Miracle-dz/UniFAR-FTUs huggingface dataset:
Formalizing WS-BPEL and Higher Order Mobile Em- bedded Business Processes in the Bigraphical Program- ming Languages (BPL) Tool

Bigraphical Reactive Systems (BRSs) have been proposed as a formal metamodel for global ubiquitous computing that encompasses process calculi for mobility, notably the π-calculus and the Mobile Ambients calculus, as well as graphical models for concurrency such as Petri Nets. In this paper we demonstrate that BRSs also allow natural formalizations of programming languages used in practice. We do so by providing a direct and extensible formalization of a subset of WS-BPEL as a binding bigraphical reactive system using the BPL Tool developed in the Bigraphical Programming Languages (BPL) project. The tool allows for compositional definition, visualization and simulation of the execution of bigraphical reactive systems. The formalization exploits the close correspondence between bigraphs and XML to provide a formalized run-time format very close to standard WS-BPEL syntax. The formalization is the starting point of an endeavor to provide a completely formalized and extensible business process engine within the Computer Supported Mobile Adaptive Business Processes (CosmoBiz) research project at the IT University of Copenhagen. Building upon the formalization of WS-BPEL we propose and formalize HomeBPEL, a higher-order WS-BPEL-like business process execution language where processes are first-class values that can be stored in variables, passed as messages, and activated as embedded sub-instances. A sub-instance is similar to a WS-BPEL scope, except that it can be dynamically frozen and stored as a process in a variable, and then subsequently be thawed when reactivated as a sub-instance. We motivate HomeBPEL by an example of pervasive health care where treatment guidelines are dynamically deployed as sub processes that may be delegated dynamically to other workflow engines and in particular stay available for disconnected operation on mobile devices. ∗This work was funded in part by the Danish Research Agency (grant no.: 2106-07-0019, no.: 274-060415 and no.: 2059-03-0031) and the IT University of Copenhagen (the TrustCare, CosmoBiz and BPL projects).
Possible ionospheric preconditioning by shear flow leading to equatorial spread F

Abstract. Vertical shear in the zonal plasma drift speed is apparent in incoherent and coherent scatter radar observations of the bottomside F region ionosphere made at Jicamarca from about 1600–2200 LT. The relative importance of the factors controlling the shear, which include competition between the E and F region dynamos as well as vertical currents driven in the E and F regions at the dip equator, is presently unknown. Bottom-type scattering layers arise in strata where the neutral and plasma drifts differ widely, and periodic structuring of irregularities within the layers is telltale of intermediate-scale waves in the bottomside. These precursor waves appear to be able to seed ionospheric interchange instabilities and initiate full-blown equatorial spread F . The seed or precursor waves may be generated by a collisional shear instability. However, assessing the viability of shear instability requires measurements of the same parameters needed to understand shear flow quantitatively - thermospheric neutral wind and off-equatorial conductivity profiles. Keywords. Ionosphere (Equatorial ionosphere; ionospheric irregularities) – Space plasma physics (Waves and instabilities)
Strangers on a Plane: Context-Dependent Willingness to Divulge Sensitive Information

New marketing paradigms that exploit the capabilities for data collection, aggregation, and dissemination introduced by the Internet provide benefits to consumers but also pose real or perceived privacy hazards. In four experiments, we seek to understand consumer decisions to reveal or withhold information and the relationship between such decisions and objective hazards posed by information revelation. Our central thesis, and a central finding of all four experiments, is that disclosure of private information is responsive to environmental cues that bear little connection, or are even inversely related, to objective hazards. We address underlying processes and rule out alternative explanations by eliciting subjective judgments of the sensitivity of inquiries (experiment 3) and by showing that the effect of cues diminishes if privacy concern is activated at the outset of the experiment (experiment 4). This research highlights consumer vulnerabilities in navigating increasingly complex privacy issues intro.
Multivariate Locally Adaptive Density

SUMMARY: Multivariate versions of variable bandwidth kernel density estimators can be used to combat the eeects of the curse of dimensionality. They are also more exible than the xed bandwidth estimator to model complex (multimodal) densities. In this work, two variable bandwidth estimators are discussed: the balloon estimator which varies the smoothing matrix with each estimation point and the sample point estimator which uses a diierent smoothing matrix for each data point. Binning is used to compute the mean integrated squared error (MISE) for the sample point estimator. This allows a direct comparison between the xed, sample point, and the balloon estimator. Both adaptive estimators show considerable improvement in terms of MISE over the xed bandwidth estimator, and the sample point estimator beats the balloon estimator in two dimensions with moderate sample sizes. Parameterization of the smoothing matricies is also discussed and it is shown that while a more restrictive smoothing matrix can lead to improved estimates in practice, a more general smoothing matrix can lead to serious problems.
Expression of TaWRKY44, a wheat WRKY gene, in transgenic tobacco confers multiple abiotic stress tolerances

The WRKY transcription factors have been reported to be involved in various plant physiological and biochemical processes. In this study, we successfully assembled 10 unigenes from expressed sequence tags (ESTs) of wheat and designated them as TaWRKY44–TaWRKY53, respectively. Among these genes, a subgroup I gene, TaWRKY44, was found to be upregulated by treatments with PEG6000, NaCl, 4°C, abscisic acid (ABA), H2O2 and gibberellin (GA). The TaWRKY44-GFP fusion protein was localized to the nucleus of onion epidermal cells, and TaWRKY44 was able to bind to the core DNA sequences of TTGACC and TTAACC in yeast. The N-terminal of TaWRKY44 showed transcriptional activation activity. Expression of TaWRKY44 in tobacco plants conferred drought and salt tolerance and transgenic tobacco exhibited a higher survival rate, relative water content (RWC), soluble sugar, proline and superoxide dismutase (SOD) content, as well as higher activities of catalase (CAT) and peroxidase (POD), but less ion leakage (IL), lower contents of malondialdehyde (MDA), and H2O2. In addition, expression of TaWRKY44 also increased the seed germination rate in the transgenic lines under osmotic stress conditions while exhibiting a lower H2O2 content and higher SOD, CAT, and POD activities. Expression of TaWRKY44 upregulated the expression of some reactive oxygen species (ROS)-related genes and stress-responsive genes in tobacco under osmotic stresses. These data demonstrate that TaWRKY44 may act as a positive regulator in drought/salt/osmotic stress responses by either efficient ROS elimination through direct or indirect activation of the cellular antioxidant systems or activation of stress-associated gene expression.
Changes in Parental Emotional Support and Psychological Control in Early Adulthood

Early adulthood is a critical period during which real-world adjustment sets the stage for lifelong well-being. However, little is known about how the emotional quality of parental relationships may help or hinder adjustment. This longitudinal study investigated (a) changes in mother and father emotional support and psychological control during early adulthood, (b) whether such changes predicted young adults’ educational and occupational adjustment, and (c) whether these associations occurred indirectly through young adults’ depressive and anxiety symptoms. Participants were 240 youth assessed at four time points over a 6-year period. Multilevel modeling showed that on average, parental emotional support increased and psychological control decreased over time. Latent growth curve mediation analyses revealed significant direct associations between parental emotional support and psychological control and adjustment outcomes as well as indirect effects through mental health symptoms. Findings particularly highlight the negative effects of parental psychological control on young adults’ academic and occupational adjustment.
Automatic Generation of Integration and Preprocessing Ontologies for Biomedical Sources in a Distributed Scenario

Access to a large number of remote data sources has boosted research in biomedicine, where different biological and clinical research projects are based on collaborative efforts among international organizations. In this scenario, the authors have developed various methods and tools in the area of database integration, using an ontological approach. This paper describes a method to automatically generate preprocessing structures (ontologies) within an ontology-based KDD model. These ontologies are obtained from the analysis of data sources, searching for: (i) valid numerical ranges (using clustering techniques), (ii) different scales, (iii) synonym transformations based on known dictionaries and (iv) typographical errors. To test the method, experiments were carried out with four biomedical databases -containing rheumatoid arthritis, gene expression patterns, biological processes and breast cancer patients- proving the performance of the approach. This method supports experts in data analysis processes, facilitating the detection of inconsistencies.
On the (Ir)Relevance of Distribution and Labor Supply Distortion to Government Policy

Should the assessment of government policies, such as the provision of public goods and the control of externalities, deviate from first-best principles to account for distributive effects and for the distortionary cost of labor income taxation? For example, is the optimal extent of public goods provision smaller than indicated by the Samuelson rule because finance is distortionary? Or should environmental regulations fail to internalize externalities fully if the incidence of the regulations is regressive? It is suggested that these questions are best addressed by considering distribution-neutral implementation, in which budget balance is achieved by choosing an adjustment to the income tax that offsets the distributive impact of the policy in question. In basic cases, both distribution and labor supply distortion are moot because the target policy and the tax adjustment produce offsetting effects on each. Thus, traditional first-best principles provide good benchmarks for policy analysis after all. Moreover, even when actual implementation will not be distribution neutral in aggregate, distribution-neutral policy analysis has many conceptual and practical virtues that render it quite useful to investigators.
Effects of domain-specific SVM kernel design on the robustness of automatic speech recognition

We consider the effects of incorporating prior knowledge of features which correlate with phoneme identity as well as perceptual invariances into the design of SVM kernels for phoneme classification in high-dimensional spaces of acoustic waveforms of speech. To this end we explore products and linear combinations of polynomial and radial basis function kernels to design composite kernels which are invariant to waveform sign and time shift, and capture the dynamics of energy evolution in the time-frequency plane. Experiments show marked improvements in phoneme classification as a result of this custom kernel design. This demonstrates that even in high-dimensional feature spaces, careful kernel design based on prior knowledge of the problem domain can have significant payback.
TOWARDS A COMPLETE DETECTION/CORRECTION SYSTEM

In this paper we describe a system for detection and correction of lexical and syntactic errors in a French text. The lexical level uses several techniques (keys, phonetics and morphological generation). The aim of the syntactic level is verification of the structure of a sentence and of relations between words (e.g. agreement). It proceeds by unification of the decorations on the nodes of a dependency tree, by application of condition-action rules. By use of a morphological generator, corrections can be offered for agreement errors. We propose to integrate the two levels in a complete tool, based on a real size lexicon.
Text-Based Age and Gender Prediction for Online Safety Monitoring

This paper explores the capabilities of text-based age and gender prediction geared towards the application of detecting harmful content and conduct on social media. More specifically, we focus on the use case of detecting sexual predators who try to “groom” children online and possibly provide false age and gender information in their user profiles. We perform age and gender classification experiments on a dataset of nearly 380,000 Dutch chat posts from a social network. We evaluate and compare binary age classifiers trained to separate younger and older authors according to different age boundaries and find that macro-averaged Fscores increase when the age boundary is raised. Furthermore, we show that use-case applicable performance levels can be achieved for the classification of minors versus adults, thereby providing a useful component in a cybersecurity monitoring tool for social network moderators.
Event related synchronization and Hilbert Huang transform in the study of motor adaptation: A comparison of methods

The study of neural correlates of motor execution is commonly performed by means of event-related processing of electroencephalographic (EEG) recordings, in which each event refers to a standardized, repeatable movement. Some authors have proposed a valuable single-parameter method, the Event-Related Synchronization and Desynchronization (ERS/ERD) approach, for the identification of motor-related power modulation in each EEG frequency band. Under evolving experimental conditions (such as learning or adaptation), though, the repetition of a motor scheme becomes time-variant, and the employment of single-parameter descriptors no longer represents the optimal choice. This occurrence is typically found in motor learning and adaptation studies. In this work we compared the performance of the ERS/ERD method with the multi-parametric Hilbert Huang Transform (HHT). Results confirmed the statistically significant equivalence of the two methods in providing indexes of neural synchronization and desynchronization. Moreover, HHT allowed the tracking of frequency shifts in the alpha and beta EEG bands. The two methods were tested on an EEG dataset recorded during a motor adaptation test.
The Role of the Retention Coefficient the Role of the Retention Coefficient for the Scavenging and Redistribution of Highly Soluble Trace Gases by Deep Convective Cloud Systems: Model Sensitivity Studies Acpd the Role of the Retention Coefficient

The role of the retention coefficient (i.e. the fraction of a dissolved trace gas which is retained in hydrometeors during freezing) for the scavenging and redistribution of highly soluble trace gases by deep convective cloud systems is investigated using a modified version of the Weather Research and Forecasting (WRF) model. Results from cloud 5 system resolving model runs (in which deep convection is initiated by small random perturbations in association with so-called " large scale forcings (LSF) ") for a tropical oceanic (TOGA COARE) and a mid-latitude continental case (ARM) are compared to two runs in which bubbles are used to initiate deep convection (STERAO, ARM). In the LSF runs scavenging is found to almost entirely prevent a highly soluble tracer initially 10 located in the lowest 1.5 km of the troposphere from reaching the upper troposphere, independent of the retention coefficient. The release of gases from freezing hydrom-eteors leads to mixing ratio increases in the upper troposphere comparable to those calculated for insoluble trace gases only in runs in which bubbles are used to initiate deep convection. This result indicates that previous cloud resolving model studies us-15 ing bubbles to initiate deep convection may possibly have overestimated the influence of the retention coefficient on the vertical transport of highly soluble tracers. The retention coefficient is, however, found to play an important role for the scavenging and redistribution of highly soluble trace gases with a (chemical) source in the free tropo-sphere and also for trace gases for which even relatively inefficient transport may be 20 important.
Design and Implementation of Hybrid Broadcast Authentication Protocols in Wireless Sensor Networks

The proposed broadcast authentication protocols for wireless sensor networks can be divided into two categories, protocols based on digital signature and protocols based on improved message authentication code. This paper implements and evaluates the performance of two broadcast authentication: TinyECC, which is based on ECDSA, and GBA, which is based on improved MAC. Through analysis of the performance difference of the two protocols, this paper proposes a hybrid broadcast authentication protocol (HBA). HBA achieves an appropriate compromise of security and performance according to packet value. The analysis and experiments show that HBA is efficient and practical.
MPISE: Symbolic Execution of MPI Programs

Message Passing Interfaces (MPI) plays an important role in parallel computing. Many parallel applications are implemented as MPI programs. The existing methods of bug detection for MPI programs have the shortage of providing both input and non-determinism coverage, leading to missed bugs. In this paper, we employ symbolic execution to ensure the input coverage, and propose an on-the-fly schedule algorithm to reduce the interleaving explorations for non-determinism coverage, while ensuring the soundness and completeness. We have implemented our approach as a tool, called MPISE, which can automatically detect the deadlock and runtime bugs in MPI programs. The results of the experiments on benchmark programs and real world MPI programs indicate that MPISE finds bugs effectively and efficiently. In addition, our tool also provides diagnostic information and replay mechanism to help understand bugs.
Hand and object segmentation from RGB-D images for interaction with planar surfaces

We introduce a new approach for hand and object segmentation using RGB-D cameras suitable for gesture-based Human-Computer Interfaces (HCIs) that involve an interaction plane. The technique consists of detecting the interaction plane using a temporally coherent version of RANSAC, followed by segmenting off-plane objects using a markers-based watershed transform with an energy function that combines depth and chromaticity gradients. Experimental results show that our approach can segment the hand even when it is very close to the interaction plane, unlike traditional approaches based on distance thresholds.
On testing methods for biometric authentication

The use of biometric data for user authentication and/or recognition is now a reality. On the other hand, there is still a strong need for new technologies to overpass intrinsic limitations of already "established" techniques. This not only requires to devise new algorithms but to determine the real potential and limitations of existing techniques. This is possible only devising standard testing and assessment procedures based on statistical observations of the outputs of the system. In order to define better standard evaluation process, a system based on space-variant iconic image matching is described and the validation procedure defined. It turns out that all methods based on the same biometric measurements have the same intrinsic limitations, which can be only overcome by the adoption of a multi-modal or multi-algorithmic approach.
On dynamic packet fragmentation for traffic integration over bandwidth-limited links

We consider a home networking system for integrating packetized isochronous and best-effort traffic over a shared link with limited bandwidth, wherein the isochronous traffic comprises multiple isochronous flows, each associated with a periodic packet arrival process having a constant isochronous packet transmission period. In such a system, best-effort packets of variable size can render it impossible to guarantee QoS of the isochronous traffic. We propose a dynamic packet fragmentation method to integrate isochronous and best-effort traffic, in particular, fragmentation with fixed size or variable size frames. We show that the method effectively increases link utilization and best-effort traffic throughput, without violating the delay and jitter requirements for isochronous traffic.
Building a learning environment for research methods in psychology

Understanding research methodology can be very hard for students and several difficulties appear to them when faced with methodological problems. Certain applied courses expect students to have a good theoretical insight into research design and practical data-analysis while they have not been able to fully process the theory behind those. Theoretical courses provide the knowledge without the full context of practical research, which makes it hard for students to develop a profound understanding of the theory. Applied courses provide this kind of context without paying much attention to the lack of knowledge within the student population. This situation has created a gap between theory and applications of that theory. Most skills needed for applying research methodology cannot be learnt by merely absorbing knowledge. Designing experiments collecting data, or statistical analysis need some kind of problem solving skills which depend rather on insight in the problem than on theoretical knowledge. Such problem solving skills can best be taught using real life situations (Dewey, 1916). More importantly the context wherein problems are presented should correspond with the situations students will face in their academic or professional career. The methodological issues mentioned above are sometimes hard for students to understand because they are presented in a very abstract way. Teachers, however, do not always have the time or the means to provide several examples or to present a context wherein these issues could appear. Modern information technology can be used to support methodology teaching by presenting a context and in that way making learning more attractive (Norman & Schmidt, 1992). Moreover students are given the opportunity to study the problems in a more elaborate way (Norman & Schmidt, 1992). This paper presents ELEDES (short for Electronic learning environment for research design), a new software tool to simulate experimental data.
Knowledge and Semantic Technologies for Agile and Adaptive E-government

Managing knowledge assets in government has proven to be a critical factor in reinventing public administration and facilitating improved service provision. In the present paper we argue that an enabler to knowledge management in e-government is the use of semantic technologies, which would allow information access and use based on machine-processable semantics of data. Specifically we outline research efforts to use semantic technologies in order to facilitate two critical issues in e-government: (a) supporting change management and agility within the back-office processes of public administrations; and (b) facilitating the development of adaptive front-office processes.