Miracle-dz/UniFAR-FTUs huggingface dataset:
Issues in Design and Collection of Large Telephone Speech Corpus for Slovenian Language

In this paper, different issues in design, collection and evaluation of the large vocabulary telephone sp eech corpus of Slovenian language are discussed. The database is composed of three text corpora containing 1530 different sentences. It contains read sp eech of 82 speakers where each speaker read in average more than 200 sentences and 21 speakers read also the text passage of 90 sentenc es. The initial manual segmentation and labeling of speech material was performed. Based on this the automatic segmentation was car ried out. The database should facilitate the development of speech recognition systems to be used in dictation tasks over the teleph one. Until now the database was used mostly for isolated digit recognition tasks and word spotting.
Execution dependencies in transaction closures

Activities of advanced applications can be modeled by interrelated transactions. These relations can be described by different kinds of transaction dependencies. The notion of transaction closure is a generalization of nested transactions providing means to describe complex activities such as transactional workflows. In this paper our main focus lies on execution dependencies for describing certain control flows among related transactions of transaction closures. In particular we consider the transitivity property for all kinds of transaction execution dependencies and discuss their relationship to other kinds of dependencies such as transaction termination dependencies. We point out that some of these dependency combinations are incompatible. As a result we present rules for reasoning about the transitivity of execution dependencies. Thus, we are able to conclude how arbitrary transactions of a transaction closure are transitively interrelated.
On-line Estimation of Biomass Concentration and Specific Growth Rate in the Fermentation Process

The biomass concentration, the same as concentrations of substrates or products, a very important state variable of almost every bioprocess, cannot often be measured on-line, due to the lack of reliable and cheap sensors, which makes this set of variables limited for control purposes. In this paper, a type of soft sensing model for the on-line estimation of biomass concentration has been developed based on the least squares support vector machines approach. The soft sensing model was trained on data coming from nosiheptide fermentation process, and evaluated the production. The results show that this method is potentially useful for estimation biomass on-line in bioprocesses. In addition, an on-line computing model based on the biomass estimator was developed for the specific growth rate. This model consists of three sub-models. They describe the growth characteristic of different phases very well and facilitate its on-line monitoring
The Pleasures and Perils of Darwinizing Culture (with Phylogenies)

Current debates about “Darwinizing culture” have typically focused on the validity of memetics. In this article we argue that meme-like inheritance is not a necessary requirement for descent with modification. We suggest that an alternative and more productive way of Darwinizing culture can be found in the application of phylogenetic methods. We review recent work on cultural phylogenetics and outline six fundamental questions that can be answered using the power and precision of quantitative phylogenetic methods. However, cultural evolution, like biological evolution, is often far from treelike. We discuss the problems reticulate evolution can cause for phylogenetic analyses and suggest ways in which these problems can be overcome. Our solutions involve a combination of new methods for the study of cultural evolution (network construction, reconciliation analysis, and Bayesian mixture models), and the triangulation of different lines of historical evidence. Throughout we emphasize that most debates about cultural phylogenies can only be settled by empirical research rather than armchair speculation.
Diversity–Multiplexing Tradeoff and Outage Performance for 2×2 Dual-Polarized Uncorrelated Rice MIMO Channels

In this paper, diversity-multiplexing tradeoff (DMT) curve for 2×2 Dual-Polarized uncorrelated Rice MIMO channels is studied. Exact expressions for statistic information of mutual information exponent are derived. Impacts of channel parameters such as signal to noise ratio (SNR), k-factor and cross polarization discrimination (XPD) on mutual information exponent are analyzed. Compared to conventional single-polarized (SP) Rice MIMO systems, a qualitatively different behavior is observed for DP Rice systems. The work in this paper, allows identifying quantitatively for which channels (k-factor) and SNR levels the use of dual polarization becomes beneficial. Gamma or lognormal distribution are used to describe mutual information component, and a theoretical formulation for finite-SNR DMT curve in 2×2 DP uncorrelated Rice channels is presented for the first time, which is valid in low and medium SNRs when multiplexing gain is larger than 0.75.
Targeted trajectories optimization from 2D LIDAR measurements

In many applications involving robotics and intelligent vehicles, high precision multi-target trajectories are needed for analysis, especially those associated with control and safety applications. This paper presents an optimization approach to obtain multiple targeted trajectories from a stationary 2D LIDAR along the LIDAR's measurement plane. The use of the 2D LIDAR allows this method to work in various environments (e.g. both indoor and outdoor) compared to Global Navigation Satellite Systems (GNSS) and vision based approaches. A cylinder with high reflectivity is attached to each of the targets of interest where the 2D LIDAR measurements correspond to these cylinders are extracted and the trajectories are estimated. This approach is robust toward short duration occlusions from dynamic objects (both targeted and non-targeted) moving in the environment. Preliminary data are presented in the experimental results which includes the processing of multi-target data.
Protest : Occurrence & ( De ) Escalation

The literature on Civil Conflict has reached a point of maturity in identifying the correlates of conflict; however, the risk factors for conflict are far more common than conflict itself. Even when underlying conditions appear similar, as for the countries impacted by the Arab Spring, diverse outcomes can arise. By modeling the escalation process and incorporating protest as a signal to the government and potential dissidents in society, this paper shows how similar starting conditions can lead to protest, government concessions, or even civil war. This paper also contributes to understanding the relationship between repression and dissent. We argue that repression may reduce overall dissent, but cause dissent that occurs to become more violent. Finally we examine some predictions of the; this is done by complementing traditional conflict data from Uppsala Conflict Data Program (UCDP) with data on protest from the Social Conflict in Africa Database (SCAD). The analysis finds support for two key predictions in the model: the likelihood of a concession increases with protest size, and a non-monotonic relationship between protest size and the probability of escalation to conflict.
Analyzing control challenges for thermal energy storage in foodstuffs

We consider two important challenges that arise when thermal energy is to be stored in foodstuffs. We have previously introduced economic optimizing MPC schemes that both reduce operating costs and offer flexible power consumption in a future Smart Grid. The goal is to utilize the thermal capacity of refrigerated goods in a supermarket to shift the load of the system in time without deteriorating the quality of the foodstuffs. The analyses in this paper go before closing any control loops. In the first part, we introduce and validate a new model with which we can estimate the actual temperatures of refrigerated goods from available air temperature measurements. This is based on data obtained from a dedicated experiment. Since limits are specified for food temperatures, the estimate is essential for full exploitation of the thermal potential. Secondly, the thermal properties, shapes and sizes of different foodstuffs make them behave differently when exposed to changes in air temperature. We present a novel analysis based on Biot and Fourier numbers for the different foodstuffs. This provides a valuable tool for determining how different items can be utilized in load-shifting schemes on different timescales and for estimating maximum energy storage time. The results are shown for a large range of parameters, and with specific calculations for selected foodstuff items.
Harnessing the Knowledge Assets of Older Workers : A Work in Progress Report

This paper reports part of a study that examines how to harness the knowledge assets of older workers. Five older workers, from both public and private sector organisations, were interviewed face-to-face regarding their potential contributions to other work colleagues based on their expertise on work practices. Preliminary results revealed the following set of common themes: (a) challenges in transitioning to retirement, (b) relevant and transferable skills and knowledge, (c) organisational readiness in retaining knowledge and skills and (d) the use of information technology to support knowledge sharing. The implications the findings have for future research will be discussed.
A Forecasting Model to Evaluate a Freshman's Ability to Succeed by Using Particular Full-Scaled Class Association Rules (PFSCARs)

This study was to create a forecasting model for evaluate freshmen's ability to succeed with using the longest rules from CARs technique as called a particular full-scaled class association rules (PFSCARs). The purposed of this study was to create a classifier tool to evaluate freshmen's ability. This study used demographic data of students in Information Technology program Chandrakasem Rajabhat University and current grade levels of students as equalized levels. The equalized levels consist of 3 classes: good, fair and poor. The result of this study that proposed that the forecasting model to evaluate freshmen quality with PFSCARs performed at a good level of performance with an accuracy rate of 79% of the students equalized model. Finally, the research discovered that the forecasting model to evaluate freshmen quality can be a guideline for academic advisors or other relevant persons to help new students, to manage an appropriated study plan and could help them to improve course or curriculum in the future as well.
A Cross-Lingual Approach to the Discourse Automatic Annotation: Application to French and Bulgarian

In this paper we propose a cross-lingual approach to the discourse automatic annotation of scientific articles by the Contextual Exploration method. We present an application to French and Bulgarian as an illustration of the possibility to work with different languages that the method provides. We describe the methodology for the construction of the linguistic resources for Bulgarian based on the already existing resources for French and make an evaluation of the obtained annotations. We also discuss some of the applications of the discourse automatic annotation for automatic summarization and information retrieval.
The impact of Privatisation on Wages: Evidence from the Portuguese Banking Industry

This paper adopts a difference-in-differences estimator to examine the impact of privatisation on wages in the Portuguese banking industry for the period 1989-97. The design of the reform and the nature of dataset employed (matched employer-employee) provided a particularly important opportunity to analyse the effects of privatisation on different demographic groups, using multiple control groups, and considering the timing of the effects. The empirical evidence suggests a U-shaped relationship between wage variation and time period of restructuring, regardless of the choice of the comparison group, for those employees, either men or women, retained by privatised firms.
Optimal Suffix Tree Construction with Large Alphabets

The su x tree of a string is the fundamental data structure of combinatorial pattern matching. In this paper, we present a novel, deterministic algorithm for the construction of su x trees. We settle the main open problem in the construction of su x trees: we build su x trees in linear time for integer alphabet.
Edge dominating and hypomatchable sets

The weighted edge dominating set problem (EDS) generalizes both the weighted vertex cover problem and the problem of covering the edges of graph by a minimum cost set of both vertices and edges. Although EDS was proven NP-complete in 1980, not much progress had been made in improving its approximability to match that of weighted vertex cover until 2000. In this paper we develop a 2-approximation for weighted EDS by honing the technique of a recent 2 1/10-approximation which exploits the close polyhedral relationship between EDS and the edge cover problem. For the sake of completeness we also present a new direct proof of Edmonds and Johnson's characterization of the edge cover polyhedron. Our approximation guarantee is tight in the sense that the existence of a (2-ε)-approximation for weighted EDS for some constant, ε would imply a (2-ε)-approximation for weighted vertex cover, constituting a major breakthrough in the field.
A Smart TV Application for Personalized Recommender Services

With the TV channel explosion, many people face an exhausting task of having to find something to watch on TV that fits their interest. Despite the excessive increase of TV contents, there are few considerations in the development of novel methods for personalized smart TV content recommender services. In this paper, we define an application architecture of personalized TV content recommender service. In addition, for the personalized recommender service, we consider the use of user’s context data increasing the user’s satisfaction about the recommender service.
Regional Selective Neuronal Degeneration after Protein Phosphatase Inhibition in Hippocampal Slice Cultures: Evidence for a MAP Kinase-Dependent Mechanism

The regional selectivity and mechanisms underlying the toxicity of the serine/threonine protein phosphatase inhibitor okadaic acid (OA) were investigated in hippocampal slice cultures. Image analysis of propidium iodide-labeled cultures revealed that okadaic acid caused a dose- and time-dependent injury to hippocampal neurons. Pyramidal cells in the CA3 region and granule cells in the dentate gyrus were much more sensitive to okadaic acid than the pyramidal cells in the CA1 region. Electron microscopy revealed ultrastructural changes in the pyramidal cells that were not consistent with an apoptotic process. Treatment with okadaic acid led to a rapid and sustained tyrosine phosphorylation of the mitogen-activated protein kinases ERK1 and ERK2 (p44/42mapk). The phosphorylation was markedly reduced after treatment of the cultures with the microbial alkaloid K-252a (a nonselective protein kinase inhibitor) or the MAP kinase kinase (MEK1/2) inhibitor PD98059. K-252a and PD98059 also ameliorated the okadaic acid-induced cell death. Inhibitors of protein kinase C, Ca2+/calmodulin-dependent protein kinase II, or tyrosine kinase were ineffective. These results indicate that sustained activation of the MAP kinase pathway, as seen after e.g., ischemia, may selectively harm specific subsets of neurons. The susceptibility to MAP kinase activation of the CA3 pyramidal cells and dentate granule cells may provide insight into the observed relationship between cerebral ischemia and dementia in Alzheimer’s disease.
Ensemble Learning of Regional Classifiers

We present a new ensemble learning method that employs a set of regional classifiers, each of which learns to handle a subset of the training data. We split the training data and generate classifiers for different regions in the feature space. When classifying new data, we apply a weighted voting among the classifiers that include the data in their regions. We used 10 datasets to compare the performance of our new ensemble method with that of single classifiers as well as other ensemble methods such as bagging and Adaboost. As a result, we found that the performance of our method is comparable to that of Adaboost and bagging when the base learner is C4.5. In the remaining cases, our method outperformed the benchmark methods.
Joining interval data in relational databases

The increasing use of temporal and spatial data in present-day relational systems necessitates an efficient support of joins on interval-valued attributes. Standard join algorithms do not support those data types adequately, whereas special approaches for interval joins usually require an augmentation of the internal access methods which is not supported by existing relational systems. To overcome these problems we introduce new join algorithms for interval data. Based on the Relational Interval Tree, these algorithms can easily be implemented on top of any relational database system while providing excellent performance on joining intervals. As experimental results on an Oracle9i server show, the new techniques outperform existing relational methods for joining intervals significantly.
Imaging seismic velocity structure beneath the Iceland hot spot: A finite frequency approach

[1] Tomographic models based on hypothetically infinite frequency ray interpretation of teleseismic travel time shifts have revealed a region of relatively low P and S wave speeds extending from shallow mantle to 400 km depth beneath Iceland. In reality, seismic waves have finite frequency bandwidths and undergo diffractive wave front healing. The limitation in ray theory leaves large uncertainties in the determinations of the magnitude and shape of the velocity anomaly beneath Iceland and its geodynamic implications. We developed a tomographic method that utilizes the banana-shaped sensitivity of finite frequency relative travel times from the paraxial kernel theory. Using available seismic data from the ICEMELT and HOTSPOT experiments, we applied the new method to image subsurface velocity structure beneath Iceland. Taking advantage that the sensitivity volume of broadband waveforms varies with frequency, we measured relative delay times in three frequency ranges from 0.03 to 2 Hz for P and 0.02 to 0.5 Hz for S waves. Given similar fit to data, the kernel-based models yield the root-mean-square amplitudes of P and S wave speed perturbations about 2–2.8 times those from ray tomography in the depths of 150–400 km. The kernel-based images show that a columnar low-velocity region having a lateral dimension of � 250–300 km extends to the base of the upper mantle beneath central Iceland, deeper than that resolved by the ray-based studies. The improved resolution in the upper mantle transition zone is attributed to the deeper crossing of broad off-path sensitivity of travel time kernels than in ray approximation and frequency-dependent wave front healing as an intrinsic measure of the distance from velocity heterogeneity to receivers. INDEX TERMS: 8180 Tectonophysics: Tomography; 7203 Seismology: Body wave propagation; 7218 Seismology: Lithosphere and upper mantle; 3260 Mathematical Geophysics: Inverse theory; 8121 Tectonophysics: Dynamics, convection currents and mantle plumes;
Collaborative Leadership and Teachers Wellbeing. Research Strategies and School Governance in the Italian Education Field

The article deals with the relationship between research methods and strategies of governing in Italian education field. In particular, it relates to the surveys, whose interpretative and methodological machinery colludes with the neomanagerialist re-culturing of education space by embedding new public management ideas and tools within the educational texture. Thus, in order to analyse the generative effects that certain methodological choices can have on producing the field to be inquired, it focuses on the way in which defining unit of analysis, choosing techniques to collect data and aiming to such research objectives contribute to produce the “representation for the field to be governed [. ] the techniques to be employed, and the ends to be achieved” (Dean 2010, p. 268) in education field. Our findings show how: the neo-managerialist ‘tyranny of numbers’ (Ball, 2007) imposed both on education space, and research methods in education field can be refused, because despite inquiry contexts “governed by numbers” (Ozga, 2009) readings in line with a democratic perspective can be supplied.
Short communication Sensation seeking and negative affectivity as predictors of risky behaviors: A distinction between occasional versus frequent risk-taking

The tendency for occasional risk-taking was compared with the tendency for frequent risk-taking within a population of 201 young people. Positive affectivity, negative affectivity, sensation seeking, and risk-taking were measured for the domains of substance use, behavior on the road, sexual relations, and deviant behavior. The tendencies for occasional versus frequent risk-taking generalize across three of the four domains. Multivariate analysis show that demographics variables and personality traits do not predict the tendency for occasional risk-taking as well as they predict the tendency for frequent risk-taking. Furthermore, sensation seeking is the only trait linked to the tendency for occasional risk-taking in the domains of substance use and deviant behavior. The tendency for frequent risk-taking, notably in the domain of substance use, is predicted by age, sensation seeking, and negative affectivity. The other three domains are only predicted by sensation seeking. The results support the idea that the tendency for occasional risk-taking is distinct from the tendency for frequent risk-taking and that the two tendencies are not controlled by the same determinisms.
T Lymphocyte Antigen 4-Modified Dendritic Cell Therapy for Asthmatic Mice Guided by the CCR7 Chemokine Receptor

The CD80/CD86-CD28 axis is a critical pathway for immuno-corrective therapy, and the cytotoxic T lymphocyte antigen 4 (CTLA4) is a promising immunosuppressor targeting the CD80/CD86-CD28 axis; however, its use for asthma therapy needs further optimization. A human CTLA4 fused with the IgCγ Fc (CTLA4Ig) and mouse CC chemokine receptor type7 (CCR7) coding sequences were inserted into a recombinant adenovirus (rAdV) vector to generate rAdV-CTLA4Ig and rAdV-CCR7. The naive dendritic cells (DCs) were infected with these rAdVs to ensure CCR7 and CTLA4Ig expression. The therapeutic effects of modified DCs were evaluated. rAdV-CTLA4Ig and rAdV-CCR7 infected DCs improved all asthma symptoms. Inflammatory cell infiltration and cytokine analysis showed that rAdV-CTLA4Ig and rAdV-CCR7-modified DC therapy reduced the number of eosinophils and lymphocyte and neutrophil infiltration in the lung. Interestingly, assessment of the humoral immunity showed that the IL-4 and IFNγ levels of the rAdV-CTLA4Ig and rAdV-CCR7-modified DC-treated mice decreased significantly and did not reverse the Th1/Th2 balance. DCs expressing CCR7 displayed guidance ability for DC migration, primarily for DCs in the inflammatory lung. Additionally, the rAdVs caused an inflammatory response by inducing DC differentiation, inflammatory cell infiltration and changes in cytokines; however, mice transplanted with rAdV-green fluorescent protein (GFP)-infected DCs displayed no asthma manifestations. In conclusion, CTLA4Ig-modified DCs exhibited a therapeutic effect on asthma, and CCR7 may guide DC homing. The combination of these two molecules may be a model for precision-guided immunotherapy.