help dealing with cold-start problem. We proposed a method to predict user rating based on the hypotesis that the rating of the node in the network corresponded to the rating of the most important nodes which are connected to it. The proposed method has been particularly applied to three MovieLens datasets to evaluate rating predition performance. Obtained results showed competitiveness of our method.
Shrinkage based features for slot tagging with conditional random fields

In this paper we propose a set of class-based features that are generated in an unsupservised fashion to improve slot tagging with Conditional Random Fields (CRFs). The feature generation is based on the idea behind shrinkage based language models, where shrinking the sum of parameter magnitudes in an exponential model tends to improve performance. We use these features with CRFs and show that they consistently improve the slot tagging performance against baselines on several natural language understanding tasks. Since the proposed features are generated in an unsupervised manner without significant computational overhead, the improvements in performance comes for free and we expect that the same features may result in gains in other tagging tasks.
Characterization of Somatostatin Receptor Subtype 2 Expression in Stably Transfected A-427 Human Cancer Cells

Although radiolabeled somatostatin analogs have become highly prevalent in the diagnosis and treatment of somatostatin receptor subtype (sst)-positive tumors, there are relatively few options with respect to sst-positive tumor cell lines and animal models. It would be highly beneficial, particularly for therapeutic purposes, to have several clones of one human sst2-positive cell line that express a range of sst2 concentrations for evaluating the dose response and intracellular processing of radiolabeled somatostatin analogs. The human non–small cell lung cancer line A-427 was stably transfected with a hemagglutinin-tagged human sst2. Expression of the receptor was evaluated in vitro using flow cytometry, saturation binding analysis, internalization assays, and quantitative polymerase chain reaction. The receptor expression was also validated in an in vivo mouse model in biodistribution and micro–positron emission tomography (microPET) studies using the somatostatin analog octreotide (OC), which was linked to the 64Cu chelator 1,4,8,11-tetraazacyclotetradecane-1,4,8,11-tetraacetic acid (TETA), or 64Cu-TETA-OC. Stable clones were isolated, and four clones (2, 4, 5, and 7) were chosen for further examination. In vitro assays showed that clone 4 had no expression of sst2, whereas the others had various levels in the order of 7 > 2 > 5. Biodistribution studies with 64Cu-TETA-OC showed the same rank order, with tumor uptake of the clones ranging from 0.8 to 6.5% injected dose/g. These studies showed that there was a strong correlation among the in vitro assays and between the in vitro assays and the biodistribution. MicroPET confirmed significant uptake of 64Cu-TETA-OC in clone 7 and background uptake in clone 4. These studies show that clones of a human cell line can be produced expressing various levels of sst2 that should be useful for the future evaluation of radiolabeled somatostatin analogs.
A Framework for Rapid Prototyping of Multimodal Interaction Concepts

Ubiquitous systems provide users with various possibilities of interacting with applications and components using different modalities and devices. To offer the most appropriate mode of interaction in a given context, various types of sensors are combined to create interactive applications. Thus, the need for integrated development and evaluation of suitable interaction concepts for ubiquitous systems increases. Creation of prototypes for interactions is a complex and time consuming part of iterative software engineering processes, currently not well supported by tools as prototypes are considered to be short-living software artifacts. In this paper, we introduce the framework Connect that enables rapid prototyping of interaction concepts with a focus on software engineering aspects. The framework allows the definition and modification of event-to-action mappings for arbitrary interaction devices and applications. By applying Connect, model-based prototypes of multimodal interaction concepts involving multiple devices can be created, evaluated and refined during the entire engineering process.
Advances in Multilingual Text Retrieval

Multilingual text retrieval extends the basic monolingual detection task to include retrieving relevant documents in languages other than the query language. The task therefore merges efforts in machine translation with efforts in text retrieval, but the machine translation component may be substantially simplified due to some basic assumptions about the design and implementation of high-performance text retrieval systems. A primary consideration is that most modern text retrieval systems regard queries and documents as unordered "bags" of words. The translation of an unordered set of terms is therefore approximately the translation of the terms themselves. Although a linearity assumption such as this breaks down when considering phrasal elements in most languages, it is reasonably accurate for many terms and becomes increasingly accurate at the sentence level and above.
Stepwise Morphological and Functional Maturation of Mechanotransduction in Rat Outer Hair Cells

Inner ear mechanosensory hair cells convert mechanical vibrations into electrical signals via the coordinated interaction of multiple proteins precisely positioned within the sensory hair bundle. Present work identifies the time course for the acquisition and maturation of mechanoelectric transduction (MET) in rat cochlea outer hair cells maintained in organotypic cultures. A spatiotemporal developmental progression was observed morphologically and functionally with basal cochlea maturation preceding apical cochlea by 2–3 d in all measured properties. The fraction of mechanosensitive cells increased rapidly, with a midpoint at postnatal day 0 for basal cells, and correlated with myosin IIIa immunoreactivity. MET current magnitude increased over several days. Adaptation lagged the onset of transduction by a day and matured more slowly, overlapping but preceding the rise in myosin Ic immunoreactivity. Less than ∼25% of myosin Ic expression was required for the mature adaptation response, suggesting multiple roles for this protein in hair bundle function. Directional sensitivity, lacking in immature responses, developed rapidly and correlated with the pruning of radial links and an increase in tenting of stereociliary tips. Morphological and electrophysiological data support a hypothesis in which key elements arrive independently at the site of MET, with a mature response occurring as membrane tension increases, likely by the increased tensioning of the tip link with the onset of adaptation. Organotypic cultures developed normal, tonotopically specific, MET response properties, suggesting that maturation was not influenced significantly by external factors such as innervation, endolymph, normal mechanical stimulation, or an intact organ of Corti.
Coordination Mechanisms for Self-Organizing Femtocells in Two-Tier Coexistence Scenarios

We propose and investigate distributed coordination mechanisms for controlling the co-channel interference generated by standalone femtocells in two-tier coexistence scenarios consisting of macrocells underlaid with short-range small cells. The rationale behind employing such mechanism is to opportunistically reuse resources without compromising ongoing transmissions on overlaid macrocells, while still guaranteeing Quality of Service in both tiers. Stochastic geometry is used to model network deployments, while higher-order statistics through the cumulants concept is utilized to characterize the probability distribution of the aggregate interference at the tagged receiver. To conduct our studies, we consider a shadowed fading channel model incorporating log-normal shadowing and Nakagami fading. In addition, various network algorithms, such as power control and frequency (re)allocation, are included in the analytical framework. To evaluate the performance of the proposed solutions, we also derive closed-form expressions for the outage probability and average spectral efficiency with respect to the tagged receiver. Results show that the analytical framework matches well with numerical results obtained from Monte Carlo simulations, and that the coordination mechanisms substantially improve the performance of overlaid macrocell networks, while also benefiting femtocells.
Gaps Between Actual and Preferred Career Paths Among Professional Employees

Organizations are increasingly opting to offer alternative career paths to the traditional managerial ladder (particularly, a technical ladder). Although research has mainly focused on differences between the managerial and technical paths with regard to rewards and prestige, our study focuses on gaps between employees’ actual (current) and preferred career paths, that is, being on the technical path while preferring the managerial path and vice versa. We examine how employees experiencing career path gaps compare with employees experiencing career path fit, in terms of self-rated performance and burnout. The results, based on data from 210 professional employees working in four global high-technology companies, suggest that performance levels are lowest among employees who are currently on the technical career path but would prefer the managerial path, whereas burnout levels are lowest among employees experiencing career path fit. Furthermore, among employees experiencing the former, career path gap, performance is lower when supervisor support is high.
Center Block Duplication Detection and Indexing for Efficient Web Information Retrieval

Duplicated information in today's Web has serious negative impact to search engines in that it increases the size of the index and results in low efficiency for Web information retrieval. A large amount of Web content duplication happens at block level in addition to page level. Besides, when searching the web, in most cases the desired information is located at the center block of a page. Based on these two observations, we propose a block level duplication detection algorithm, and index center blocks instead of entire Web pages for Web information retrieval. Experiments show that these strategies can effectively reduce index size and indexing time without sacrificing the effectiveness of Web information retrieval.
The Sociology of the Police

In 1997 and 1998 several books were published in French on the sociology of the police. Two of these works, both published in Quebec, have essentially practical or programmatic aims; a collection in homage to Lode Van Outrive, published in Belgium, contains only a few articles on the police, some of outstanding quality. Finally, the work published in France by D. Monjardet, the most important French sociologist of the police, offers a remarkable synthesis of twelve years of research. Using a truly exemplary sociological approach, Monjardet analyzes the characteristics of police work and the police profession in France, demonstrating the weakness of the political authority's control over the police and elucidating the mechanisms that give the police its considerable operational freedom within society. At present Monjardet's work is the main French reference in this field, one that is developing considerably in France.
Efficient Mining of Maximal Sequential Patterns Using Multiple Samples

In this paper, we propose a new algorithm, named MSPX, which mines maximal sequential patterns by using multiple samples to effectively exclude infrequent candidates. MSPX begins with a bottom-up search. But at each pass, instead of processing all candidates, it always tries to find most of the infrequent ones effectively by counting only the potentially infrequent candidates against the whole database. After removing verified infrequent candidates, the remaining candidates are used to generate new candidates. Finally, with a topdown search, all the maximal frequent sequences can be identified efficiently. Sampling technique is used at each pass to distinguish potentially infrequent candidates. How to increase the minimum support level for the mining of samples to estimate if candidates could be infrequent is analyzed theoretically. Due to the supersequence frequence based pruning, MSPX reduces much more search space than other algorithms. Unlike the traditional single-sample methods proposed for mining frequent itemsets, MSPX uses multiple samples. Thus, it can avoid or alleviate some problems inherent in the single-sample methods. Our experiments show MSPX has very good performance and better scalability than other algorithms. Moreover, even though MSPX uses sampling, the variance of its performance is very small in multiple runs for the same task.
Spatiotemporal brain mapping of spatial attention effects on pattern‐reversal ERPs

Recordings of event‐related potentials (ERPs) were combined with structural and functional magnetic resonance imaging (fMRI) to investigate the timing and localization of stimulus selection processes during visual‐spatial attention to pattern‐reversing gratings. Pattern reversals were presented in random order to the left and right visual fields at a rapid rate, while subjects attended to the reversals in one field at a time. On separate runs, stimuli were presented in the upper and lower visual quadrants. The earliest ERP component (C1, peaking at around 80 ms), which inverted in polarity for upper versus lower field stimuli and was localized in or near visual area V1, was not modulated by attention. In the latency range 80–250 ms, multiple components were elicited that were increased in amplitude by attention and were colocalized with fMRI activations in specific visual cortical areas. The principal anatomical sources of these attention‐sensitive components were localized by fMRI‐seeded dipole modeling as follows: P1 (ca. 100 ms—source in motion‐sensitive area MT+), C2 (ca. 130 ms—same source as C1), N1a (ca. 145 ms—source in horizontal intraparietal sulcus), N1b (ca. 165 ms—source in fusiform gyrus, area V4/V8), N1c (ca. 180 ms—source in posterior intraparietal sulcus, area V3A), and P2 (ca. 220 ms—multiple sources, including parieto‐occipital sulcus, area V6). These results support the hypothesis that spatial attention acts to amplify both feed‐forward and feedback signals in multiple visual areas of both the dorsal and ventral streams of processing. Hum Brain Mapp, 2011. © 2011 Wiley‐Liss, Inc.
Special Issue: Progress of the Knowledge Grid

This special issue contains five papers [1–5] reflecting the progress of the Knowledge Grid [6]. Most of them were selected from the First International Conference on Semantics, Knowledge and Grid (SKG2005; http://www.knowledgegrid.net), which is currently the unique forum crossing the areas of knowledge sharing, semantic networking and Grid computing. The first paper [1] proposes a distributed end-host multicast algorithm for efficient multicast query within the decentralized Knowledge Grid. In [2], a solution is proposed to top-K join queries in P2P networks based on semantic links. It can be used to construct a semantic overlay over the Knowledge Grid to support advanced intelligent applications. It provides a significant method for realizing a decentralized Knowledge Grid by semantic P2P data management. In [3], a Grid-based software platform, MS-Analyzer, is presented for the integrated management and analysis of spectra data. In [5], a user reputation model for a user-interactive question answering system is presented. Knowledge flow is the distinguished characteristic of the Knowledge Grid [6]. A knowledge flow is invisible, but it plays an important role in ordering knowledge exchange in teamwork. It can help achieve effective team knowledge management by modeling, optimizing, monitoring and controlling the operation of knowledge flow processes. In [4], the notion of potential knowledge energy is proposed as the driving force of forming an autonomous knowledge flow network, and the underlying principles are explored. Knowing these principles helps teams and the support systems improve cooperation by monitoring the knowledge energy of nodes, by evaluating and adjusting knowledge flows, and by adopting appropriate strategies. An effective knowledge flow network management mechanism can help improve the efficiency of knowledge-intensive distributed teamwork. The research on knowledge flow will form a significant contribution to the decentralized Knowledge Grid. We hope this special issue can make a significant contribution to push the development of the Knowledge Grid area.
Model Predictive Control of Nonholonomic Mobile Robots Without Stabilizing Constraints and Costs

The problem of steering a nonholonomic mobile robot to a desired position and orientation is considered. In this paper, a model predictive control (MPC) scheme based on tailored nonquadratic stage cost is proposed to fulfill this control task. We rigorously prove asymptotic stability while neither stabilizing constraints nor costs are used. To this end, we first design suitable maneuvers to construct bounds on the value function. Second, these bounds are exploited to determine a prediction horizon length such that the asymptotic stability of the MPC closed loop is guaranteed. Finally, numerical simulations are conducted to explain the necessity of having nonquadratic running costs.