Miracle-dz/UniFAR-FTUs huggingface dataset:
Electrophysiological and Structural Remodeling in Heart Failure Modulate Arrhythmogenesis. 2D Simulation Study

Background Heart failure is operationally defined as the inability of the heart to maintain blood flow to meet the needs of the body and it is the final common pathway of various cardiac pathologies. Electrophysiological remodeling, intercellular uncoupling and a pro-fibrotic response have been identified as major arrhythmogenic factors in heart failure. Objective In this study we investigate vulnerability to reentry under heart failure conditions by incorporating established electrophysiological and anatomical remodeling using computer simulations. Methods The electrical activity of human transmural ventricular tissue (5 cm×5 cm) was simulated using the human ventricular action potential model Grandi et al. under control and heart failure conditions. The MacCannell et al. model was used to model fibroblast electrical activity, and their electrotonic interactions with myocytes. Selected degrees of diffuse fibrosis and variations in intercellular coupling were considered and the vulnerable window (VW) for reentry was evaluated following cross-field stimulation. Results No reentry was observed in normal conditions or in the presence of HF ionic remodeling. However, defined amount of fibrosis and/or cellular uncoupling were sufficient to elicit reentrant activity. Under conditions where reentry was generated, HF electrophysiological remodeling did not alter the width of the VW. However, intermediate fibrosis and cellular uncoupling significantly widened the VW. In addition, biphasic behavior was observed, as very high fibrotic content or very low tissue conductivity hampered the development of reentry. Detailed phase analysis of reentry dynamics revealed an increase of phase singularities with progressive fibrotic components. Conclusion Structural remodeling is a key factor in the genesis of vulnerability to reentry. A range of intermediate levels of fibrosis and intercellular uncoupling can combine to favor reentrant activity.
Efficient Analysis of Simultaneous Events in Distributed Simulation

Simultaneous events are a fundamental challenge in distributed discrete-event simulation: Different execution orders may lead to different simulation results. Commonly, simultaneous events are handled by tie-breaking rules in order to guarantee reproducibility. A second approach, however, is examining different execution orders with a branching mechanism. By analyzing the effects of simultaneous events, confidence in simulation results may be increased. Naturally, branching may get expensive with large numbers of simultaneous events. Thus, efficiency is crucial for branching in order to be a practical method. In this paper, we present an efficient branching mechanism for simultaneous events in distributed simulation, which may be used in conjunction with, or as an alternative to tie-breaking rules. We apply techniques which optimize the detection of simultaneous events and reduce the number of branches as much as possible. Furthermore, we use cloning to share computations among different branches.
Structure modeling of RNA using sparse NMR constraints

Abstract RNAs fold into distinct molecular conformations that are often essential for their functions. Accurate structure modeling of complex RNA motifs, including ubiquitous non-canonical base pairs and pseudoknots, remains a challenge. Here, we present an NMR-guided all-atom discrete molecular dynamics (DMD) platform, iFoldNMR, for rapid and accurate structure modeling of complex RNAs. We show that sparse distance constraints from imino resonances, which can be readily obtained from routine NMR experiments and easier to compile than laborious assignments of non-solvent-exchangeable protons, are sufficient to direct a DMD search for low-energy RNA conformers. Benchmarking on a set of RNAs with complex folds spanning up to 56 nucleotides in length yields structural models that recapitulate experimentally determined structures with all-heavy-atom RMSDs ranging from 2.4 to 6.5 Å. This platform represents an efficient approach for high-throughput RNA structure modeling and will facilitate analysis of diverse, newly discovered functional RNAs.
Gibbs sampling based Multi-scale Mixture Model for speaker clustering

The aim of this work is to apply a sampling approach to speech modeling, and propose a Gibbs sampling based Multi-scale Mixture Model (M3). The proposed approach focuses on the multi-scale property of speech dynamics, i.e., dynamics in speech can be observed on, for instance, short-time acoustical, linguistic-segmental, and utterance-wise temporal scales. M3 is an extension of the Gaussian mixture model and is considered a hierarchical mixture model, where mixture components in each time scale will change at intervals of the corresponding time unit. We derive a fully Bayesian treatment of the multi-scale mixture model based on Gibbs sampling. The advantage of the proposed model is that each speaker cluster can be precisely modeled based on the Gaussian mixture model unlike conventional single-Gaussian based speaker clustering (e.g., using the Bayesian Information Criterion (BIC)). In addition, Gibbs sampling offers the potential to avoid a serious local optimum problem. Speaker clustering experiments confirmed these advantages and obtained a significant improvement over the conventional BIC based approaches.
ICDAR 2003 page segmentation competition

There is a significant need to objectively evaluate layout analysis (page segmentation and region classification) methods. This paper describes the Page Segmentation Competition (modus operandi, dataset and evaluation criteria) held in the context of ICDAR2003 and presents the results of the evaluation of the candidate methods. The main objective of the competition was to evaluate such methods using scanned documents from commonly-occurring publications. The results indicate that although methods seem to be maturing, there is still a considerable need to develop robust methods that deal with everyday documents.
Identifying Dynamic Topics of Interest across Social Networks

Information propagation plays a significant role in online social networks, mining the latent information produced became crucial to understand how information is disseminated. It can be used for market prediction, rumor controlling, and opinion monitoring among other things. Thus, in this paper, an information dissemination model based on dynamic individual interest is proposed. The basic idea of this model is to extract effective topic of interest of each user overtime and identify the most relevant topics with respect to seed users. A set of experiments on real twitter dataset showed that the proposed dynamic prediction model which applies machine learning techniques outperformed traditional models that only rely on words extracted from tweets.
Constraint-aware learning of policies by demonstration

Many practical tasks in robotic systems, such as cleaning windows, writing, or grasping, are inherently constrained. Learning policies subject to constraints is a challenging problem. In this paper, we propose a method of constraint-aware learning that solves the policy learning problem using redundant robots that execute a policy that is acting in the null space of a constraint. In particular, we are interested in generalizing learned null-space policies across constraints that were not known during the training. We split the combined problem of learning constraints and policies into two: first estimating the constraint, and then estimating a null-space policy using the remaining degrees of freedom. For a linear parametrization, we provide a closed-form solution of the problem. We also define a metric for comparing the similarity of estimated constraints, which is useful to pre-process the trajectories recorded in the demonstrations. We have validated our method by learning a wiping task from human demonstration on flat surfaces and reproducing it on an unknown curved surface using a force- or torque-based controller to achieve tool alignment. We show that, despite the differences between the training and validation scenarios, we learn a policy that still provides the desired wiping motion.
Doing hard labour: gendered emotional labour in academic management

This paper explores, from the authors' experiences, emotional labour as gendered experience in the area of university management in Australia. University work (teaching and research) clearly involves high levels of emotional labour. Commitment, passion and curiosity in the self and created in others are keys to developing and transmitting knowledge. But what of the managerial roles within universities? To explore the gendered nature of managerial work in the university context, the authors related to each other three critical incidents associated with their work as senior managers. These narratives were explored to determine themes within our experiences. Some of the new forms of emotional labour found in our critical incidents suggest a need for further research and theorising. For example, our stories revealed a common theme of high levels of selfmonitoring. We found that high levels of self-monitoring in this context entail endless self-questioning of how we might be doing the job, at least doubling the work requirements, time and energy invested. This selfmonitoring often leads to self-punishment and selfdeprecation and the conduct of 'repair work' when perceiving that one has behaved 'badly'. We found it also led to self-justification and deficits in credits or the let offs given for perceived transgressions. Other similar experiences are explored in the paper. We conclude by analysing these experiences as a part of the identity construction of women as managers and raise the inherent contradiction that this identity formation presents. A final discussion of our methodology raises issues of selfdisclosure and authenticity and concludes by noting that many of the issues we have raised remain unresolved but are deeply embedded in our everyday experiences as women managers in academia. Disciplines Business | Social and Behavioral Sciences Publication Details Hort, L. , Barrett, M. & Fulop, L (2001). Doing hard labour gendered emotional labour in academic management. Conference on Critical Management Studies, UMIST, Manchester, UK, 11-13 July, 2001 (pp. 1-18). This conference paper is available at Research Online: http://ro.uow. edu.au/commpapers/755 Doing Hard Labour: Gendered Emotional Labour in Academic Management Linda Hort, Mary Barrett, Liz Fulop School of Marketing and Management Griffith University PMB 50 Gold Coast Mail Centre Queensland, 9726 Australia. Phone: +61 755528757 Fax: +61 7 55528085 E-mail: L.Hort@mailbox.gu. edu.au
Education in the wild: contextual and location-based mobile learning in action. A report from the STELLAR Alpine Rendez-Vous workshop series.

A new report has been published by the LSRI/University of Nottingham that gives an essential overview of research into location-based contextual mobile learning primarily across Europe, edited by Elizabeth Brown. The report follows on from a 2-day workshop funded by the STELLAR Network of Excellence as part of their 2009 Alpine Rendez-Vous workshop series. Contributors have provided examples of innovative and exciting research projects and practical applications for mobile learning in a location-sensitive setting, including the sharing of good practice and the key findings that have resulted from this work. (http://www.lsri.nottingham.ac.uk/ejb/preprints/ARV_Education_in_the_wild.pdf)
Mitral flow derived Doppler indices of left ventricular diastolic function in a general population; the Tromso study.

AIMS Left ventricular diastolic dysfunction has been proposed as the basis of heart failure in patients with normal left ventricular systolic function. Doppler indices of mitral inflow have been widely used to diagnose this condition and have been shown to correlate well with increased left atrial pressure in patients with cardiovascular disease. We wanted to establish age-specific criteria for normality of these indices in a large population and to determine the association of abnormal values to age and cardiovascular disease. METHODS AND RESULTS In our sample of subjects aged 25-85 years, 3022 had pulsed Doppler measurements of mitral inflow velocities and early inflow deceleration time. The association of these indices to age and gender were established in a 'healthy' reference subsample of 949 subjects. Age-specific percentiles showed a significant decline with increasing age for peak early mitral inflow velocity and the ratio of peak early and atrial inflow velocities (E/A ratio), whereas early inflow deceleration time and peak atrial inflow velocity showed a significant increase with increasing age. According to current criteria for diastolic dysfunction, the prevalence of dysfunction decreases with increasing age in the general population, as well as in the subgroup with cardiovascular disease. Only 7% of the variance in deceleration time was explained by cardiovascular disease or risk factors. For the E/A ratio, however, 41 and 48% of the variance were explained for men and women, respectively. CONCLUSION Age- and gender-specific criteria for normality are provided. Our data confirm the existence of a significant effect of age and gender on mitral Doppler indices of diastolic dysfunction. However, Doppler criteria for diastolic dysfunction based on these measurements need revision.
The image edge detection algorithm based on wavelet denoising and mathematics morphology

A new edge detection method based on the wavelet denoising and the mathematic morphology transform is presented in this paper. Firstly, the improved wavelet semisoft threshold method is used to suppress noise of image, where the algorithm of Bayes threshold is adopted to calculate the value of threshold. Secondly, A multi-scale and multi-structural elements morphological edge detection algorithms with entropy weights is presented and compared with two more popular morphological edge detection algorithms from three aspects (run times, SNR, precision). Finally, the comprehensive experiment shows that the improved edge detection based on the morphological transformation can get the more satisfactory results.
Step Motor Selection and Control: An Industrial Case Study

The process of selecting a step motor to an industrial application is not straightforward. Several aspects need to be considered at the beginning of the design, specially when dealing with a step motor due to its peculiar Speed × T orque relation. This paper presents a case study of a step motor selection for a food industryproblem, introducing the main aspects to be taken into account and the challenges this type of motor poses to meet the requirements. The intention is to describe the selection and design process and compare two different control approaches, first a classical approach using a lead/lag compensator, then a robust control approach using a H∞ control.
Hormonal changes during non-climacteric ripening in strawberry

In contrast to climacteric fruits, where ethylene is known to be pivotal, the regulation of ripening in non-climacteric fruits is not well understood. In the non-climacteric strawberry (Fragaria anannassa), auxin and abscisic acid (ABA) are thought to be important, but the roles of other hormones suggested to be involved in fruit development and ripening are not clear. Here changes in the levels of indole-3-acetic acid (IAA), ABA, GA1, and castasterone from anthesis to fully ripened fruit are reported. The levels of IAA and GA1 rise early in fruit development before dropping to low levels prior to colour accumulation. Castasterone levels are highest at anthesis and drop to very low levels well before ripening commences, suggesting that brassinosteroids do not play an important role in ripening in strawberry. ABA levels are low at anthesis and gradually rise through development and ripening. The synthetic auxin, 1-naphthaleneacetic acid (NAA), can delay ripening, but the application of GA3, the gibberellin biosythesis inhibitor paclobutrazol, and ABA had no significant effect. IAA and ABA levels are higher in the developing achenes than in the receptacle tissue and may be important for receptacle enlargement and ripening, and seed maturation, respectively. Contrary to a recent report, the biologically active GA4 was not detected. The pattern of changes in the levels of the hormones are different from those reported in another well studied non-climateric fruit, grape, suggesting that a single consistent pattern of hormone changes does not occur in this group of fruit during ripening.
On dual mining: from patterns to circumstances, and back

Previous work on frequent item set mining has focused on finding all itemsets that are frequent in a specified part of a database. We motivate the dual question of finding under what circumstances a given item set satisfies a pattern of interest (e.g., frequency) in a database. Circumstances form a lattice that generalizes the instance lattice associated with datacube. Exploiting this, we adapt known cube algorithms and propose our own, minCirc, for mining the strongest (e.g., minimal) circumstances under which an itemset satisfies a pattern. Our experiments show that minCirc is competitive with the adapted algorithms. We motivate mining queries involving migration between item set and circumstance lattices and propose the notion of Armstrong Basis as a structure that provides efficient support for such migration queries, as well as a simple algorithm for computing it.
Wireless sensor networks: a new regime for time synchronization

Wireless sensor networks (WSNs) consist of large populations of wirelessly connected nodes, capable of computation, communication, and sensing. Sensor nodes cooperate in order to merge individual sensor readings into a high-level sensing result, such as integrating a time series of position measurements into a velocity estimate. The physical time of sensor readings is a key element in this process called data fusion. Hence, time synchronization is a crucial component of WSNs. We argue that time synchronization schemes developed for traditional networks such as NTP [23] are ill-suited for WSNs and suggest more appropriate approaches.
Polar codes for bidirectional broadcast channels with common and confidential messages

We consider the bidirectional broadcast channel with common and confidential messages. We show that polar codes achieve the capacity of binary input symmetrical bidirectional broadcast channels with confidential messages, if one node's channel is a degraded version of the other node's channel. We also find a new bound on the cardinality of the auxiliary random variable in this setup.
Towards everyday language information retrieval systems via minicomputers

Minicomputer‐operated information retrieval (IR) systems are capable of employing relatively advanced methods, some of which are comparable with those employed in main‐frame systems. Many of these systems operate on dedicated machines and can therefore provide very rapid access to information, while remaining under the direct control of an information department. One system has now given over three years of satisfactory operation: this is MORPHS‐Minicomputer Operated Retrieval (Partially Heuristic) System. This system incorporates a number of linguistic features including the ability to find roots of words through affix stripping. Synonyms and compound words can also be handled and several search strategies (including SDI) are available. The latter have been developed considerably since the inception of the system. Consideration is given to the automation of the indexing process which is currently restricted to material for SDI.
Cross infection between cystic fibrosis patients colonised with Burkholderia cepacia

Whilst patient to patient spread of the respiratory pathogenBurkholderia cepacia is well recognised between patients with cystic fibrosis, prompting a strict segregation policy, cross colonisation between cystic fibrosis patients already infected withB cepacia has not been described and surveys show a very low incidence of patients with more than one strain. Five adult cystic fibrosis patients with B cepacia are presented who became cross colonised with a second B cepacia (UK epidemic) strain, four of whom then died, three from the cepacia syndrome. These cases show that, amongst segregated patients, cross colonisation with different B cepacia strains is possible, and even in these patients the acquisition of the UK epidemic strain may have a fatal outcome. In future it may be necessary to segregate cystic fibrosis patients colonised with the UK epidemic strain from all other patients with cystic fibrosis.
New Smith Predictor and RBF Neural Network Control for Networked Control Systems

This paper aims to the random and uncertain network delay, as well as controlled plant might be time-variant or nonlinear, a novel approach is proposed that novel Smith predictor combined with the radial basis function neural network (RBFNN) control for the networked control systems (NCS). This novel Smith predictor comes true to hide predictor models of the network delays of the forward and return paths into real network data transmission processes, therefore network delays don’t need to be measured, identified or estimated on-line. It is applicable to some occasions that the network delays are larger than one, even tens of sampling periods. Based on CSMA/CD (Ethernet), the results of simulation show validity of this control scheme, and indicate that system has better dynamic performance and anti-jamming ability.
DUBMMSM'12: international workshop on data-driven user behavioral modeling and mining from social media

Massive amounts of data are being generated on social media sites, such as Twitter and Facebook. This data can be used to better understand people, such as their personality traits, perceptions, and preferences, and predict their behavior. This deeper understanding of users and their behaviors can benefit a wide range of intelligent applications, such as advertising, social recommender systems, and personalized knowledge management. These applications will also benefit individual users themselves by optimizing their experiences across a wide variety of domains, such as retail, healthcare, and education. Since mining and understanding user behavior from social media often requires interdisciplinary effort, including machine learning, text mining, human-computer interaction, and social science, our workshop aims to bring together researchers and practitioners from multiple fields to discuss the creation of deeper models of individual users by mining the content that they publish and the social networking behavior that they exhibit.
Reducing Interrupting Duties of Medium -Voltage Circuit Breakers by Increasing Contact Parting Time

Interrupting duty of circuit breakers can be reduced by increasing the contact parting time, which is sum of tripping delay considered as one-half cycle in ANSI/IEEE standards and the circuit breaker opening time, which is a function of the breaker interrupting time. The contact parting time is fixed, however the tripping delay can be increased. Though this method is not discussed in current technical literature, it is valid according to ANSI/IEEE standards. Immediate replacement of the circuit breakers or other means to reduce interrupting duties can be avoided, resulting in large cost savings and also process downtime. The problem occurred in a large paper mill distribution system, where the circuit breakers were applied well within their close and latch ratings, but the interrupting duty exceeded by 6%. By introducing an additional tripping delay of one cycle, the interrupting duty is reduced and the existing breakers can be retained in service. The paper demonstrates these calculations.