Miracle-dz/UniFAR-FTUs huggingface dataset:
Absence of Rapid Propagation through the Purkinje Network as a Potential Cause of Line Block in the Human Heart with Left Bundle Branch Block

Background: Cardiac resynchronization therapy is an effective device therapy for heart failure patients with conduction block. However, a problem with this invasive technique is the nearly 30% of non-responders. A number of studies have reported a functional line of block of cardiac excitation propagation in responders. However, this can only be detected using non-contact endocardial mapping. Further, although the line of block is considered a sign of responders to therapy, the mechanism remains unclear. Methods: Herein, we created two patient-specific heart models with conduction block and simulated the propagation of excitation based on a cellmodel of electrophysiology. In one model with a relatively narrow QRS width (176 ms), we modeled the Purkinje network using a thin endocardial layer with rapid conduction. To reproduce a wider QRS complex (200 ms) in the second model, we eliminated the Purkinje network, and we simulated the endocardial mapping by solving the inverse problem according to the actual mapping system. Results: We successfully observed the line of block using non-contact mapping in the model without the rapid propagation of excitation through the Purkinje network, although the excitation in the wall propagated smoothly. This model of slow conduction also reproduced the characteristic properties of the line of block, including dense isochronal lines and fractionated local electrocardiograms. Further, simulation of ventricular pacing from the lateral wall shifted the location of the line of block. By contrast, in the model with the Purkinje network, propagation of excitation in the endocardial map faithfully followed the actual propagation in the wall, without showing the line of block. Finally, switching the mode of propagation between the two models completely reversed these findings. Conclusions: Our simulation data suggest that the absence of rapid propagation of excitation through the Purkinje network is the major cause of the functional line of block recorded by non-contact endocardial mapping. The line of block can be used to identify responders as these patients loose rapid propagation through the Purkinje network.
A Research Overview of the Siltation Loss Controls and Capacity Recovery Processes in China’s Reservoirs

There are many reservoirs in China with serious siltation issues which are affecting the function and safety of the reservoirs. Recently, research studies have been carried out regarding siltation loss control and capacity recovery technology due to the decreases in suitable dam sites for establishing reservoirs, and the increasingly serious siltation losses which have been occurring in the present reservoirs. The results of these studies have been of great significance to the partial recoveries of the siltation capacities of reservoirs, improvements in the respective efficiencies of the current reservoirs, and the prolonging of the service life the reservoirs. This study presented a simple review of the previous research findings regarding the current siltation loss situations and controls, as well as the capacity recoveries which have been achieved. Also, this study proposed the urgent need for in-depth examinations to be conducted pertaining to the national investigations of the reservoir siltation status in China, as well as a review of the current mechanisms and control measures for reservoir siltation losses.
Technologie de l ’ information Building Models from Sensor Data , an Application Shared by the Vision and Graphics Community *

The problem of building virtual models from sensor data increases in importance as powerful graphics rendering hardware becomes widespread. Model building stands at the interface between computer vision and computer graphics, and researchers from both areas have made contributions. We believe that only by a systematic review of the remaining open research question can further progress be made. This paper is an attempt at providing such a review. First, we describe the basic steps in the model building pipeline. Then we discuss the open problems that remain in each step. Finally, we describe some overall research themes that we believe should guide further work in this area.
TURBULENSI DAN LEGALISASI KLEPTOKRASI DALAM PENGELOLAAN KEUANGAN DESA

Abstrak: Turbulensi dan Legalisasi Kleptokrasi dalam Pengelolaan Keuangan Desa. Penelitian ini berusaha untuk mengkaji pengalaman dan pemahaman pengelola keuangan Desa Gambo di Kabupaten Samanta . Hal ini dilatarbelakangi oleh implementasi UU desa yang berimplikasi pada meningkatnya jumlah anggaran, namun dalam pengelolaannya ditemukan berbagai penyimpangan. Fenomenologi-hermeneutika digunakan untuk menemukan makna dan hakikat dari pengalaman dan pemahaman informan yang merupakan dysfunctional behavior . Temuan menunjukkan bahwa penyimpangan terjadi karena pelaku menerima berbagai tekanan. Keberadaan diskresi dan inkonsistensi kebijakan menjadi penyebab terjadinya legalisasi kleptokrasi. Pemangku kepentingan perlu memiliki komitmen dan konsistensi untuk mencegah dan meminimalkan terjadinya penyimpangan. Abstract: Turbulence and Legalised Kleptocracy on Village Financial Management . This research aims to analyse experiences and knowledges the financial manager of Gambo village. This is motivated by the implementation of village law that ha s implication for the budget amount increase, but has divergences in management . Phenomenologic-hermeunistic is applied to find the core experiences and knowledges of informants, which are dysfunctional behavior. The findings show that the divergence occurs because the actors r ec e iv e pressures. Discretion and inconsistence of policy have caused the divergence in village financial management and become legalised kleptocracy. Stakeholders commitment and consistency are needed to minimise the divergences .
Effects of Oceanographic Variability on the Trophic Ecology of Eight Species of Coral Reef Fishes From the Remote Central Pacific

Ecologists have long been interested in the factors that influence species’ ecological niches. Factors such as interand intraspecific competition, predation risk, and resource availability have been demonstrated to cause either expansions or constrictions in populations’ niches. Coral reefs represent complex systems rich in ecological interactions to study these effects on species’ niches. However, much of our knowledge of the ecological processes responsible for regulating community structure and function in tropical coral reefs originated in areas that were already strongly influenced by anthropogenic factors, such as fishing and eutrophication. In this study, I examined the role of natural oceanographic variation on the trophic ecology of eight common coral reef species spanning multiple trophic guilds. These fishes were collected from the Southern Line Islands, a chain of five remote, uninhabited islands spanning a strong primary productivity gradient in the central Pacific. A combination of stomach content and stable isotope analyses (δ15N, δ13C) were used to elucidate the spatial variability of diet composition, trophic niche width, and degree of individual dietary specialization in these species. I found evidence of spatial variation in diet composition for most of the species, with planktivorous species incorporating more larvaceans and foraminifera at productive islands and herbivores incorporating more invertebrates or filamentous algae at productive islands, depending on the species. Additionally, across species, populations tended to either have larger dietary niche widths and degree of individual specialization at the more productive islands or show no sign of change. The planktivores exhibited the strongest effect of
Multiple mobile target localization and pursuit based on discrete measurements of the energy intensity field

The application of mobile robotic sensor networks has been widely studied in target localization and pursuit. Conventional target tracking methods always require an explicit system observation model of the target positions, which, however, would fail if such model is unobtainable. In this paper, a distributed target localization and pursuit scheme is proposed based on discrete measurements of the target energy intensity field. The accurate observation model of such field is unknown except some critical bounds. By the proposed method, all robots are categorized into two groups: the leaders, responsible for the target pursuit, and the followers, responsible for the formation and connectivity maintenance. The proposed scheme is demonstrated by simulation of multiple target localization and pursuit.
Discovering configuration templates of virtualized tenant networks in multi-tenancy datacenters via graph-mining

Multi-tenant datacenter networking, with which multiple customer (tenant) networks are virtualized over a single shared physical infrastructure, is cost-effective but poses significant costs on manual configuration. Such tasks would be alleviated with configuration templates, whereas a crucial difficulty stems from creating appropriate (i.e., reusable) ones. In this work, we propose a graph-based method of mining configurations of existing tenants to extract their recurrent patterns that would be used as reusable templates for upcoming tenants. The effectiveness of the proposed method is demonstrated with actual configuration files obtained from a business datacenter network.
Learning Tractable Multidimensional Bayesian Network Classifiers

Multidimensional classification has become one of the most relevant topics in view of the many domains that require a vector of class values to be assigned to a vector of given features. The popularity of multidimensional Bayesian network classifiers has increased in the last few years due to their expressive power and the existence of methods for learning different families of these models. The problem with this approach is that the computational cost of using the learned models is usually high, especially if there are a lot of class variables. Class-bridge decomposability means that the multidimensional classification problem can be divided into multiple subproblems for these models. In this paper, we prove that class-bridge decomposability can also be used to guarantee the tractability of the models. We also propose a strategy for efficiently bounding their inference complexity, providing a simple learning method with an order-based search that obtains tractable multidimensional Bayesian network classifiers. Experimental results show that our approach is competitive with other methods in the state of the art and ensures the tractability of the learned models.
Substrate integrated hybrid Butler matrix

In this paper, a substrate integrated hybrid Butler matrix is proposed and experimented making full use of the mode-to-mode coupling effect between a half mode substrate integrated waveguide (HMSIW) and a conductor-backed slotline etched on its broad wall. Several microstrip-to-slotline transitions are employed to connect such four hybrid HMSIW-slotline structures and also offer required phase shifts. This type of hybrid Butler matrix not only keeps a compact and small physical dimension, but also associates the HMSIW's excellent property with the planar structure's flexibility and integrated circuit compatibility. Thus it is believed that this substrate integrated hybrid circuit (SIHC) technology has great potentialities for microwave and millimeter-wave applications.
Cluster structures for 2-Calabi–Yau categories and unipotent groups

Abstract We investigate cluster-tilting objects (and subcategories) in triangulated 2-Calabi–Yau and related categories. In particular, we construct a new class of such categories related to preprojective algebras of non-Dynkin quivers associated with elements in the Coxeter group. This class of 2-Calabi–Yau categories contains, as special cases, the cluster categories and the stable categories of preprojective algebras of Dynkin graphs. For these 2-Calabi–Yau categories, we construct cluster-tilting objects associated with each reduced expression. The associated quiver is described in terms of the reduced expression. Motivated by the theory of cluster algebras, we formulate the notions of (weak) cluster structure and substructure, and give several illustrations of these concepts. We discuss connections with cluster algebras and subcluster algebras related to unipotent groups, in both the Dynkin and non-Dynkin cases.
Geophysical Variables and Behavior: Xci. Ambulatory Behavior in Rats following Prenatal Exposures to Complex Magnetic Fields Designed to Interact with Genetic Expression

A total of 45 litters were exposed during their entire prenatal development to one of two complex patterns of magnetic fields whose strengths varied within one of four intensity ranges between 10 nT and 1000 nT or to sham-field conditions. The litters exposed to the most complex pattern, composed of 50 200-msec. presentations of different pulses for 10 sec. every 50 sec. , displayed more ambulation in an open field at 21 days of age than the litters that had been exposed continuously to a repetitive frequency-modulated field or to sham-field conditions. This treatment explained 25% of the variance in the numbers of squares traversed. The results suggest that complexity of the applied magnetic field during prenatal development may be more important than intensity for permanently affecting neuronal organization and behavior.
Dependence of field enhancement factor on power frequency voltage in vacuum

The objective of this paper is to determine the dependence of field enhancement factor β on power frequency (50 Hz) voltage in vacuum. A rod-plane vacuum gap was designed in a vacuum interrupter. Shots of ac power frequency voltage were applied at three vacuum gaps till breakdown occurred and the three vacuum gaps were 1.0 mm, 0.8 mm and 0.5 mm, respectively. The field emission current and applied voltage were measured at the same time. Through Fowler-Nordheim theory analysis, the electric field enhancement factor is obtained to represent a physical change of the emitters. The results showed the dependence of the field enhancement factor β on the applied voltage followed a “V” shape curve. The minimum β value, a turning point of the “V” shape curve, corresponded to a turning point voltage. The turning point voltage was about 90.1% ∼ 95.7% of the breakdown voltage. It could be an indication to predict a breakdown in vacuum.
Semi-supervised CCG Lexicon Extension

This paper introduces Chart Inference (CI), an algorithm for deriving a CCG category for an unknown word from a partial parse chart. It is shown to be faster and more precise than a baseline brute-force method, and to achieve wider coverage than a rule-based system. In addition, we show the application of CI to a domain adaptation task for question words, which are largely missing in the Penn Treebank. When used in combination with self-training, CI increases the precision of the baseline StatCCG parser over subject-extraction questions by 50%. An error analysis shows that CI contributes to the increase by expanding the number of category types available to the parser, while self-training adjusts the counts.
Automated melanoma recognition

A system for the computerized analysis of images obtained from epiluminescence microscopy (ELM) has been developed to enhance the early recognition of malignant melanoma. As an initial step, the binary mask of the skin lesion is determined by several basic segmentation algorithms together with a fusion strategy. A set of features containing shape and radiometric features as well as local and global parameters is calculated to describe the malignancy of a lesion. Significant features are then selected from this set by application of statistical feature subset selection methods. The final kNN classification delivers a sensitivity of 87% with a specificity of 92%.
Persistent Noise Signal in the FairfieldNodal Three‐Component 5‐Hz Geophones

Data from deployments of the FairfieldNodal three-component nodes were used to analyze a persistently observed noise signal. The noise signal is most prominent in the 20to 40-Hz range but has been observed anywhere in the 10to 100-Hz range. Interestingly, the signal is affected by air temperature and moves to higher frequencies in colder temperatures. Nodes that were deployed in seismic vaults directly on flat concrete slabs do not show the noise signal, and nodes that were buried in the ground or covered in snow show a significant decrease in the noise signal. This suggests that whatever is causing this signal may be mitigated by better coupling to the ground. Spectral analysis of hydrothermal tremor in the Upper Geyser Basin, Yellowstone, suggests this noise signal can interfere with the true ground vibration and can impede the ability to accurately characterize these signals. It is our recommendation to always bury the nodes if it is possible to reduce this noise signal that can interfere with natural signals of interest in a similar frequency band. In addition, tests to better estimate the best gain setting were done, and results show that above 12 dB, the waveforms of teleseismic events on the three-component nodes are very similar, suggesting that there is no advantage to using a gain setting higher than 18 dB for recording teleseismic events. If background noise is of interest in addition to teleseismic events, we see no adverse effects on the waveforms of teleseismic events using the max gain setting of 36 dB.
From gene names to actual genes

A common task in biomedical text mining is the recognition of gene names. In many applications though, it is important to know whether a gene name refers to the actual gene or to an entity related to it. This paper presents a trainable system to perform this task. It combines syntactic parsing with SVMs and achieves 78.63% accuracy. The training data used were generated automatically by a simple rule-based tagger. Such an approach can be useful to other fields which exhibit similar ambiguity in the way names are used to refer to entities.
Facebook and the Spiral of Silence: Examining the Social Media Dynamics among Female Students in Pakistan

The aim of this study is to investigate the way in which female Facebook users engage in political discourse, aligning its inquiry with Elisabeth Noelle-Neumann's seminal Spiral of Silence theory (1974). Focusing on key variables like participants' perceived opinion climate, willingness to express opinions, fear of social isolation, the research explores the dynamics within two distinct Facebook audience compositions: the expansive macro climate and the intimate micro-climate. The former encompasses a diverse range of connections, from old friends to online communities, while the latter involves daily interactions with friends, family, and significant others. Survey data (quantitative analysis) has been collected targeting university students in the federal capital and Rawalpindi. This study corroborates earlier findings, affirming the presence of the Spiral of Silence phenomenon on Facebook. Notably, it reveals that Pakistani women who use Facebook are more likely to express themselves in micro groups with friends and relatives compared to macro-Facebook communities with lots of individuals. The study confirmed that fear of isolation has a major impact on opinion expression in macro circles, and that opinion climate evaluation is significant for both circles.
Software for Computing and Annotating Genomic Ranges

We describe Bioconductor infrastructure for representing and computing on annotated genomic ranges and integrating genomic data with the statistical computing features of R and its extensions. At the core of the infrastructure are three packages: IRanges, GenomicRanges, and GenomicFeatures. These packages provide scalable data structures for representing annotated ranges on the genome, with special support for transcript structures, read alignments and coverage vectors. Computational facilities include efficient algorithms for overlap and nearest neighbor detection, coverage calculation and other range operations. This infrastructure directly supports more than 80 other Bioconductor packages, including those for sequence analysis, differential expression analysis and visualization.
An Examination of How Toxic Leadership Behaviours of School Principals Relate to Teachers' Perceived Stress

The study examines how toxic leadership behaviours of school principals relate to teachers' perceived stress. It is a correlational survey model, and the sample consists of 278 primary and secondary school teachers. We collected the data with the Perceived Stress Scale and Toxic Leadership Scale. The findings show that gender does not cause a statistical difference in perceived stress and all dimensions of toxic leadership. Stress levels of branch teachers are higher than those of primary school teachers, with a statistically significant difference. The perception of branch teachers in ignorance, self-interest, and negative mental state of toxic leadership is significantly higher than classroom teachers. A moderately significant positive relationship exists between teachers' perceptions of stress and all dimensions of toxic leadership. 20% of teachers' perceptions of stress are explained by toxic leadership. The negative mental state of school principals is a significant predictor of teachers' perceptions of stress.
Automatic Detection of Stable Grammatical Features in N-Grams

This paper presents an algorithm that allows the user to issue a query pattern, collects multi-word expressions (MWEs) that match the pattern, and then ranks them in a uniform fashion. This is achieved by quantifying the strength of all possible relations between the tokens and their features in the MWEs. The algorithm collects the frequency of morphological categories of the given pattern on a unified scale in order to choose the stable categories and their values. For every part of speech, and for all of its categories, we calculate a normalized Kullback-Leibler divergence between the category’s distribution in the pattern and its distribution in the corpus overall. Categories with the largest divergence are considered to be the most significant. The particular values of the categories are sorted according to a frequency ratio. As a result, we obtain morphosyntactic profiles of a given pattern, which includes the most stable category of the pattern, and their values.
A complete treatment of CMB anisotropies in a FRW universe

We generalize the total angular momentum method for computing cosmic microwave background anisotropies to Friedmann-Robertson-Walker ~FRW! spaces with arbitrary geometries. This unifies the treatment of temperature and polarization anisotropies generated by scalar, vector and tensor perturbations of the fluid, seed, or a scalar field, in a universe with constant comoving curvature. The resulting formalism generalizes and simplifies the calculation of anisotropies and, in its integral form, allows for a fast calculation of model predictions in linear theory for any FRW metric. @S0556-2821~98! 05006-1#