Miracle-dz/UniFAR-FTUs huggingface dataset:
Influence of Biphasic Stimulation on Olfactory Ensheathing Cells for Neuroprosthetic Devices

The recent success of olfactory ensheathing cell (OEC) assisted regeneration of injured spinal cord has seen a rising interest in the use of these cells in tissue-engineered systems. Previously shown to support neural cell growth through glial scar tissue, OECs have the potential to assist neural network formation in living electrode systems to produce superior neuroprosthetic electrode surfaces. The following study sought to understand the influence of biphasic electrical stimulation (ES), inherent to bionic devices, on cell survival and function, with respect to conventional metallic and developmental conductive hydrogel (CH) coated electrodes. The CH utilized in this study was a biosynthetic hydrogel consisting of methacrylated poly(vinyl-alcohol) (PVA), heparin and gelatin through which poly(3,4-ethylenedioxythiophene) (PEDOT) was electropolymerised. OECs cultured on Pt and CH surfaces were subjected to biphasic ES. Image-based cytometry yielded little significant difference between the viability and cell cycle of OECs cultured on the stimulated and passive samples. The significantly lower voltages measured across the CH electrodes (147 ± 3 mV) compared to the Pt (317 ± 5 mV), had shown to influence a higher percentage of viable cells on CH (91–93%) compared to Pt (78–81%). To determine the functionality of these cells following electrical stimulation, OECs co-cultured with PC12 cells were found to support neural cell differentiation (an indirect measure of neurotrophic factor production) following ES.
Low-Cost Checkpointing and Failure Recovery in Mobile Computing Systems

A mobile computing system consists of mobile and stationary nodes, connected to each other by a communication network. The presence of mobile nodes in the system places constraints on the permissible energy consumption and available communication bandwidth. To minimize the lost computation during recovery from node failures, periodic collection of a consistent snapshot of the system (checkpoint) is required. Locating mobile nodes contributes to the checkpointing and recovery costs. Synchronous snapshot collection algorithms, designed for static networks, either force every node in the system to take a new local snapshot, or block the underlying computation during snapshot collection. Hence, they are not suitable for mobile computing systems. If nodes take their local checkpoints independently in an uncoordinated manner, each node may have to store multiple local checkpoints in stable storage. This is not suitable for mobile nodes as they have small memory. This paper presents a synchronous snapshot collection algorithm for mobile systems that neither forces every node to take a local snapshot, nor blocks the underlying computation during snapshot collection. If a node initiates snapshot collection, local snapshots of only those nodes that have directly or transitively affected the initiator since their last snapshots need to be taken. We prove that the global snapshot collection terminates within a finite time of its invocation and the collected global snapshot is consistent. We also propose a minimal rollback/recovery algorithm in which the computation at a node is rolled back only if it depends on operations that have been undone due to the failure of node(s). Both the algorithms have low communication and storage overheads and meet the low energy consumption and low bandwidth constraints of mobile computing systems.
A new reconfigurable methodology to implement the 8-bit linear quantization for real-time SAR

With the developing of science and technology, microwave remote sensing has been widely applied to many areas of production and life. Synthetic Aperture Radar (SAR) which can provide high-resolution images, has become an important means of objective observation and surveillance in military and civilian fields. This paper based on the analysis of SAR radar echo data characteristics, using the peak clipping quantization to complete the 8-bit quantification processing of the 32-bit single precision floating point SAR raw data in the field programmable gate array (FPGA) hardware platform. Finally, comparing the results of hardware implementation and the theoretical results of the MATLAB, the consequence indicates the effectiveness and availability of the SAR 8-bit quantization processing in the real-time system.
Community detection on heterogeneous networks by multiple semantic-path clustering

Heterogeneous networks have become a commonly used model to represent complex and abstract social phenomena. They allow objects to have many different relationships and represent relationships by semantic paths which connect object types via a sequence of relations. A major challenge in community detection on heterogeneous networks is how to organize and combine different semantic paths. In order to acquire desired clustering, we propose a novel community detection method for heterogeneous networks based on matrix decomposition and semantic paths. The major advantage of this method is to treat objects individually and to assign them with different combinations of semantic-path weights so as to improve the clustering quality. The comparative experiments of the proposed method with another two state-of-the-art methods, spectral clustering and path-selection clustering, confirms that it can acquire desired clustering results better.
Computational load reduction for anomaly detection in hyperspectral images: An experimental comparative analysis

In this manuscript we investigate the efficient implementation of anomaly detection strategies in hyperspectral images. We especially focus on methods to reduce the computational complexity for a fast implementation of the detection algorithms. In particular, we consider two strategies based on data fusion methods applied to the outputs of the optical heads of the hyperspectral sensor. Furthermore, we consider, two computationally efficient implementations of anomaly detection where the well known RX algorithm is applied to hyperspectral data after dimensionality reduction. The detection performances of the anomaly detection strategies are compared using real data acquired by the MIVIS sensor. An estimate of the reduction of the computational load achieved with the different techniques is also provided.
Short Presentation : Combining Garbage Collection and Safe Manual Memory Management

Garbage collection (GC) provides an elegant, convenient, and safe approach to managing memory. For many applications, it is an appropriate technique for all data. For other applications, it works well only for most data. For example, it may complicate data-level interoperability with legacy code or exhibit poor performance with respect to a few critical data types. In other systems, such as embedded devices and operating systems, the environment may simply prove too hostile for GC to be a realistic technique. Unfortunately, an approach to memory management is often a system-wide decision, made when choosing a run-time system or even when choosing a language. Furthermore, using malloc and free, as in C, usually requires sacrificing safety. We believe programming languages should support manual and automatic memory-management, allowing programmers to choose the mechanisms most appropriate for (different parts of) their applications. They should us GC when possible and manual techniques when necessary, with smooth intra-language evoluation paths among the options. At the same time, the language should remain safe, which to us means (at least) two things. First, programs should not crash (or worse, silently misbehave) because the same memory is simultaneously used for different types. Second, parts of an application should be able to maintain private state by allocating fresh memory and restricting access to it. The key to both requirements is to prohibit dangling-pointer dereferences; making the allocator type-safe by partitioning memory into typed pools satisfies the first requirement but not the second. Toward this end of safe, flexible memory management we have designed and implemented a comprehensive memorymanagement framework meeting our requirements in the context of the Cyclone programming language. Cyclone is a type-safe, C-like language intended for use in systems programs where control is needed over low-level details such as data representations and resource management. In the remainder of this paper, we provide an overview of our approach in Cyclone, summarizing technical results presented in other papers [2, 3]. We present some performance measurements that show how manual and automatic memory management can be combined to good effect, and lay out plans for future work.
Labor Force Behavior of Hispanic Elderly : Insights from HRS No . 96-032

This paper seeks to augment the relatively scarce information available about the labor market and economic characteristics of Hispanic elderly. Specifically, we examine the factors associated with the late-aged labor force participation decisions of elderly Hispanic men and women, and how they are related to aggregate economic well-being. Our results indicate a high degree of labor force instability and involuntary joblessness among older Hispanics. For many Hispanic elders, retirement is not the voluntary termination of a career job, but instead results from prolonged or frequent periods of joblessness that eventuate in retirement. This process of labor force withdrawal was markedly different for men and women, and was influenced by age, education, job characteristics (e.g., firm size and industrial sector), and employment experience (e.g., experience of being laid off and pension coverage). Low rates of pension coverage and low savings for retirement among the Hispanic elderly imply a high degree of economic vulnerability, especially for the unmarried elderly and for those who do not receive assistance from other family members. Data used: Health and Retirement Study: U.S., 1992 (first wave) and 1994
An Investigation into Multivariate Variance Ratio Statistics and Their Application to Stock Market Predictability

We propose several multivariate variance ratio statistics. We derive the asymptotic distribution of the statistics and scalar functions thereof under the null hypothesis that returns are unpredictable after a constant mean adjustment (i.e., under the weak form Efficient Market Hypothesis). We do not impose the no leverage assumption of Lo and MacKinlay (1988) but our asymptotic standard errors are relatively simple and in particular do not require the selection of a bandwidth parameter. We extend the framework to allow for a time varying risk premium through common systematic factors. We show the limiting behaviour of the statistic under a multivariate fads model and under a moderately explosive bubble process: these alternative hypotheses give opposite predictions with regards to the long run value of the statistics. We apply the methodology to five weekly size-sorted CRSP portfolio returns from 1962 to 2013 in three subperiods. We find evidence of a reduction of linear predictability in the most recent period, for small and medium cap stocks. The main findings are not substantially affected by allowing for a common factor time varying risk premium.
Distribution, Abundance and Roosts of the Fruit Bat Artibeus fraterculus (Chiroptera: Phyllostomidae)

Where does a species live? How common is it? Where does it spend its inactive periods? These are basic questions about the biology of a species, which bring key information for application in conservation and management. Unfortunately, this information is available for only a minimum fraction of all animal species. Using 1) ecological niche modeling with maximum entropy (Maxent), 2) relative abundance estimates using museum records, and 3) field surveys of roosting sites, we report the fraternal fruit-eating bat, Artibeus fraterculus, as having a distribution limited to the Tumbesian ecoregion in Ecuador and west central Peru, being the relatively most abundant bat species throughout its range, with healthy populations which are primarily sustained by cultivated and introduced plants, and using human-made constructions as roost sites. Additionally, we described a large congregation of individuals of this species in a single roost, representing the largest colony reported for the genus Artibeus. These results may indicate resilience of A. fraterculus to human disturbance.
In search of optimal data selection for training of automatic speech recognition systems

This paper presents an extended study in the topic of optimal selection of speech data from a database for efficient training of ASR systems. We reconsider a method of optimal selection introduced in our previous work and introduce variosearch as an alternative selection method developed in order to find a representative sample of speech data with a simultaneous control of acoustical and statistical parameters of data selected. Next, we present experiments in which the performance of a standard ASR system trained with data sets selected from a Dutch digits database via different selection methods was compared. The results show that the length of training utterances has a dominant impact on the recognition performance. Therefore, the length of the utterances is a factor that must be taken into account when interpreting phoneme recognition scores.
Bacteria Regulate Intestinal Epithelial Cell Differentiation Factors Both In Vitro and In Vivo

Background The human colon harbours a plethora of bacteria known to broadly impact on mucosal metabolism and function and thought to be involved in inflammatory bowel disease pathogenesis and colon cancer development. In this report, we investigated the effect of colonic bacteria on epithelial cell differentiation factors in vitro and in vivo. As key transcription factors we focused on Hes1, known to direct towards an absorptive cell fate, Hath1 and KLF4, which govern goblet cell. Methods Expression of the transcription factors Hes1, Hath1 and KLF4, the mucins Muc1 and Muc2 and the defensin HBD2 were measured by real-time PCR in LS174T cells following incubation with several heat-inactivated E. coli strains, including the probiotic E. coli Nissle 1917+/− flagellin, Lactobacilli and Bifidobacteria. For protein detection Western blot experiments and chamber-slide immunostaining were performed. Finally, mRNA and protein expression of these factors was evaluated in the colon of germfree vs. specific pathogen free vs. conventionalized mice and colonic goblet cells were counted. Results Expression of Hes1 and Hath1, and to a minor degree also of KLF4, was reduced by E. coli K-12 and E. coli Nissle 1917. In contrast, Muc1 and HBD2 expression were significantly enhanced, independent of the Notch signalling pathway. Probiotic E. coli Nissle 1917 regulated Hes1, Hath1, Muc1 and HBD2 through flagellin. In vivo experiments confirmed the observed in vitro effects of bacteria by a diminished colonic expression of Hath1 and KLF4 in specific pathogen free and conventionalized mice as compared to germ free mice whereas the number of goblet cells was unchanged in these mice. Conclusions Intestinal bacteria influence the intestinal epithelial differentiation factors Hes1, Hath1 and KLF4, as well as Muc1 and HBD2, in vitro and in vivo. The induction of Muc1 and HBD2 seems to be triggered directly by bacteria and not by Notch.
Revealing skull identity through a fusion of Viola-Jones and CCA

Face detection using skull has been referred as the most complex and challenging task in the domain of computer vision, by the large intra-class variations occurred due to the changes in facial perspectives, expression and illumination. Distinct approaches have paid attention on this skill, still only open source implementations have been greatly exercised by researchers. The best example is the Viola-Jones Object Detection framework that especially in the case of facial processing has been recurrently used which imparts real-time contentious object detection rates. The important stages stated in this research work is to first eradicate the detected feature parts from face which will be correlated through Canonical Correlation Analysis(CCA) against the feature extracted from the skull. The Canonical correlation analysis is largely concerned with the estimation of a linear composition of each of two pairs of variables suchlike the correlation present between two functions should be maximized. Hence the combination of Viola-Jones with CCA will definitely boost up the matching accuracy as well as ease the task eradication and correlation.
Towards a Unified Approach for Opinion Question Answering and Summarization

The aim of this paper is to present an approach to tackle the task of opinion question answering and text summarization. Following the guidelines TAC 2008 Opinion Summarization Pilot task, we propose new methods for each of the major components of the process. In particular, for the information retrieval, opinion mining and summarization stages. The performance obtained improves with respect to the state of the art by approximately 12.50%, thus concluding that the suggested approaches for these three components are adequate.
Bayesian propensity score analysis for observational data

In the analysis of observational data, stratifying patients on the estimated propensity scores reduces confounding from measured variables. Confidence intervals for the treatment effect are typically calculated without acknowledging uncertainty in the estimated propensity scores, and intuitively this may yield inferences, which are falsely precise. In this paper, we describe a Bayesian method that models the propensity score as a latent variable. We consider observational studies with a dichotomous treatment, dichotomous outcome, and measured confounders where the log odds ratio is the measure of effect. Markov chain Monte Carlo is used for posterior simulation. We study the impact of modelling uncertainty in the propensity scores in a case study investigating the effect of statin therapy on mortality in Ontario patients discharged from hospital following acute myocardial infarction. Our analysis reveals that the Bayesian credible interval for the treatment effect is 10 per cent wider compared with a conventional propensity score analysis. Using simulations, we show that when the association between treatment and confounders is weak, then this increases uncertainty in the estimated propensity scores. Bayesian interval estimates for the treatment effect are longer on average, though there is little improvement in coverage probability. A novel feature of the proposed method is that it fits models for the treatment and outcome simultaneously rather than one at a time. The method uses the outcome variable to inform the fit of the propensity model. We explore the performance of the estimated propensity scores using cross‐validation. Copyright © 2008 John Wiley & Sons, Ltd.
Microevolution of Virulence-Related Genes in Helicobacter pylori Familial Infection

Helicobacter pylori, a bacterial pathogen that can infect human stomach causing gastritis, ulcers and cancer, is known to have a high degree of genome/epigenome diversity as the result of mutation and recombination. The bacteria often infect in childhood and persist for the life of the host. One of the reasons of the rapid evolution of H. pylori is that it changes its genome drastically for adaptation to a new host. To investigate microevolution and adaptation of the H. pylori genome, we undertook whole genome sequencing of the same or very similar sequence type in multi-locus sequence typing (MLST) with seven genes in members of the same family consisting of parents and children in Japan. Detection of nucleotide substitutions revealed likely transmission pathways involving children. Nonsynonymous (amino acid changing) mutations were found in virulence-related genes (cag genes, vacA, hcpDX, tnfα, ggt, htrA and the collagenase gene), outer membrane protein (OMP) genes and other cell surface-related protein genes, signal transduction genes and restriction-modification genes. We reconstructed various pathways by which H. pylori can adapt to a new human host, and our results raised the possibility that the mutational changes in virulence-related genes have a role in adaptation to a child host. Changes in restriction-modification genes might remodel the methylome and transcriptome to help adaptation. This study has provided insights into H. pylori transmission and virulence and has implications for basic research as well as clinical practice.
Polar Subcodes

An extension of polar codes is proposed, which allows some of the frozen symbols, called dynamic frozen symbols, to be data-dependent. A construction of polar codes with dynamic frozen symbols, being subcodes of extended BCH codes, is proposed. The proposed codes have higher minimum distance than classical polar codes, but still can be efficiently decoded using the successive cancellation algorithm and its extensions. The codes with Arikan, extended BCH and Reed-Solomon kernel are considered. The proposed codes are shown to outperform LDPC and turbo codes, as well as polar codes with CRC.
SWAG: Semantic web application generator - a library for using ontologies as web services

This paper addresses the problem of integrating ontological knowledge bases into complex software applications by proposing a library for exposing ontology access and manipulation as web services. The proposed framework is an extension of our previous work, the M2O framework, and enhances it by integrating reasoning techniques and generating a web services layer for performing basic CRUD operations and inferred information retrieval over ontologies. The ontology access is provided by 3rd party APIs, such as Jena API for simple ontology access or D2RQ, in case of using ontologies mapped to relational databases for storing individuals. An object oriented layer is generated to intermediate the flow of information between the data sources and web services. The ontology, the reasoning rules and the database may be generated at runtime by using Java reflection techniques. The framework is used with the Diagnostic ontology to perform a set of experiments that illustrate the benefits of the proposed solution, such as code complexity reduction and reasoning capabilities.