Miracle-dz/UniFAR-FTUs huggingface dataset:
Using contextual analysis for news event detection

The rapidly growing amount of newswire stories stored in electronic devices raises new challenges for information retrieval technology. Traditional query‐driven retrieval is not suitable for generic queries. It is desirable to have an intelligent system to automatically locate topically related events or topics in a continuous stream of newswire stories. This is the goal of automatic event detection. We propose a new approach to performing event detection from multilingual newswire stories. Unlike traditional methods which employ simple keyword matching, our method makes use of concept terms and named entities such as person, location, and organization names. Concept terms of a story are derived from statistical context analysis between sentences in the news story and stories in the concept database. We have conducted a set of experiments to study the effectiveness of our approach. The results show that the performance of detection using concept terms together with story keywords is better than traditional methods which only use keyword representation. © 2001 John Wiley & Sons, Inc.
Recent Insights on Prevalence and Corelations of Hypoactive Delirium

Delirium is a complex neuropsychiatric syndrome which is common in all medical settings. It often goes unrecognized due to difficulties in the detection of its hypoactive variant. This review aims to provide an up-to-date account on recent research on hypoactive delirium (HD). Thirty-eight studies, which were conducted in various clinical settings, including the Intensive Care Unit (ICU), were included in this review. Those studies involved recent research that has been published during the last 6 years. Prevalence of HD was found to vary considerably among different settings. HD seems to be more common in critically ill patients and less common in patients examined by consultation-liaison psychiatric services and in mixed patient populations. The presence of HD in ICU patients was associated with higher short- and long-term mortality and other adverse outcomes, but no such association was reported in other settings. Research on other possible associations of HD with clinical variables and on symptom presentation yielded inconclusive results, although there is some evidence for a possible association of HD with benzodiazepine use. There are several methodological issues that need to be addressed by future research. Future studies should examine HD in the primary care setting; treatment interventions should also be the objective of future research.
An empirical research on knowledge management orientation and organizational performance: the mediating role of organizational innovation

A great research suggests that effective knowledge management can strengthen organizational performance. But empirical research is very scarce. The concept of knowledge management orientation based on knowledge and resource views presents the degree to which organizations implement knowledge management.This paper mainly analyzes the relationships among knowledge management orientation, organizational innovation and organizational performance. 227 organizations in china were selected as the sample base for an empirical test. The study found that knowledge management orientation plays positive role in promoting organizational performance. Organizational innovation partially mediates the relationship between knowledge management orientation and organizational performance. In addition, this paper tests the effects of the four dimensions (organizational memory, knowledge sharing, knowledge absorption, knowledge receptivity) of knowledge management orientation on the two dimensions (administrative and technical innovations) of organizational innovation respectivelyand the effects of the two dimensions of organizational innovation on organizational performance. The results show that the effects of organizational memory on organizational performance and administrative innovation were not significant. Other effects were significant. The implications of the research findings, limitations of this study and suggestions for future research were also discussed. Key words: Knowledge management, knowledge management orientation, organizational innovation, organizational performance.
Evaluating the Privacy Risk of User-Shared Images

User-shared images are shared on social media about a user’s life and interests that are widely accessible to others due to their sharing nature. Unlike for online profiles and social graphs, most users are unaware of the privacy risks relating to shared images, as they do not directly disclose characteristics such as gender and origin. Recently, however, user-shared images have been proven to be an accessible alternative to social graphs for online friendship recommendation and gender identification. This article evaluates 1.6M user-shared images from an image-oriented social network, Fotolog, and concludes how they can create privacy risks by proposing a system for de-anonymization, as well as inferring information on online profiles with the user-shared images. It is concluded that given user-shared images, using social graphs is 2 and 2.5 times more effective in de-anonymization than using origins or genders. With two showcases, it is also proven that using user-shared images is effective in online friendship recommendation, gender identification, and origin inference. To the best of our knowledge, this is the first article to evaluate the privacy issue qualitatively with big multimedia data from a real social network.
A skin detection algorithm based on discrete Cosine transform and generalized Gaussian density

In this paper, we propose a highly efficient algorithm to model the human skin color. The underlying algorithm involves generating a discrete Cosine transform (DCT) at each pixel location, using the surrounding points. These DCT coefficients are assumed to follow a generalized Gaussian distribution (GGD). Next, the model parameters are estimated using the maximum-likelihood (ML) criterion applied to a set of training skin samples. Finally, each pixel is classified as skin or the opposite if its likelihood ratio is above some threshold. The experimental results show that our model avoids excessive false detection while still retaining a high degree of correct detection.
Treatment by human recombinant soluble TNF receptor of pulmonary fibrosis induced by bleomycin or silica in mice.

Intratracheal instillation of bleomycin (0.08 U) or silica (2 mg) to mice leads, after 15 days, to a patchy pulmonary fibrosis associated with a significant increase of the lung hydroxyproline. Since tumour necrosis factor (TNF) seems to be an important mediator in pulmonary fibrosis, we wondered whether this fibrosis might be prevented by a new TNF-alpha antagonist. Infusion of a 55 kD human recombinant soluble TNF receptor rsTNFR-beta, at a rate of 20 micrograms.day-1, prevented the bleomycin/silica induced increase of lung hydroxyproline content, as measured 15 days after instillation. Infusion of rsTNFR-beta was also effective in the treatment of an established fibrosis, i.e. administered 25 or more days after instillation of bleomycin or silica, since it reduced lung collagen content. Recombinant soluble TNFR-beta had no significant influence on the number of cells, mostly macrophages, recovered by bronchoalveolar lavage. The examination of histological sections indicated that the rsTNFR-beta reduced the proportion of areas of damaged lung and, in silicosis, the formation of nodules with a rich collagen content. This study suggests that rsTNFR-beta might be useful in the therapy of pulmonary fibrosis.
Involvement of a Novel Genistein-Inducible Multidrug Efflux Pump of Bradyrhizobium japonicum Early in the Interaction with Glycine max (L.) Merr

The early molecular dialogue between soybean and the bacterium Bradyrhizobium japonicum is crucial for triggering their symbiotic interaction. Here we found a single large genomic locus that is widely separated from the symbiosis island and was conspicuously induced within minutes after the addition of genistein. This locus (named BjG30) contains genes for the multidrug efflux pump, TetR family transcriptional regulator, and polyhydroxybutyrate (PHB) metabolism. The induction of BjG30 by genistein was competitively inhibited by daidzein, although both genistein and daidzein are soybean-derived inducers of nodulation (nod) genes. Such a differential expression pattern is also observed in some legume-derived flavonoids, which structurally differ in the hydroxy/deoxy group at the 5-position. In addition, not only did the induction start far in advance of nodW and nodD1 after the addition of genistein, but the levels showed distinct concentration dependence, indicating that the induction pattern of BjG30 is completely different from that of nod genes. The deletion of genes encoding either the multidrug efflux pump or PHB metabolism, especially the former, resulted in defective nodulation performance and nitrogen-fixing capability. Taken together, these results indicate that BjG30, and especially its multidrug efflux pump, may play a key role in the early stage of symbiosis by balancing the dual functions of genistein as both a nod gene inducer and toxicant.
Biological and Psychosocial Factors Affect Linguistic and Cognitive Development Differently : A Twin

Although twin studies clearly demonstrate that genetic factors play an important role in language acquisition, some twin studies suggest that adverse prenatal (Koeppen-Schomerus et al., 2000) or postnatal (Turkheimer et al., 2003) environments can overshadow the effects of genetic factors. The current study investigates, in the same group of twins, the extent to which prenatal and postnatal environmental factors interact with genetic factors to affect linguistic and nonlinguistic development. The study included 145 sets of samesex monozygotic twin pairs and 238 sets of same-sex dizygotic twin pairs. The twins’ development was assessed using Bricker & Squire’s (1999) Ages & Stages language, cognitive, gross motor, fine motor, and social tests. Twins were divided into two prenatal risk groups based on gestational age at birth (GA). Twins were also divided into two postnatal risk groups based on socioeconomic status (SES). Genetic factors accounted for 5 times more of the variance for high GA twins’ language scores than for low GA twins’ language scores, whereas genetic factors affected both GA groups’ cognitive scores similarly. In striking contrast, for cognitive scores, genetic factors accounted for 3 times more of the variance for high SES twins than for low SES twins, whereas for language scores, genetic factors affected high and low SES twins virtually identically. Put simply, perinatal environment affects linguistic development and postnatal environment affects cognitive development. Because prenatal factors are overwhelming biological, whereas postnatal factors tend to be psychosocial, these results support nativist/biological theories of language acquisition and call into question empiricist/emergentist theories of language development.
Unequal Protection of Video Streaming through Adaptive Modulation with a Trizone Buffer over Bluetooth Enhanced Data Rate

Bluetooth enhanced data rate wireless channel can support higher-quality video streams compared to previous versions of Bluetooth. Packet loss when transmitting compressed data has an effect on the delivered video quality that endures over multiple frames. To reduce the impact of radio frequency noise and interference, this paper proposes adaptive modulation based on content type at the video frame level and content importance at the macroblock level. Because the bit rate of protected data is reduced, the paper proposes buffer management to reduce the risk of buffer overflow. A trizone buffer is introduced, with a varying unequal protection policy in each zone. Application of this policy together with adaptive modulation results in up to 4 dB improvement in objective video quality compared to fixed rate scheme for an additive white Gaussian noise channel and around 10 dB for a Gilbert-Elliott channel. The paper also reports a consistent improvement in video quality over a scheme that adapts to channel conditions by varying the data rate without accounting for the video frame packet type or buffer congestion.
A Co-Occurrence Matrix Derived Measure of Classifiability

A n-dimensional classification problem may be visualized in (n+1) dimensions using the class label as the (n + 1)th dimension. In such visualization, the class label provides a surface which is smooth in regions where classes are non-interlaced and rough in regions where classes are interlaced. The texture of the “class label surface” thus provides an intuitive measure of pattern classifiability. Motivated by this, we propose a measure of classifiability derived from the co-occurrence matrix of labeled classification data. We establish Bayes-sense optimality of the proposed measure of classifiability and present some experimental results based on a simple algorithm to compute the proposed classifiability measure.
A Context-Specific Role for Retinoblastoma Protein-Dependent Negative Growth Control in Suppressing Mammary Tumorigenesis

Background The ability to respond to anti-growth signals is critical to maintain tissue homeostasis and loss of this negative growth control safeguard is considered a hallmark of cancer. Negative growth regulation generally occurs during the G0/G1 phase of the cell cycle, yet the redundancy and complexity among components of this regulatory network has made it difficult to discern how negative growth cues protect cells from aberrant proliferation. Methodology/Principal Findings The retinoblastoma protein (pRB) acts as the final barrier to prevent cells from entering into the cell cycle. By introducing subtle changes in the endogenous mouse Rb1 gene (Rb1ΔL), we have previously shown that interactions at the LXCXE binding cleft are necessary for the proper response to anti-growth signals such as DNA damage and TGF-β, with minimal effects on overall development. This disrupts the balance of pro- and anti-growth signals in mammary epithelium of Rb1ΔL/ΔL mice. Here we show that Rb1ΔL/ΔL mice are more prone to mammary tumors in the Wap-p53R172H transgenic background indicating that negative growth regulation is important for tumor suppression in these mice. In contrast, the same defect in anti-growth control has no impact on Neu-induced mammary tumorigenesis. Conclusions/Significance Our work demonstrates that negative growth control by pRB acts as a crucial barrier against oncogenic transformation. Strikingly, our data also reveals that this tumor suppressive effect is context-dependent.
An Analysis of Epidemic Information Access in the PeopleNet Architecture

In this paper, we look at the performance of epidemic information access in PeopleNet-like networks. PeopleNet is based on the idea of wireless virtual social networking, which mimics the way people find information via their social contacts. The basic idea is that people want easy access to information. Information, which is in high demand, can be collected and stored in a central repository or database, e.g., libraries, archives, and web sites. However, there are certain kinds of information which can neither be quantified nor categorized nicely. These kinds of information are typically location specific, community specific and even time-specific and are often found by asking your family, friends, colleagues or people you trust. Our architecture for PeopleNet consists of a multi-tiered architecture of mobile devices and access points, which allow users to navigate for information. We study and simulate the performance of an epidemic style of content dissemination and access in the PeopleNet networks. Our initial analysis indicates that PeopleNet can result in several orders of magnitude improvements over other naive proposals for wireless virtual social networking.
Security of Chien's efficient time-bound hierarchical key assignment scheme

Recently, Chien proposed a time-bound hierarchical key assignment scheme based on tamper-resistant devices. Without public key cryptography, Chien's scheme greatly reduces computation load and implementation cost. In this paper, we show that Chien's scheme is insecure against a collusion attack whereby three users conspire to access some secret class keys that they should not know according to Chien's scheme.
Using game theory and Bayesian networks to optimize cooperation in ad hoc wireless networks

Infrastructure sharing has been recently investigated as a viable solution to increase the performance of coexisting wireless networks. In this paper, we analyze a scenario where two wireless networks are willing to share some of their nodes to gain benefits in terms of lower packet delivery delay and reduced loss probability. Bayesian Network analysis is exploited to compute the correlation between local parameters and overall performance, whereas the selection of the nodes to share is made by means of a game theoretic approach. Our results are then validated through use of a system level simulator, which shows that an accurate selection of the shared nodes can significantly increase the performance gain with respect to a random selection scheme.
Research on Component Behavior Protocols Mismatch Detection and Limited Assembly

As an effective specification method of supporting component design, assembly, verification and runtime monitoring, the component behavior protocol describes the time sequence constraints when the component interacts with its external environment dynamically. Using Interface Automata to describe component behavior protocol, the article proposes a formal definition and a detection algorithm thougths for behavior protocols mismatches which would occur when components assembled. Compared with existing research on the compatibility of component interaction, our work has considered control characteristics of component interfaces and different situations of interfaces bindings, therefore the compatible and incompatible parts of composite component behavior protocol can be accurately distinguished. Based on above work, a limited composition approach for components is proposed. Two incompatible components can be assembled as a composite component with limited behavior protocol but reliable and usable, the reuse probability of a component is increased accordingly
Coupling the snow thermodynamic model SNOWPACK with the microwave emission model of layered snowpacks for subarctic and arctic snow water equivalent retrievals

Satellite‐passive microwave remote sensing has been extensively used to estimate snow water equivalent (SWE) in northern regions. Although passive microwave sensors operate independent of solar illumination and the lower frequencies are independent of atmospheric conditions, the coarse spatial resolution introduces uncertainties to SWE retrievals due to the surface heterogeneity within individual pixels. In this article, we investigate the coupling of a thermodynamic multilayered snow model with a passive microwave emission model. Results show that the snow model itself provides poor SWE simulations when compared to field measurements from two major field campaigns. Coupling the snow and microwave emission models with successive iterations to correct the influence of snow grain size and density significantly improves SWE simulations. This method was further validated using an additional independent data set, which also showed significant improvement using the two‐step iteration method compared to standalone simulations with the snow model.
Cross-anchoring of tones in Hoiliuk triplication

This paper discusses the tone changes in Hoiliuk triplication, in which the prefix (the first syllable) receives a heavy stress and carries a high pitch. What is particularly of interest is that the tones in the base may be copied and undergo metathesis in the prefix, which may either be bimoraic or be lengthened as trimoraic. I posit two floating elements, a floating mora and a floating high tone, in the underlying representation of the prefix and propose a model of triplication correspondence, which considers the prefixal output as a result of the interaction between IO correspondence and OO correspondence, and of the interaction between faithfulness constraints and markedness constraints.
Forecasting South African containers for international trade: A commodity-based approach

The most common approach used internationally for forecasting international trade containers is models based on the correlation between container trade and economic growth. While the strong historical correlation is indisputable, this paper argues that there will be saturation in the propensity to containerise as all the suitable volumes of the underlying commodities shift to containers over time. In addition, the link between freight transport and GDP will decouple as more sustainable approaches to economic development, and therefore freight transport, are necessitated by economic and environmental realities. A commodity-based model, taking into account the underlying drivers of containerisation, is proposed here as a more realistic forecast of container demand. This could have a material impact on how large-scale investment decisions are directed.
2016 Ieee International Conference on Big Data (big Data) Big Data Analytics in Cloud Gaming: Players' Patterns Recognition Using Artificial Neural Networks

—The Cloud Gaming model emerges with the evolution of the Cloud Computing and communication technologies. Through smartphones, PCs, tablets, consoles and other devices, people can access and use games on demand via data streaming, regardless the computing power of these devices. The Internet is the fundamental way of communication between the device and the game, which is hosted on a environment known as Cloud, enabling a large scale offer. The variety, volume, velocity, value and veracity (Big Data 5Vs) of data that is involved in these Cloud environments exceed the limits of analysis and manipulation of conventional tools, therefore, Big Data platforms are required to handle and interpret this data. The model known as Big Data Analytics is an effective and capable way to, not only work with these data, but understand its meaning, providing inputs for assertive analysis and predictive actions. A method is presented in this study to identify and analyze players' patterns in a virtual environment. With this information, it is possible to optimize user experience, revenue for developers and raise the level of control over the environment. Results are presented based on a dataset of the World of Warcraft game. By using a neural network, it was possible to identify with an average of 91% of accuracy the players' assiduity based on patterns in the game. Using the Hadoop technology and visualization tools on a Cloud based cluster, it was possible to map and identify the players' behaviors as well as their gameplay patterns.
Preprocessing time series with ICA and savitzky-golay filtering

In this paper we summarize various possible techniques such as Crossover Prediction Model or the classical Principal Component Analysis (PCA) tool to include exogenous data. Furthermore we propose a new method for volatile time series forecasting using Independent Component Analysis (ICA) algorithms and Savitzky-Golay filtering as preprocessing tools. The preprocessed data will be introduce in a based radial basis functions (RBF) Artificial Neural Network (ANN) and the prediction result will be compared with the one we get without these preprocessing tools.