Miracle-dz/UniFAR-FTUs huggingface dataset:
Occurrence of Antimicrobial-Resistant Escherichia coli and Salmonella enterica in the Beef Cattle Production and Processing Continuum

ABSTRACT Specific concerns have been raised that third-generation cephalosporin-resistant (3GCr) Escherichia coli, trimethoprim-sulfamethoxazole-resistant (COTr) E. coli, 3GCr Salmonella enterica, and nalidixic acid-resistant (NALr) S. enterica may be present in cattle production environments, persist through beef processing, and contaminate final products. The prevalences and concentrations of these organisms were determined in feces and hides (at feedlot and processing plant), pre-evisceration carcasses, and final carcasses from three lots of fed cattle (n = 184). The prevalences and concentrations were further determined for strip loins from 103 of the carcasses. 3GCr Salmonella was detected on 7.6% of hides during processing and was not detected on the final carcasses or strip loins. NALr S. enterica was detected on only one hide. 3GCr E. coli and COTr E. coli were detected on 100.0% of hides during processing. Concentrations of 3GCr E. coli and COTr E. coli on hides were correlated with pre-evisceration carcass contamination. 3GCr E. coli and COTr E. coli were each detected on only 0.5% of final carcasses and were not detected on strip loins. Five hundred and 42 isolates were screened for extraintestinal pathogenic E. coli (ExPEC) virulence-associated markers. Only two COTr E. coli isolates from hides were ExPEC, indicating that fed cattle products are not a significant source of ExPEC causing human urinary tract infections. The very low prevalences of these organisms on final carcasses and their absence on strip loins demonstrate that current sanitary dressing procedures and processing interventions are effective against antimicrobial-resistant bacteria.
Divergence in genital morphology may contribute to mechanical reproductive isolation in a millipede

Genitalia appear to evolve rapidly and divergently in taxa with internal fertilization. The current consensus is that intense directional sexual selection drives the rapid evolution of genitalia. Recent research on the millipede Antichiropus variabilis suggests that the male genitalia are currently experiencing stabilizing selection – a pattern of selection expected for lock-and-key structures that enforce mate recognition and reproductive isolation. Here, we investigate how divergence in genital morphology affects reproductive compatibility among isolated populations of A. variabilis. Females from a focal population were mated first to a male from their own population and, second, to a male from one of two populations with divergent genital morphology. We observed variation in mating behavior that might indicate the emergence of precopulatory reproductive barriers: males from one divergent population took significantly longer to recognize females and exhibited mechanical difficulty in genital insertion. Moreover, we observed very low paternity success for extra-population males who were successful in copulating. Our data suggest that divergence in genital shape may be contributing to reproductive isolation, and incipient speciation among isolated populations of A. variabilis.
Semiparametric Approaches for Joint modeling of Longitudinal and Survival Data with Time Varying Coefficients

This working paper is hosted by The Berkeley Electronic Press (bepress) and may not be commercially reproduced without the permission of the copyright holder. In clinical trials, information is often collected on a time-to-event (e.g. " survival ") and time-dependent and time-independent covariates. An example is given by AIDS Clinical Trials Group (ACTG) Protocol 175, a randomized trial to compare zidovudine alone, zidovudine plus didanosine, zidovudine plus zalcitabine, or didanosine alone, in HIV-infected subjects on the basis of time to progression to AIDS or death (Hammer November 1994. CD4 count, as a reflection of immune status, was measured for each participant about every 12 weeks after randomization. It is well known that observations of CD4 count are subject to substantial biological variation and measurement error. In survival analysis, a routine objective is to characterize the relationship between survival and the covariates. Standard inference procedures usually require the true values of the covariates at the event times. However, covariates like CD4 count may be subject to substantial measurement error. In addition, longitudinal covariates are usually collected intermittently and may not observed at the event times. Naive approaches that ignore measurement error might lead to biased estimation and misleading inference (Pren-tice, 1982; Tsiatis and Davidian 2001; Song and Huang 2005b). A popular approach to dealing with the aforementioned measurement error is to use a joint model, which assumes that the longitudinal observations follow a mixed effects model and the survival time depends on the random effects of the mixed effects model through a survival model. The mixed effects model may be viewed as an extension of the standard additive measurement error model for time-independent covariates and the joint modeling approaches may be applied to repeated measured time-independent covariates as well (Wang, Wang and Wang, 2000). In joint modeling, the most widely used survival model is the proportional hazards model. Various approaches have been proposed under this framework, including the regression calibration (e. However, the proportional hazards assumption may be too restrictive in practice. For example, in AIDS studies, it is well known that the effect of the anti-retrovival treatments may decay after some time. More flexible models are needed to characterize such covariate effects. An appealing alternative is the time-varying-coefficient proportional hazards model, which allows the effect of coefficients to vary over time. In the case of no measurement error, this model has been studied by Zucker and Karr (1990) using the …
A multi-class SVM based phonemes classifier based on a trainable confidence measure

Although the recognition results of support vector machines(SVM) are very promising in many applications, there is a gap between the accuracy of SVM based speech recognizers and time series models (e.g. hidden Markov model) in speech recognition. The main reasons are the lack of proper methods to classify the acoustic units into more than two classes and suitable SVM based sequence decoders. This paper describes a trainable method for SVM multi-class classification based on confidence measures of the sets of two-class SVM classifiers using an artificial neural network. In addition, a pruning method has been proposed for SVM multi-class classification to decrease the computational complexity without significant decrease in accuracy. Also, a method has been proposed for time series recognition of the feature vectors of an utterance based on SVM classifiers. The experiments have been conducted on a set of confusable phonemes using TIMIT corpus. The results of the first method show 10% and 6% relative improvements in the recognition rate in comparison to one-versus-one and Kruger methods respectively for /b/, /d/ and /g/ phonemes. In addition, it is empirically deduced that the proposed phoneme classification framework yields significantly better classification rates than classic voting method. Comparing phoneme classification results of the proposed method with one-versus-one method indicate a 26% improvement in the classification rate for /b/, /d/ and /g/ phonemes.
Mechanisms of improvement of respiratory failure in patients with restrictive thoracic disease treated with non-invasive ventilation

Background: Nocturnal non-invasive ventilation (NIV) is an effective treatment for hypercapnic respiratory failure in patients with restrictive thoracic disease. We hypothesised that NIV may reverse respiratory failure by increasing the ventilatory response to carbon dioxide, reducing inspiratory muscle fatigue, or enhancing pulmonary mechanics. Methods: Twenty patients with restrictive disease were studied at baseline (D0) and at 5–8 days (D5) and 3 months (3M). Results: Mean (SD) daytime arterial carbon dioxide tension (Paco2) was reduced from 7.1 (0.9) kPa to 6.6 (0.8) kPa at D5 and 6.3 (0.9) kPa at 3M (p = 0.004), with the mean (SD) hypercapnic ventilatory response increasing from 2.8 (2.3) l/min/kPa to 3.6 (2.4) l/min/kPa at D5 and 4.3 (3.3) l/min/kPa at 3M (p = 0.044). No increase was observed in measures of inspiratory muscle strength including twitch transdiaphragmatic pressure, nor in lung function or respiratory system compliance. Conclusions: These findings suggest that increased ventilatory response to carbon dioxide is the principal mechanism underlying the long term improvement in gas exchange following NIV in patients with restrictive thoracic disease. Increases in respiratory muscle strength (sniff oesophageal pressure and sniff nasal pressure) correlated with reductions in the Epworth sleepiness score, possibly indicating an increase in the ability of patients to activate inspiratory muscles rather than an improvement in contractility.
Survey of Load Balancing and Scaling approaches in cloud

In cloud, scaling is the ability to provide the services without lagging performance, in case of increased or decreased load. The system should be able to adapt to the customer request so as to increase resources or decrease the resources, so as to maintain the balance between performance and cost effectiveness. For scaling the application it is required to increase or decrease the application instances. While doing this load on physical machines also needs to be taken into consideration for maintaining a good performance. In this paper we have studied the existing load balancing algorithm and different approaches used for scaling in cloud computing.
HCN Channels—Modulators of Cardiac and Neuronal Excitability

Hyperpolarization-activated cyclic nucleotide-gated (HCN) channels comprise a family of cation channels activated by hyperpolarized membrane potentials and stimulated by intracellular cyclic nucleotides. The four members of this family, HCN1–4, show distinct biophysical properties which are most evident in the kinetics of activation and deactivation, the sensitivity towards cyclic nucleotides and the modulation by tyrosine phosphorylation. The four isoforms are differentially expressed in various excitable tissues. This review will mainly focus on recent insights into the functional role of the channels apart from their classic role as pacemakers. The importance of HCN channels in the cardiac ventricle and ventricular hypertrophy will be discussed. In addition, their functional significance in the peripheral nervous system and nociception will be examined. The data, which are mainly derived from studies using transgenic mice, suggest that HCN channels contribute significantly to cellular excitability in these tissues. Remarkably, the impact of the channels is clearly more pronounced in pathophysiological states including ventricular hypertrophy as well as neural inflammation and neuropathy suggesting that HCN channels may constitute promising drug targets in the treatment of these conditions. This perspective as well as the current therapeutic use of HCN blockers will also be addressed.
HIV model with intracellular delay — a mathematical study

Human Immunodeficiency Virus (HIV) is observed to infect the CD4+T lymphocytes in the human blood. In this article we consider a modification of a basic HIV model introduced by Herz et al. [1] representing the HIV dynamics. We introduce an intracellular delay in the disease transmission term. Our theoretical and numerical analysis show that a HIV infected subject will remain infected irrespective of the initial viral load and CD4+T cells count. However, some crucial system parameters may significantly alter the concentrations of both CD4+T cells and the HIV populations. Systematic control of these model parameters may find potential application towards better management of the disease.
Visualizing ncRNA Structural Evolution with Arc Diagrams

The second challenge of this year’s BioVis Symposium Design Contest was to create a visualization of noncoding RNA (ncRNA) structural evolution of the human accelerated region 1 (HAR1) gene in ancestral, denisovan, and human sequences. The commonly used chart types for this data, dot plots and node-link style graphs, do not support direct comparison of base pairings among the three structures. We propose a redesign that uses arc diagram visualization techniques to highlight conserved or otherwise evolved base pairings. These diagrams support the placement of unique and prevalent base pairings along a common scale and allow mapping task-specific features to color, providing viewers with a more direct means to identify differences in the structure predictions.
Video Quality assessment Measure with a Neural Network

— In this paper, we present the video quality measure estimation via a neural network. This latter predicts MOS (mean opinion score) by providing height parameters extracted from original and coded videos. The eight parameters that are used are: the average of DFT differences, the standard deviation of DFT differences, the average of DCT differences, the standard deviation of DCT differences, the variance of energy of color, the luminance Y, the chrominance U and the chrominance V. We chose Euclidean Distance to make comparison between the calculated and estimated output.
What museums do we want in France in the future?

ABSTRACT In France on 17 May 2016, Audrey Azoulay, the then Minister of Culture and Communication, launched a debate inviting input from all the museums in the Musées de France network in an effort to identify the main guidelines for museum policy in respect of the challenges facing a society in transition. This article explores, in the following order: the circumstances in which the invitation was issued; the boundaries defining the mandate of the Museums of the twenty-first Century Project team tasked with implementing it; that team’s methods; and the results achieved.
CHAOS OF HENON MAP BASED ON THE COUPLED NETWORKS

In this paper, the relationship between the parameters of Henon map is studied, and the chaos of Henon map is also discussed based on different coupled networks. From the simulate results, we found with the increasing of parameter a the chaos of Henon map will be emerged. At the same time, the transition from non-chaotic to chaotic in coupled networks is exhibited, although the parameters in non-chaotic regions before they are coupled together.
Interactive Dissection of Digital Organs Based on Metaballs

This paper describes an interactive dissection approach based on metaballs for digital organs in virtual surgery. For organ's geometry, we employ a novel hybrid model comprising both inner metaballs and high-resolution surface mesh with texture. Using metaballs, the organ interior is geometrically simplified via a set of overlapping spheres with different radii. For physical representation, we present a hybrid framework to interlink metaballs with moving least squares (MLS) based meshfree method. MLS enables the direct and rapid transition from metaballs to local nodal formulations in physical modeling. For soft tissue dissection, the nature of our MLS-driven meshfree method also facilitates adaptive topology modification and cutting surface reconstruction. As nodal points only exist temporarily in localized regions adjacent to the cutting path, our method could generate accurate cutting surface without sacrificing real-time computational efficiency.
Increasing information transfer rates for brain-computer interfacing

The goal of a Brain-Computer Interface (BCI) consists of the development of a unidirectional interface between a human and a computer to allow control of a device only via brain signals. While the BCI systems of almost all other groups require the user to be trained over several weeks or even months, the group of Prof. Dr. Klaus-Robert Müller in Berlin and Potsdam, which I belong to, was one of the first research groups in this field which used machine learning techniques on a large scale. The adaptivity of the processing system to the individual brain patterns of the subject confers huge advantages for the user. Thus BCI research is considered a hot topic in machine learning and computer science. It requires interdisciplinary cooperation between disparate fields such as neuroscience, since only by combining machine learning and signal processing techniques based on neurophysiological knowledge will the largest progress be made. In this work I particularly deal with my part of this project, which lies mainly in the area of computer science. I have considered the following three main points: Establishing a performance measure based on information theory: I have critically illuminated the assumptions of Shannon’s information transfer rate for application in a BCI context. By establishing suitable coding strategies I was able to show that this theoretical measure approximates quite well to what is practically achieveable. Transfer and development of suitable signal processing and machine learning techniques: One substantial component of my work was to develop several machine learning and signal processing algorithms to improve the efficiency of a BCI. Based on the neurophysiological knowledge that several independent EEG features can be observed for some mental states, I have developed a method for combining different and maybe independent features which improved performance. In some cases the performance of the combination algorithm outperforms the best single performance by more than 50 %. Furthermore, I have theoretically and practically addressed via the development of suitable algorithms the question of the optimal number of classes which should be used for a BCI. It transpired that with BCI performances reported so far, three or four different mental states are optimal. For another extension I have combined ideas from signal processing with those of machine learning since a high gain can be achieved if the temporal filtering, i.e., the choice of frequency bands, is automatically adapted to each subject individually. Implementation of the Berlin brain computer interface and realization of suitable experiments: Finally a further substantial component of my work was to realize an online BCI system which includes the developed methods, but is also flexible enough to allow the simple realization of new algorithms and ideas. So far, bitrates of up to 40 bits per minute have been achieved with this system by absolutely untrained users which, compared to results of other groups, is highly successful.
Distributed MIMO in multi-cell wireless systems via finite-capacity links

Infrastructure networks, such as cellular systems, are expected to benefit from both multicell processing (cooperation at the base station level) and relaying (cooperation at the user level). This paper provides a brief review of recent results concerning the analysis of such technologies, under the practical assumption that both multicell processing and user cooperation are enabled by error-free but limited-capacity inter-base station and inter-user links, respectively. The focus is on non-fading uplink and downlink channels based on Wyner-type cellular models. The analytical treatment enhances the insight into the potential and the limitations imposed by capacity constraints on the performance gains provided by cooperative (distributed MIMO) techniques.
Plasticity in the Spinal Cord Afferent Input Modulates Neurotrophins and Synaptic

[PDF] [Full Text] [Abstract] , October 1, 2005; 128 (10): 2338-2358. Brain and V. R. Edgerton G. Courtine, R. R. Roy, J. Raven, J. Hodgson, H. Mckay, H. Yang, H. Zhong, M. H. Tuszynski tract lesion in monkeys (Macaca mulatta) Performance of locomotion and foot grasping following a unilateral thoracic corticospinal [PDF] [Abstract] , December 1, 2005; 19 (4): 283-295. Neurorehabil Neural Repair S. Vaynman and F. Gomez-Pinilla Nervous System by Using Neurotrophins License to Run: Exercise Impacts Functional Plasticity in the Intact and Injured Central
0 60 80 63 v 2 2 0 A ug 2 00 6 The Causal Boundary of spacetimes revisited

We present a new development of the causal boundary of spacetimes, originally introduced by Geroch, Kronheimer and Penrose. Given a strongly causal spacetime (or, more generally, a chronological set), we reconsider the GKP ideas to construct a family of completions with a chronology and topology extending the original ones. Many of these completions present undesirable features, like those appeared in previous approaches by other authors. However, we show that all these deficiencies are due to the attachment of an “unnecessarily big” boundary. In fact, a notion of “completion with minimal boundary” is then introduced in our family such that, when we restrict to these minimal completions, which always exist, all previous objections disappear. The optimal character of our construction is illustrated by a number of satisfactory properties and examples.
Leadership and Stress Orientation of Japanese and Russian Working Adults

This cross-cultural study utilized the full range leadership framework developed by Hofstede’s model of culture, and compared leadership styles and cultural values of 461 managerial and non-managerial employees in government and business organizations in Russia and Japan. In this article, we examine the stress, task and relationship orientations of people in Russia and in Japan. As a result of the analysis of 461 responses, some significant differences were found between the two samples. It appears that Russian respondents have higher scores on task (initiating structure) and relationship (consideration style) orientations than Japanese respondents. While gender is a significant factor in task orientation, results did not demonstrate any differences in the relationship orientations and stress perceptions of these respondents. In this article, literature on Japan and Russian cultures is presented along with practical application, suggestions and implications for future studies. The projected results of this study include better cross-cultural understanding, comparison and assessment of Japanese and Russian leadership by foreign and local organizational members.
Memory arbitration and cache management in stream-based systems

With the ongoing advancements in VLSI technology the performance of an embedded system is determined to a large extent by the communication of data and instructions. This results in new methods for on- and off-chip communication and caching schemes. In this paper we use an arbitration scheme that exploits the characteristics of continuous 'media' streams while minimizing the latency for random (e.g. CPU) memory accesses to background memory. We also introduce a novel caching scheme for a stream-based multiprocessor architecture, to limit as much as possible the amount of on-chip buffering required to guarantee the throughput of the continuous streams. With these two schemes we can build an architecture for media processing with optimal flexibility at run-time while performance guarantees can be determined at compile-time.