Miracle-dz/UniFAR-FTUs huggingface dataset:
Investigating on the Methodology Effect When Evaluating Lucid Dream

Lucid dreaming (LD) is a state of consciousness in which the dreamer is aware that he or she is dreaming and can possibly control the content of his or her dream. To investigate the LD prevalence among different samples, researchers have used different types of methodologies. With regard to retrospective self-report questionnaire, two ways of proceeding seem to emerge. In one case, a definition of LD is given to participants (“During LD, one is–while dreaming–aware of the fact that one is dreaming. It is possible to deliberately wake up, to control the dream action, or to observe passively the course of the dream with this awareness”), while in the other instances, participants are presented separate questions targeting specific LD indicators (dream awareness and dream control). In the present study, we measured LD frequency in a sample of French student in order to investigate for possible disparities in LD frequency depending on the type of questionnaire as outlined above. Moreover, we also study links between the prevalence of LD as assessed, respectively, by each questionnaire with various factors such as Vividness of Mental Imagery and Parasomnia. Results revealed no significant difference between LD frequencies across questionnaires. For the questionnaire with definition (DefQuest), 81.05% of participants reported experience of LD once or more. Concerning the questionnaire based on LD indicators (AwarContQuest), 73.38% of participants reported having experienced LD once or more. However, with regard to the correlations analysis, links between LD prevalence and factors such as Vividness of Mental Imagery and Parasomnia, varied across questionnaires. This result is an argument suggesting that researchers should be careful when investigating links between LD and other factors. The type of methodology may influence findings on LD research. Further studies are needed to investigate on the methodology effect in LD research namely on the respective weight of awareness and control.
Modeling non-Rayleigh speckle distribution in SAR images

In non-Rayleigh distributed radar images, the number of scatterers can be viewed as a Poisson distributed random variable, with the mean itself random. When this mean is Gamma distributed, then the image classically satisfies the K distribution. We add three new possible distributions for this mean: inverse Gamma, Beta of the first kind, and Beta of the second kind. We show that new intensity distributions so obtained can be estimated, with the interest of the extension validated on a real image.
Efficient Coalition Formation for Web Services

Web services are loosely-coupled business applications willing to cooperate in distributed settings within different groups called communities. Communities aim to provide better visibility, efficiency, market share and total payoff. There are a number of proposed mechanisms and models on aggregating web services and making them cooperate within their communities. However, forming optimal and stable communities as coalitions to maximize individual and group efficiency and income has not been addressed yet. In this paper, we propose an efficient coalition formation mechanism using cooperative game-theoretic techniques. We propose a mechanism for community membership requests and selections of web services in the scenarios where established communities already exist. Moreover, we analyze the scenarios where communities are not established yet and web services can form multiple communities. The ultimate objective is to develop a mechanism for web services to form stable groups allowing them to maximize their efficiency and generate near-optimal (welfare-maximizing) communities. The theoretical and simulation results show that our algorithms provide web services and community owners with applicable and near-optimal decision making mechanisms.
3D single-pixel video

Photometric stereo is an established three-dimensional (3D) imaging technique for estimating surface shape and reflectivity using multiple images of a scene taken from the same viewpoint but subject to different illumination directions. Importantly, this technique requires the scene to remain static during image acquisition otherwise pixel-matching errors can introduce significant errors in the reconstructed image. In this work, we demonstrate a modified photometric stereo system with perfect pixel-registration, capable of reconstructing 3D images of scenes exhibiting dynamic behavior in real-time. Performing high-speed structured illumination of a scene and sensing the reflected light with four spatially-separated, single-pixel detectors, our system reconstructs continuous real-time 3D video at ∼8 frames per second for image resolutions of 64 × 64 pixels. Moreover, since this approach does not use a pixelated camera sensor, it can be readily extended to other wavelengths, such as the infrared, where camera technology is expensive.
Government Social Media Messages Across Disaster Phases

Social media platforms allow emergency managers to augment traditional approaches to crisis communication. Research on government messaging, however, disproportionately addresses large‐scale disaster response efforts, neglecting smaller‐scale incidents and activities across other disaster phases (e.g., prevention, mitigation, preparedness and recovery). This article offers a more complete analysis of messaging strategies by integrating existing typologies and analysing state‐level emergency management agencies in the United States over a one‐year period. Findings illustrate a range of messages, with response and preparedness being most prevalent. While all agencies disseminated protective action messages, situational information and preparedness guidance, fewer engaged in more interactive tactics that facilitate public participation and interagency collaboration. More work, therefore, is needed to pursue social media's full potential in promoting risk reduction.
Multi-document Summarization using Tensor Decomposition

The problem of extractive text summarization for a collection of documents is defined as selecting a small subset of sentences so the contents and meaning of the original document set are preserved in the best possible way. In this paper we present a new model for the problem of extractive summarization, where we strive to obtain a summary that preserves the information coverage as much as possible, when compared to the original document set. We construct a new tensor-based representation that describes the given document set in terms of its topics. We then rank topics via Tensor Decomposition, and compile a summary from the sen- tences of the highest ranked topics.
3D ICs with TSVs—Design Challenges and Requirements

As demands accelerate for increasing density, higher bandwidths, and lower power, many IC design teams are looking up – to 3D ICs with through-silicon vias (TSVs). 3D ICs promise “more than Moore” integration by packing a great deal of functionality into small form factors, while improving performance and reducing costs. 3D IC packages may accommodate multiple heterogeneous die—such as logic, memory, analog, RF, and micro-electrical mechanical systems (MEMS)—at different process nodes, such as 28nm for high-speed logic and 130nm for analog. This provides an alternative to system-on-chip (SoC) integration, potentially postponing an expensive move to a new process node for all of the functionality developers want to place in a single package.
Enabling Attribute Based Encryption as an Internet Service

Internet enabled services and technologies are changing the way we use and manage massive amounts of data. More and more users and organizations are increasingly relying on cloud storage services for data management. In such Internet enabled environments, protecting sensitive data is increasingly becoming very crucial. Attribute-based Encryption (ABE) based approaches have been recognized as very promising for data protection in such environments. ABE approaches support data confidentiality and fine-grained access control in Internet-based environments, which include Internet of things (IoTs) and a plethora of heterogeneous mobile devices that enable large scale applications. However, in IoTs and mobile applications the limited computational resources and finite battery power of devices make it very difficult to use ABE schemes because of their heavy computational requirements. Although outsourced computational techniques have been applied in partial ABE schemes to address such issues, a unified platform that supports all aspects of data protection in an Internet-based open environment as well as fast cryptographic operations and decentralized authorities, etc., is still lacking. In this paper, we propose a novel Attribute Based Encryption as a Service (ABEaaS) that can be leveraged for data protection in the Internet environments. We propose an ABEaaS framework that can be easily deployed and present related security and performance analysis.
What Substitutes Tell Us - Analysis of an “All-Words” Lexical Substitution Corpus

We present the first large-scale English “allwords lexical substitution” corpus. The size of the corpus provides a rich resource for investigations into word meaning. We investigate the nature of lexical substitute sets, comparing them to WordNet synsets. We find them to be consistent with, but more fine-grained than, synsets. We also identify significant differences to results for paraphrase ranking in context reported for the SEMEVAL lexical substitution data. This highlights the influence of corpus construction approaches on evaluation results.
Cost-effectiveness of Antivenoms for Snakebite Envenoming in Nigeria

Background Snakebite envenoming is a major public health problem throughout the rural tropics. Antivenom is effective in reducing mortality and remains the mainstay of therapy. This study aimed to determine the cost-effectiveness of using effective antivenoms for Snakebite envenoming in Nigeria. Methodology Economic analysis was conducted from a public healthcare system perspective. Estimates of model inputs were obtained from the literature. Incremental Cost Effectiveness Ratios (ICERs) were quantified as deaths and Disability-Adjusted-Life-Years (DALY) averted from antivenom therapy. A decision analytic model was developed and analyzed with the following model base-case parameter estimates: type of snakes causing bites, antivenom effectiveness to prevent death, untreated mortality, risk of Early Adverse Reactions (EAR), mortality risk from EAR, mean age at bite and remaining life expectancy, and disability risk (amputation). End-user costs applied included: costs of diagnosing and monitoring envenoming, antivenom drug cost, supportive care, shipping/freezing antivenom, transportation to-and-from hospital and feeding costs while on admission, management of antivenom EAR and free alternative snakebite care for ineffective antivenom. Principal Findings We calculated a cost/death averted of ($2330.16) and cost/DALY averted of $99.61 discounted and $56.88 undiscounted. Varying antivenom effectiveness through the 95% confidence interval from 55% to 86% yield a cost/DALY averted of $137.02 to $86.61 respectively. Similarly, varying the prevalence of envenoming caused by carpet viper from 0% to 96% yield a cost/DALY averted of $254.18 to $78.25 respectively. More effective antivenoms and carpet viper envenoming rather than non-carpet viper envenoming were associated with lower cost/DALY averted. Conclusions/Significance Treatment of snakebite envenoming in Nigeria is cost-effective with a cost/death averted of $2330.16 and cost/DALY averted of $99.61 discounted, lower than the country's gross domestic product per capita of $1555 (2013). Expanding access to effective antivenoms to larger segments of the Nigerian population should be a considered a priority.
Experiment-Based Smartphone Traffic Modeling and Power Saving Performance Analysis for LTE DRX Mechanism

Nowadays mobile devices, accompanied with numerous diverse applications (APPs), have exactly changed Human life and brought about explosive growth in mobile data traffic. Some APPs, which create background traffic regularly, may generate periodic data traffic, frequently interrupt the sleep duration of mobile devices, and thus speed up battery power consumption. In this paper, we first study the properties of smart phone application traffic, especially the periodically-updated applications. We capture packets transmitted by and received from applications, classify applications based on their traffic patterns, and then build models to characterize periodically-update applications. Based on the models, we then investigate the effect of periodic traffic from APPs on the performance of Discontinuous Reception (DRX) mechanism in 4G LTE system. Moreover, two optimization problems on DRX configuration considering packet delay and device sleep ratio are investigated respectively.
Intracellular flow in optic nerve axons: a mechanism for cell death in glaucoma.

PURPOSE In glaucoma, elevated intraocular pressure causes a progressive loss of retinal ganglion cells and results in optic neuropathy. The authors propose a potential mechanism for cell death, whereby elevated intraocular pressure causes fluid to permeate axonal membranes, creating a passive intracellular fluid flow within the axons. It is hypothesized that this intracellular flow locally depletes the adenosine triphosphate (ATP) concentration, disrupting axonal transport and leading to cell death. METHODS A mathematical model was developed that takes into account the biomechanical principles underpinning the proposed hypothesis, and was solved to determine the implications of the mechanism. RESULTS The model suggests that the raised intraocular pressures present in glaucoma are adequate to produce significant intracellular fluid flow. In the periphery of the optic nerve head, this flow may be sufficient to disrupt the diffusion of ATP and hence interrupt active axonal transport. CONCLUSIONS The mathematical model demonstrates that it is physically plausible that a passive intracellular fluid flow could significantly contribute to the pathophysiology of the retinal ganglion cell axon in glaucoma.
DiOLISTIC Labeling of Neurons from Rodent and Non-human Primate Brain Slices

DiOLISTIC staining uses the gene gun to introduce fluorescent dyes, such as DiI, into neurons of brain slices (Gan et al., 2009; O'Brien and Lummis, 2007; Gan et al., 2000). Here we provide a detailed description of each step required together with exemplary images of good and bad outcomes that will help when setting up the technique. In our experience, a few steps proved critical for the successful application of DiOLISTICS. These considerations include the quality of the DiI-coated bullets, the extent of fixative exposure, and the concentration of detergent used in the incubation solutions. Tips and solutions for common problems are provided. This is a versatile labeling technique that can be applied to multiple animal species at a wide range of ages. Unlike other fluorescent labeling techniques that are limited to preparations from young animals or restricted to mice because they rely on the expression of a fluorescent transgene, DiOLISTIC labeling can be applied to animals of all ages, species and genotypes and it can be used in combination with immunostaining to identify a specific subpopulation of cells. Here we demonstrate the use of DiOLISTICS to label neurons in brain slices from adult mice and adult non-human primates with the purpose of quantifying dendrite branching and dendritic spine morphology.
Field weakening of induction motors in a very wide region with regard to parameter uncertainties

In this paper, a new approach to induction machine control is presented that ensures the production of maximum torque over the permitted speed range. In the first part of the paper the steady state torque capability of an induction motor with saturation air gap inductance is analysed, when voltage as well as current are limited. This maximum torque can be achieved with different control schemes. Nevertheless, the schemes differ in view of robustness and the requirements to reach the optimum. In this paper, a scheme is presented that achieves the optimum operating point in the whole field weakening region only by means of the measured values of voltage and current. This method guarantees a robust adjustment with regard to the parameter uncertainties and the variable DC link voltage.
Class-Conditional Probabilistic Principal Component Analysis: Application to Gender Recognition

This paper presents a solution to the problem of recognizing the gender of a human face from an image. We adopt a holistic approach by using the cropped and normalized texture of the face as input to a Naive Bayes classifier. First it is introduced the Class-Conditional Probabilistic Principal Component Analysis (CC-PPCA) technique to reduce the dimensionality of the classification attribute vector and enforce the independence assumption of the classifier. This new approach has the desirable property of a simple parametric model for the marginals. Moreover this model can be estimated with very few data. In the experiments conducted we show that using CC-PPCA we get 90% classification accuracy, which is similar result to the best in the literature. The proposed method is very simple to train and implement.
Discrete-time fuzzy sliding mode control for a vehicle suspension system featuring an electrorheological fluid damper

This paper presents real-time control characteristics of an electrorheological (ER) suspension system via a fuzzy sliding mode control algorithm which is formulated in a discrete-time manner by considering the sampling rate of an electronic control unit for a vehicle system. A quarter-vehicle system consisting of sprung mass, spring, tire and a cylindrical ER damper (shock absorber) is constructed for the real-time control. After deriving the governing equation of motion of the proposed system, a discrete-time control model with system uncertainties is formulated. A stable sliding surface is then designed and followed by the formulation of the discrete-time sliding mode controller which consists of a discontinuous part and an equivalent part. In the controller formulation, the fuzzy control algorithm is also adopted to enhance system robustness to the mass variation and reaching time to the sliding surface. The controller is then experimentally realized for the manufactured quarter-vehicle ER suspension system. Control performances such as vertical acceleration are evaluated under various road conditions and presented in both time and frequency domains.
Internal singularity analysis of a class of lower mobility parallel manipulators with articulated traveling plate

This paper deals with a particular family of lower mobility parallel kinematic manipulators. The four degrees of freedom of the end-effector consist of three translations plus one rotation with a high tilting angle. Robots belonging to this family are first introduced, and a common parameterization is established. Then an extended kinematic model is proposed for this family of robots using a new Jacobian matrix. Relevant information about robot kinematic singularities, internal singularities, and possible end-effector motions can be obtained by resorting to this matrix. The efficiency of this method is proven by applying it to several traveling-plate architectures corresponding to already built robot prototypes. The results of the expected behavior are compared with the prototype's real behavior. The goal of this paper is to show that internal (or constraint) singularities can occur in lower mobility parallel kinematic manipulators, and to underline the influence they have during the design stage.
Feature engineering using shallow parsing in argument classification of Persian verbs

Identifying the verb's dependents and determining the semantic role for them is a natural pre-processing step in applications such as machine translation (MT) and question answering (QA). In this paper, we present a feature set for assigning argument instances into thematic role classes such as “Agent” and “Patient”. This feature set contains mainly language specific features for syntactic segments (chunks) of Persian sentences which can be categorized into three feature types including verb properties, chunk content and relation between the argument and verb of a sentence. We train an instance-based classifier on our manually annotated dataset to select the appropriate semantic role of each chunk. The classifier discriminates the best semantic role without considering the interaction between chunks in a sentence. The results show that our feature set discriminates the thematic roles of arguments in a considerable accuracy about 81.9% which enhances the baseline accuracy about 18.8%. Our dataset is free release and available for the researchers.
Evaluation of a deductive procedure to teach grammatical inflections to children with language impairment.

PURPOSE To evaluate the learning effects of a deductive language-teaching procedure when teaching a novel gender agreement verb inflection to children with language impairment. METHOD Thirty-two 6-8-year-old children with language impairment were randomly assigned to either a deductive (N = 16) or an inductive (N = 16) treatment group. In the deductive treatment, the examiner presented a rule guiding the novel inflection to be learned as well as models of the inflection. In the inductive treatment, only models of the verb inflection were presented. Learning was assessed in 3 different production contexts during each of 4 treatment sessions. RESULTS Significantly more participants in the deductive group than the inductive group acquired the novel morpheme based on a teaching probe (10 vs. 3), generalization probe (10 vs. 3), and maintenance probe (7 vs. 2). Task performance was not significantly influenced by language ability or nonverbal intelligence. CONCLUSIONS The deductive teaching procedure was found to be efficacious when teaching a novel grammatical inflection. However, this effect was limited because treatment gains varied across participants, testing contexts, and sessions. Future studies should continue to examine the efficacy of deductive procedures when integrated into traditional implicit approaches for children with language impairment.