Miracle-dz/UniFAR-FTUs huggingface dataset:
Decomposing background topics from keywords by principal component pursuit

Low-dimensional topic models have been proven very useful for modeling a large corpus of documents that share a relatively small number of topics. Dimensionality reduction tools such as Principal Component Analysis or Latent Semantic Indexing (LSI) have been widely adopted for document modeling, analysis, and retrieval. In this paper, we contend that a more pertinent model for a document corpus as the combination of an (approximately) low-dimensional topic model for the corpus and a sparse model for the keywords of individual documents. For such a joint topic-document model, LSI or PCA is no longer appropriate to analyze the corpus data. We hence introduce a powerful new tool called Principal Component Pursuit that can effectively decompose the low-dimensional and the sparse components of such corpus data. We give empirical results on data synthesized with a Latent Dirichlet Allocation (LDA) mode to validate the new model. We then show that for real document data analysis, the new tool significantly reduces the perplexity and improves retrieval performance compared to classical baselines.
Towards semi-episodic learning for robot damage recovery

The recently introduced Intelligent Trial and Error algorithm (IT\&E) enables robots to creatively adapt to damage in a matter of minutes by combining an off-line evolutionary algorithm and an on-line learning algorithm based on Bayesian Optimization. We extend the IT\&E algorithm to allow for robots to learn to compensate for damages while executing their task(s). This leads to a semi-episodic learning scheme that increases the robot's lifetime autonomy and adaptivity. Preliminary experiments on a toy simulation and a 6-legged robot locomotion task show promising results.
Mary101: A Photorealistic Text-to-Audio-Visual Speech Syn- thesizer

Previous Work: Much of the previous work in text-to-audio-visual (TTAVS) speech synthesis [9] [2] has focused on integrating physically-based facial models with a particular speech synthesis system in order to give the impression of a ”talking face”. Some TTAVS systems have also resorted to Cyberware scanning techniques to overlay realisticlooking skin texture on top of the underlying graphics model [8].
Linear Algorithms for Radioelectric Spectrum Forecast

This paper presents the development and evaluation of two linear algorithms for forecasting reception power for different channels at an assigned spectrum band of global systems for mobile communications (GSM), in order to analyze the spatial opportunity for reuse of frequencies by secondary users (SUs) in a cognitive radio (CR) network. The algorithms employed correspond to seasonal autoregressive integrated moving average (SARIMA) and generalized autoregressive conditional heteroskedasticity (GARCH), which allow for a forecast of channel occupancy status. Results are evaluated using the following criteria: availability and occupancy time for channels, different types of mean absolute error, and observation time. The contributions of this work include a more integral forecast as the algorithm not only forecasts reception power but also the occupancy and availability time of a channel to determine its precision percentage during the use by primary users (PUs) and SUs within a CR system. Algorithm analyses demonstrate a better performance for SARIMA over GARCH algorithm in most of the evaluated variables.
The Aetiology of Reduced Cardiorespiratory Fitness Among Adults with Severe Traumatic Brain Injury and the Relationship with Physical Activity: A Narrative Review

Reduced cardiorespiratory fitness or cardiorespiratory deconditioning is a secondary physical impairment commonly reported to affect people after traumatic brain injury (TBI), both in the short- and long-term. Eleven studies have measured peak oxygen uptake ${\rm ({\dot V}O}_{{\rm 2peak}} )$ to evaluate fitness in this population. The mean (SD) ${\rm \dot VO}_{{\rm 2peak}}$ from these studies was 27.2 (6.7) mL.kg−1·min−1, which is markedly below the average fitness level of age-matched healthy individuals. The aetiology of cardiorespiratory deconditioning has not been well evaluated among people with TBI; however, studies on prolonged bed rest and studies on the acute consequences of TBI inform our current understanding. The primary aim of this paper is to present a model to describe the physiological factors contributing to the development of cardiorespiratory deconditioning among people with severe TBI. We propose that both central and peripheral factors contribute to reduced fitness, and that these changes occur because of both the initial brain damage and trauma sustained and the prolonged and initially extreme physical inactivity that is commonly experienced after this type of injury. Reduced fitness can significantly affect the ability to return to pre-injury activities. Given that reintegration into the community is a key goal of rehabilitation among people with TBI, interventions that can prevent or reverse reduced fitness need to be implemented.
Nonlinear higher spin theories in various dimensions

In this article, an introduction to the nonlinear equations for completely symmetric bosonic higher spin gauge fields in anti de Sitter space of any dimension is provided. To make the presentation self-contained we explain in detail some related issues such as the MacDowell-Mansouri-Stelle-West formulation of gravity, unfolded formulation of dynamical systems in terms of free differential algebras and Young tableaux symmetry properties in terms of Howe dual algebras.
An efficient algorithm for pairwise test case generation in presence of constraints

Constraints handling problem in combinational testing is an intensive computation process. In this paper, we present an effective algorithm, called IPO SAT (In-Parameter-Order-Satisfiability), for pairwise test case generation in presence of constraints. In our strategy, constraints are denoted as forbidden tuples, which are converted to conjunctive normal form. Then, the combination test cases which meet the constraints are found out by calling Boolean satisfiability(SAT) solvers. Besides, an optimization upon the process is given, in order to improve the performance of IPO SAT by reducing the number of times of calling SAT solver and avoiding checking irrelevant constraints. Finally, experimental results show that the proposed IPO SAT algorithm is efficient and the optimization has obvious improvements on reducing time cost.
Psychopathological Symptoms as a Function of Trauma, Dreams, and Inhibitions

This study investigates the cumulative effects of lifetime traumatization on dream activities and the extent to which potentially traumatic events, dream variables, and inhibitory functions can predict the severities of psychopathological symptoms. The sample consisted of 564 young adults, whose dream experiences, trauma history, ego functions, and symptom manifestations were assessed using the Dream Intensity Scale, Dream Motif Scale, Traumatic Experiences Checklist, and Ko’s Mental Health Questionnaires, respectively. The 2 dream scales profile an individual’s phenomenological experience of dream activities by retrospectively quantifying some typical dream themes—such as being pursued and encountering a person whom is desired— and variables indicative of subjective dream intensity, for example, nightmare frequency, lucid dreaming frequency, and confusion between real and dreamed events. The overall results suggest that psychopathological symptoms can be predicted positively by emotional trauma, accumulated traumatic experiences, thematic dream content, and sexual suppression (resistance against activity, material, or conversation relating to sex) and negatively by repressive defensiveness (denial of negative attributes) and counterdependence (active resistance against relying on other people) with impressive effect sizes.
Answering for Concepts Relaxed by Similarity Measures

In Description Logics (DL) knowledge bases (KBs) information is typically captured by crisp concept descriptions. However, for many practical applications querying the KB by crisp concepts is too restrictive. A controlled way of gradually relaxing a query concept can be achieved by the use of similarity measures. To this end we formalize the task of instance query answering for crisp DL KBs using concepts relaxed by similarity measures. We identify relevant properties for the similarity measure and give first results on a computation algorithm.
Online assessment for hands-on cyber security training in a virtual lab

Online (self) assessment is an important functionality e-learning courseware, especially if the system is intended for use in distant learning courses. Precisely for hands-on exercises, the implementation of effective and cheating-proof assessment tests poses a great challenge. That is because of the static characteristics of exercise scenarios in the laboratories: adopting the environment for the provision of a “unique” hands-on experience for every student in a manual manner is connected with enormous maintenance efforts and thus not scalable to a large number of students. This work presents a software solution for the assessment of practical exercises in an online lab based on virtual machine technology. The basic idea is to formally parameterize the exercise scenarios and implement a toolkit for the dynamic reconfiguration of virtual machines in order to adopt the defined parameters for the training environment. The actual values of these parameters come to use again in the dynamic generation of multiple-choice or free-text answer tests for a web-based e-assessment environment.
MicroRNA-148b enhances the radiosensitivity of non-Hodgkin's Lymphoma cells by promoting radiation-induced apoptosis

Growing evidence has demonstrated that microRNAs (miRNAs) play an important role in regulating cellular radiosensitivity. This study aimed to explore the role of miRNAs in non-Hodgkin's lymphoma (NHL) radiosensitivity. Microarray was employed to compare the miRNA expression profiles in B cell lymphoma cell line Raji before and after a 2-Gy dose of radiation. A total of 20 differentially expressed miRNAs were identified including 10 up-regulated and 10 down-regulated (defined as P < 0.05). Among the differentially expressed miRNAs, miR-148b was up-regulated 1.53-fold in response to radiation treatment. A quantitative real-time polymerase chain reaction (PCR) assay confirmed the up-regulation of miR-148b after radiation. Transient transfection experiments showed that miR-148b was up-regulated by miR-148b mimic and down-regulated by miR-148b inhibitor in the Raji cells. A proliferation assay showed that miR-148b could inhibit the proliferation of Raji cells before and after radiation. A clonogenic assay demonstrated that miR-148b sensitized Raji cells to radiotherapy. MiR-148b did not affect the cell cycle profile of post-radiation Raji cells compared with controls. An apoptosis assay showed that miR-148b enhanced apoptosis of Raji cells after irradiation. Taken together, these results demonstrate that miR-148b increased the radiosensitivity of NHL cells probably by promoting radiation-induced apoptosis, which suggests that miR-148b plays an important role in the response of NHL to ionizing radiation.
An examination of college students’ fears about terrorism and the likelihood of a terrorist attack

ABSTRACT After the September 11, 2001, terrorist attacks on the United States, a new phenomenon, fear of terrorism, was found to affect many Americans. Almost 15 years later, with few exceptions, the US homeland has enjoyed an environment free of major terrorist attacks. However, fear of terrorism remains high among Americans. Using a sample of 524 undergraduate students from a major regional university in the Midwest region of the United States, researchers distributed a survey to investigate levels of fear of terrorism and perceptions about the likelihood of a terrorist attack happening on American soil. The findings of this study indicated that respondents were moderately fearful of terrorism and moderately certain than an attack would happen in the near future. Many of the measures previously identified in the research continue to influence fears and concerns about the risk and fear of an attack.
Family Quality of Life from the Perspectives of Individual Family Members: A Korean-American Family and Deafness.

Beginning in the mid-to-late 1980s, the focus on individual quality of life expanded to family quality of life (FQOL) in the field of intellectual disabilities. However, few studies examined FQOL for families who have children with hearing loss. Furthermore, most studies focused on mothers’ perceptions of FQOL. The purpose of this study is to understand how different members of a family experience FQOL when there is a member with hearing loss and how those experiences contribute to aggregated FQOL perception as a family unit. Three KoreanAmerican family members, including the father, mother, and individual with hearing loss, participated and presented diverse perceptions of their FQOL. Results indicated each family member described diverse perceptions in seven (58%) of the 12 indicators categorized in four of the five FQOL domains. Implications for future research were described.
An analysis of the variation of ocean floor bathymetry and heat flow with age

Two models, a simple cooling model and the plate model, have been advanced to account for the variation in depth and heat flow with increasing age of the ocean floor. The simple cooling model predicts a linear relation between depth and t½, and heat flow and 1/t½, where t is the age of the ocean floor. We show that the same t½ dependence is implicit in the solutions for the plate model for sufficiently young ocean floor. For larger ages these relations break down, and depth and heat flow decay exponentially to constant values. The two forms of the solution are developed to provide a simple method of inverting the data to give the model parameters. The empirical depth versus age relation for the North Pacific and North Atlantic has been extended out to 160 m.y. B.P. The depth initially increases as t½, but between 60 and 80 m.y. B.P. the variation of depth with age departs from this simple relation. For older ocean floor the depth decays exponentially with age toward a constant asymptotic value. Such characteristics would be produced by a thermal structure close to that of the plate model. Inverting the data gives a plate thickness of 125±10 km, a bottom boundary temperature of 1350°±275°C, and a thermal expansion coefficient of (3.2±1.1) × 10−5°C−1. Between 0 and 70 m.y. B.P. the depth can be represented by the relation d(t) = 2500 + 350t½ m, with t in m.y. B.P., and for regions older than 20 m.y. B.P. by the relation d(t) = 6400 - 3200 exp (−t/62.8) m. The heat flow data were treated in a similar, but less extensive manner. Although the data are compatible with the same model that accounts for the topography, their scatter prevents their use in the same quantitative fashion. Our analysis shows that the heat flow only responds to the bottom boundary at approximately twice the age at which the depth does. Within the scatter of the data, from 0 to 120 m.y. B.P., the heat flow pan be represented by the relation q(t) = 11.3/t½ μcal cm−2s−1. The previously accepted view that the heat flow observations approach a constant asymptotic value in the old ocean basins needs to be tested more stringently. The above results imply that a mechanism is required to supply heat at the base of the plate.
Trimmed Bagging

Bagging has been found to be successful in increasing the predictive performance of unstable classifiers. Bagging draws bootstrap samples from the training sample, applies the classifier to each bootstrap sample, and then averages overal lobtained classification rules. The idea of trimmed bagging is to exclude the bootstrapped classification rules that yield the highest error rates, as estimated by the out-of-bag error rate, and to aggregate over the remaining ones. In this note we explore the potential benefits of trimmed bagging. On the basis of numerical experiments, we conclude that trimmed bagging performs comparably to standard bagging when applied to unstable classifiers as decision trees, but yields better results when applied to more stable base classifiers, like support vector machines.
The shortest path: Comparison of different approaches and implementations for the automatic routing of vehicles

The routing of vehicles or personnel in complex logistics systems is a task that needs to be solved in numerous applications, e.g., detailed models of transport networks or order picking areas. The number of relevant nodes in such networks can easily exceed 10,000 nodes. Often, a basic task is finding the shortest path from one node (start) to another (destination). Within the last years various simulation tools have been extended by respective algorithms. However, the execution time of the simulation model may significantly depend on the number of nodes in the network. We present algorithms from the literature and a comparison of three simulation tools with respect to execution time and model size for different scenarios. We further present an approach to work with so called sub-networks, i.e., the network is separated into areas, where finding the shortest path includes the task of starting at a node in one sub-network with a destination in another one.
MACHINE LEARNING AT THE CTBTO . TESTING , AND EVALUATION OF THE FALSE EVENTS IDENTIFICATION ( FEI ) AND VERTICALLY INTEGRATED SEISMIC ASSOCIATION ( VISA ) PROJECTS

Since 2009, an initiative to investigate the potential of machine learning methods to improve automatic data processing at the CTBTO and in particular the recall and accuracy of the automatic bulletins is starting to bear fruit beyond the stage of research and has entered the domain of development and testing with the goal of operational testing for one of the projects (FEI) by the end of 2011. The prospect for FEI is that the tool will comfort analysts in their decision-making process when they make decisions on whether a (mostly smaller) event is real or false, and it is thus an enhancement of the current analysis system. The VISA projects are more ambitious and aim at replacing key components of the processing system. The prototype of the first generation, which aims at replacing the current automatic association tool (GA), is being evaluated on the vDEC collaborative platform of the CTBTO. Results show much improved accuracy using VISA as compared to the SEL3 for the same recall value, or much-improved recall value using VISA as compared to the SEL3 for the same processing accuracy. A consequence is a significant decrease in either the number of false alarms or the number of missed events, depending on the setting of the processing parameters.
Exploiting Randomized Prim’s Algorithm and Background Contrast forSaliency Detection

The geodesic saliency method in the literature was based on the boundary and connectivity priority, which as- sumed that most of the background regions can touch the image boundaries. It cannot deal with the images with complex backgrounds or variant textures. To address such problem, we propose an improved saliency detection method by involv- ing the important foreground priority. First, the statistical results of randomized Prim's algorithm are used to generate a coarse conspicuity map, which aims to roughly estimate the potential foreground. Then, the image is over-segmented into some individual superpixels and an affinity propagation clustering method is used to group the superpixels having a simi- lar color appearance together. This is followed by the foreground probability map computation through the spatial interac- tion information between the coarse conspicuity map and superpixel based color clusters. The final saliency map is gener- ated by integrating the above foreground probability map and background color contrast in a unified way. The quantitative and qualitative comparisons on the benchmark dataset MSRA-1000 and SED show that our method outperforms many re- cent proposed state-of-the-art approaches significantly.
RedTag: automatic content metadata capture for cameras

RedTag is an optical tagging system that provides time based identification of objects, people or devices via small low cost infrared transmitters and receivers. We have developed RedTag as a cheap and flexible method of augmenting existing video capture equipment with an additional temporal metadata output of content based information. In this note, we describe the technology behind RedTag and demonstrate the interaction opportunities that arise through access to temporal metadata.
Integrable twists in AdS/CFT

A class of marginal deformations of four-dimensional = 4 super Yang-Mills theory has been found to correspond to a set of smooth, multiparameter deformations of the S5 target subspace in the holographic dual on AdS5 ? S5. We present here an analogous set of deformations that act on global toroidal isometries in the AdS5 subspace. Remarkably, certain sectors of the string theory remain classically integrable in this larger class of so-called ? -deformed AdS5 ? S5 backgrounds. Relying on studies of deformed (2)? models, we formulate a local (2)? Lax representation that admits a classical, thermodynamic Bethe equation (based on the Riemann-Hilbert interpretation of Bethe's ansatz) encoding the spectrum in the deformed AdS5 geometry. This result is extended to a set of discretized, asymptotic Bethe equations for the twisted string theory. Near-pp-wave energy spectra within (2)? and (2)? sectors provide a useful and stringent test of such equations, demonstrating the reliability of this technology in a wider class of string backgrounds. In addition, we study a twisted Hubbard model that yields certain predictions of the dual ? -deformed gauge theory.
Distributed Power Allocation For OFDM Wireless Ad-Hoc Networks Based On Average Consensus

This paper addresses the problem of optimal power allocation in multiuser OFDM ad-hoc networks. Our objective is to maximize the weighted rate-sum of users under total transmit power constraint. Maximizing a weighted rate-sum is more amenable whereas appropriate weight assignment to different users, guarantees fairness among users. We propose a distributed algorithm for optimal power allocation based on reaching a consensus among users for power allocation. The proposed algorithm is tractable in the sense of computational complexity and requires only local information at each node. Simulation results and the analysis of the algorithm are presented to support the proposed idea
Reactive dynamic architectures

1. ABSTRACT Dynamic modifications to architectures include replacing components and re-wiring of connectors. In this position paper we present the manner in which architectures can perform self-governed re-configurations dynamically using rule-based architectural agents. Agents can monitor the architecture and perform simple re-configurations. This paper describes work in progress, and point out interesting areas of research connected to architectural agents.
TransformeR : A DSL for Safe Variable Transformation Yisu

TransformeR is a domain-specific language embedded in the R programming language for writing safe variable transformations within the PSI private data sharing interface. In this document, we present the integration of TransformeR within the PSI prototype and the language’s grammar, statistical operations and type system. We also attach a list of desiderata together with guidelines for future contributors.