Miracle-dz/UniFAR-FTUs huggingface dataset:
Fuzzy - Rough Feature Selection With Π- Membership Function For Mammogram Classification

Breast cancer is the second leading cause for death among women and it is diagnosed with the help of mammograms. Oncologists are miserably failed in identifying the micro calcification at the early stage with the help of the mammogram visually. In order to improve the performance of the breast cancer screening, most of the researchers have proposed Computer Aided Diagnosis using image processing. In this study mammograms are preprocessed and features are extracted, then the abnormality is identified through the classification. If all the extracted features are used, most of the cases are misidentified. Hence feature selection procedure is sought. In this paper, FuzzyRough feature selection with π membership function is proposed. The selected features are used to classify the abnormalities with help of Ant-Miner and Weka tools. The experimental analysis shows that the proposed method improves the mammograms classification accuracy.
A Non-Parametric Based Mapping Algorithm for Use in Audio Fingerprinting

Over the past few years, the online multimedia collection has grown at a fast pace. Several companies showed interest to study the different ways to organise the amount of audio information without the need of human intervention to generate metadata. In the past few years, many applications have emerged on the market which are capable of identifying a piece of music in a short time. Different audio effects and degradation make it much harder to identify the unknown piece. In this paper, an audio fingerprinting system which makes use of a non-parametric based algorithm is presented. Parametric analysis is also performed using Gaussian Mixture Models (GMMs). The feature extraction methods employed are the Mel Spectrum Coefficients and the MPEG-7 basic descriptors. Bin numbers replaced the extracted feature coefficients during the non-parametric modelling. The results show that nonparametric analysis offer potential results as the ones mentioned in the literature. Keywords—Audio fingerprinting, mapping algorithm, Gaussian Mixture Models, MFCC, MPEG-7.
Edinburgh Research Explorer Divergence of Mammalian Higher Order Chromatin Structure Is Associated with Developmental Loci

Several recent studies have examined different aspects of mammalian higher order chromatin structure – replication timing, lamina association and Hi-C inter-locus interactions — and have suggested that most of these features of genome organisation are conserved over evolution. However, the extent of evolutionary divergence in higher order structure has not been rigorously measured across the mammalian genome, and until now little has been known about the characteristics of any divergent loci present. Here, we generate a dataset combining multiple measurements of chromatin structure and organisation over many embryonic cell types for both human and mouse that, for the first time, allows a comprehensive assessment of the extent of structural divergence between mammalian genomes. Comparison of orthologous regions confirms that all measurable facets of higher order structure are conserved between human and mouse, across the vast majority of the detectably orthologous genome. This broad similarity is observed in spite of many loci possessing cell type specific structures. However, we also identify hundreds of regions (from 100 Kb to 2.7 Mb in size) showing consistent evidence of divergence between these species, constituting at least 10% of the orthologous mammalian genome and encompassing many hundreds of human and mouse genes. These regions show unusual shifts in human GC content, are unevenly distributed across both genomes, and are enriched in human subtelomeric regions. Divergent regions are also relatively enriched for genes showing divergent expression patterns between human and mouse ES cells, implying these regions cause divergent regulation. Particular divergent loci are strikingly enriched in genes implicated in vertebrate development, suggesting important roles for structural divergence in the evolution of mammalian developmental programmes. These data suggest that, though relatively rare in the mammalian genome, divergence in higher order chromatin structure has played important roles during evolution.
Head-to-Head Comparison between Collagen Proportionate Area and Acoustic Radiation Force Impulse Elastography in Liver Fibrosis Quantification in Chronic Hepatitis C

Background The aim of this study was to compare the diagnostic performances of the collagen proportionate area (CPA) and liver stiffness measurement (LSM) for liver fibrosis quantification in chronic hepatitis C (CHC). Methods A total of 137 eligible consecutive Taiwanese patients (74 women and 63 men; age 21–80 years; median age 54 years), with CHC underwent LSM by using acoustic radiation force impulse (ARFI) elastography and an immediate percutaneous liver biopsy for METAVIR scoring. Liver tissue sections were stained using picrosirius red. Areas of the stained collagen and the tissue parenchyma were calculated in pixels. The ratio between the two areas was expressed as a CPA percentage. The result of LSM was presented as shear wave velocity (SWV). Results METAVIR fibrosis (F) stages were dichotomized using the CPA (%) and SWV (m/s), and the optimal cut-off values were 7.47 and 1.59 for F1 versus F2–4; 12.56 and 1.73 for F1, 2 versus F3, 4; 15.32 and 1.96 for F1–3 versus F4. To dichotomize F1 versus F2–4, the areas under receiver operating characteristic curves for the CPA was 0.9349 (95% confidence interval: 0.8943–0.9755) and for SWV was 0.8434 (0.7762–0.9105) (CPA versus SWV, P = 0.0063). For F1, 2 versus F3, 4, the CPA was 0.9436 (0.9091–0.9781); SWV was 0.8997 (0.8444–0.9551) (P = 0.1587). For F1–3 versus F4, the CPA was 0.8647 (0.7944–0.9349); SWV was 0.9036 (0.8499–0.9573) (P = 0.2585). The CPA could be predicted in a linear regression formula by using SWV and platelet count (R2 = 0.524). Conclusions The CPA and ARFI elastography are promising tools for liver fibrosis evaluation. The CPA was superior to ARFI elastography in the diagnosis of significant fibrosis (≥ F2). The CPA may be independent of severe necroinflammation, which may augment liver stiffness.
Enforcing balance allows local supervised learning in spiking recurrent networks

To predict sensory inputs or control motor trajectories, the brain must constantly learn temporal dynamics based on error feedback. However, it remains unclear how such supervised learning is implemented in biological neural networks. Learning in recurrent spiking networks is notoriously difficult because local changes in connectivity may have an unpredictable effect on the global dynamics. The most commonly used learning rules, such as temporal back-propagation, are not local and thus not biologically plausible. Furthermore, reproducing the Poisson-like statistics of neural responses requires the use of networks with balanced excitation and inhibition. Such balance is easily destroyed during learning. Using a top-down approach, we show how networks of integrate-and-fire neurons can learn arbitrary linear dynamical systems by feeding back their error as a feed-forward input. The network uses two types of recurrent connections: fast and slow. The fast connections learn to balance excitation and inhibition using a voltage-based plasticity rule. The slow connections are trained to minimize the error feedback using a current-based Hebbian learning rule. Importantly, the balance maintained by fast connections is crucial to ensure that global error signals are available locally in each neuron, in turn resulting in a local learning rule for the slow connections. This demonstrates that spiking networks can learn complex dynamics using purely local learning rules, using E/I balance as the key rather than an additional constraint. The resulting network implements a given function within the predictive coding scheme, with minimal dimensions and activity.
Regulation of Microtubule Dynamics by Protein: Interaction Networks at Microtubule Tips

textabstractMicrotubules are cytoskeletal fi laments, which play essenti al roles in cell division, morphology, migrati on and organizati on of intracellular organelles. Many of these functi ons are regulated by the associati on of microtubule plus ends with a group of structurally diverse and unrelated proteins - the microtubule plus-end tracking proteins (+TIPs). This thesis describes how +TIPs infl uence microtubule dynamics, how the assembly of interacti on networks from a large number of +TIPs at the relati vely small MT end is regulated both in space and ti me, and how this contributes to the cellular functi ons. In additi on, this thesis addresses the identi fi cati on and characterizati on of proteins that control local microtubule dynamics at the cell cortex. Chapter 1 introduces the key players in the fi eld of microtubule dynamic instability.
Behavioural phenotypes of hypomorphic KCC2‐deficient mice

Hyperpolarizing fast inhibitory neurotransmission by γ‐aminobutyric acid and glycine requires an efficient chloride extrusion mechanism in postsynaptic neurons. A major effector of this task in adult animals is the potassium‐chloride co‐transporter KCC2 that is selectively and abundantly expressed postsynaptically in most CNS neurons. Yet, the role of KCC2 in adult brain at the systems level is poorly known. Here, we characterize the behaviour of mice doubly heterozygous for KCC2 null and hypomorphic alleles that retain 15–20% of normal KCC2 protein levels in the brain. These hypomorphic KCC2‐deficient mice were viable and fertile but weighed 15–20% less than wild‐type littermates at 2 weeks old and thereafter. The mice displayed increased anxiety‐like behaviour in several tests including elevated plus‐maze and were more susceptible to pentylenetetrazole‐induced seizures. Moreover, the mice were impaired in water maze learning and showed reduced sensitivity to tactile and noxious thermal stimuli in von Frey hairs, hot plate and tail flick tests. In contrast, the mice showed normal spontaneous locomotor activity in open field and Y‐maze tests, and intact motor coordination in rotarod and beam tests. The results suggest that requirements for KCC2‐dependent fast hyperpolarizing inhibition may differ among various functional systems of the CNS. As shunting inhibition is expected to be intact in KCC2‐deficient neurons, these mice may provide a useful tool to study the specific functions and relative importance of hyperpolarizing fast synaptic inhibition in adult CNS that may have implications for human neuropsychiatric disorders, such as epilepsy, pain and anxiety.
Metal Artefact Reduction by Least-Squares Penalized-Likelihood Reconstruction with a Fast Polychromatic Projection Model

We consider penalized-likelihood reconstruction for X-ray computed tomography of objects that contain small metal structures. To reduce the beam hardening artefacts induced by these structures, we derive the reconstruction algorithm from a projection model that takes into account the photon emission spectrum and nonlinear variation of attenuation to photon energy. This algorithm requires excessively long runtimes to attain convergence. We contribute refinements in the representation of the object and the modelling of the photon emission spectrum aimed at reducing the runtime. These refinements yield an algorithm for which the reconstruction runtime is reduced by at least one order of magnitude on each considered dataset. For real data that were preprocessed for metal artefact reduction, the enhanced polychromatic algorithm provides the best observed image quality for objects with large metal structures. For objects with small metal structures, the gains are less significant with respect to a penalized-likelihood algorithm derived from a monochromatic projection model. PACS numbers: 87.57cp,87.57nf,87.57nt,87.57QSubmitted to: Phys. Med. Biol. Metal Artefact Reduction . with a Fast Polychromatic Projection Model 2
Optimistic Recovery for Iterative Dataflows in Action

Over the past years, parallel dataflow systems have been employed for advanced analytics in the field of data mining where many algorithms are iterative. These systems typically provide fault tolerance by periodically checkpointing the algorithm's state and, in case of failure, restoring a consistent state from a checkpoint. In prior work, we presented an optimistic recovery mechanism that in certain cases eliminates the need to checkpoint the intermediate state of an iterative algorithm. In case of failure, our mechanism uses a compensation function to transit the algorithm to a consistent state, from which the execution can continue and successfully converge. Since this recovery mechanism does not checkpoint any state, it achieves optimal failure-free performance while guaranteeing fault tolerance. In this paper, we demonstrate our recovery mechanism with the Apache Flink data processing engine. During our demonstration, attendees will be able to run graph algorithms and trigger failures to observe the algorithms recovering with compensation functions instead of checkpoints.
GestureCam: a video communication system for sympathetic remote collaboration

An approach supporting spatial workspace collaboration via a video-mediated communication system is described. Based on experimental results, the following were determined to be the system requirements to support spatial workspace collaboration: independency of a field of view, predictability, confidence in transmission and sympathy toward the system. Additionally, a newly developed camera system, the GestureCam System, is introduced. A camera is mounted on an actuator with three degrees of freedom. It is controlled by master-slave method or by a touch-sensitive CRT. Also, a laser pointer is mounted to assist with remote pointing. Preliminary experiments were conducted and the results are described herein.
Insufﬁcient Knowledge and Resources — A Biological Constraint and Its Functional Implications

Insufﬁcient knowledge and resources is not only a biological constraint on human and animal intelligence, but also has important functional implications for ar-tiﬁcial intelligence (AI) systems. Traditional theories dominating AI research typically assume some kind of sufﬁciency of knowledge and resources, so cannot solve many problems in the ﬁeld. AI needs new theories obeying this constraint, which cannot be obtained by minor revisions or extensions of the traditional theories. The practice of NARS, an AI project, shows that such new theories are feasible and promising in providing a new theoretical foundation for AI.
Validation of qPCR Methods for the Detection of Mycobacterium in New World Animal Reservoirs

Zoonotic pathogens that cause leprosy (Mycobacterium leprae) and tuberculosis (Mycobacterium tuberculosis complex, MTBC) continue to impact modern human populations. Therefore, methods able to survey mycobacterial infection in potential animal hosts are necessary for proper evaluation of human exposure threats. Here we tested for mycobacterial-specific single- and multi-copy loci using qPCR. In a trial study in which armadillos were artificially infected with M. leprae, these techniques were specific and sensitive to pathogen detection, while more traditional ELISAs were only specific. These assays were then employed in a case study to detect M. leprae as well as MTBC in wild marmosets. All marmosets were negative for M. leprae DNA, but 14 were positive for the mycobacterial rpoB gene assay. Targeted capture and sequencing of rpoB and other MTBC genes validated the presence of mycobacterial DNA in these samples and revealed that qPCR is useful for identifying mycobacterial-infected animal hosts.
Do Electronic Health Records Help Undergraduate Health Informatics Students to Develop Health Informatics Competencies?

The purpose of this paper is to determine the effects of hands-on exposure to an educational electronic health record (EHR) system upon undergraduate health informatics (HI) student competency development. We undertook a quasi-experimental study (i.e. pre-test, post-test design), where students were given the opportunity to do hands-on work with an educational EHR over a 10 week period. HI student competencies were measured pre and post educational EHR exposure. Several HI student competencies improved significantly following hands-on work with the EHR. As well, students provided more higher quality case study answerfollowing EHR use.
Letters to the Editor Morphological Quantitation of Emphysema: A Debate The following series of letters to the editor concerns a recently published morphologic method proposed by Parameswaran and colleagues for sensitive, early detection of emphysema

The following series of letters to the editor concerns a recently published morphologic method proposed by Parameswaran and colleagues for sensitive, early detection of emphysema (J Appl Physiol 100: 186–193, 2006). The validity of the proposed method was critiqued by Ewald Weibel, and, in turn, this critique was rebutted by Parameswaran et al. Additional brief commentaries were contributed by scientists working in the field. Further comments on this important topic are welcome.
A real-time spatio-temporal stereo matching for road applications

This paper presents a real-time approach for matching stereo images acquired by a stereo sensor embedded in a moving vehicle. The new method consists of matching edge points extracted from stereo images using the temporal relationship, which exists between consecutive stereo pairs. Matching a current stereo pair takes into account the matching results of the preceding stereo pair. The method looks first for what we call matching control edge points (MCEPs) based on spatio-temporal matching of edge curves of consecutive stereo pairs. Dynamic programming is considered for matching edge points of the stereo images. The MCEPs drive the optimal path of the dynamic programming. The proposed approach has been tested on virtual and real stereo image sequences and the results are satisfactory.
Research on Role-Based Joint Authorization Administration Model

In order to avoid the abuse of administrative permission in authorization process, the paper proposes a joint administration model. In the model, the concept of joint administrative role is proposed. A joint administrative role is comprised of several administrative roles who are assigned different weights, and regular roles are associated with different thresholds. Using the method, administrative roles can jointly assign the regular role to a user when the sum of weight exceeds the threshold. By setting the weight of administrative role and the threshold of regular role flexibly, the model can meet the requirement of diverse administrative scale and security hierarchies, and make the authorization decision more reasonable, improving the security of role assignment effectively.
Tetracycline Regulated Systems in Functional Oncogenomics

The increasing number of proteomic and DNA-microarray studies is continually providing a steady acquisition of data on the molecular abnormalities associated with human tumors. Rapid translation of this accumulating biological information into better diagnostics and more effective cancer therapeutics in the clinic depends on the use of robust function-testing strategies. Such strategies should allow identification of molecular lesions that are essential for the maintenance of the transformed phenotype and enable validation of potential drug-targets. The tetracycline regulated gene expression/ suppression systems (Tet-systems) developed and optimized by bioengineers over recent years seem to be very well suited for the function-testing purposes in cancer research. We review the history and latest improvements in Tet-technology in the context of functional oncogenomics.
Methodological Issues in Genetic Association Studies of Inherited Thrombophilia: Original Report of Recent Practice

The aims of this article are to evaluate the methodological quality of genetic association studies on the inherited thrombophilia published during 2003 to 2005, to identify the most common mistakes made by authors of those studies, and to examine if overall quality of the article correlates with the quality of the journal. Articles were evaluated by 2 independent reviewers using the checklist of 16 items. A total of 58 eligible studies were identified. Average total score was 7.59 ± 1.96. Total article score did not correlate with the journal impact factor (r = 0.3971; 95% confidence interval [CI], 0.1547-0.5944, P = .002). Total score did not differ across years (P = .624). Finally, it is concluded that methodological quality of genetic association studies is not optimal, and it does not depend on the quality of the journal. Journals should adopt methodological criteria for reporting the genetic association studies, and editors should encourage authors to strictly adhere to those criteria.
Balancing Systematic and Flexible Exploration of Social Networks

Social network analysis (SNA) has emerged as a powerful method for understanding the importance of relationships in networks. However, interactive exploration of networks is currently challenging because: (1) it is difficult to find patterns and comprehend the structure of networks with many nodes and links, and (2) current systems are often a medley of statistical methods and overwhelming visual output which leaves many analysts uncertain about how to explore in an orderly manner. This results in exploration that is largely opportunistic. Our contributions are techniques to help structural analysts understand social networks more effectively. We present SocialAction, a system that uses attribute ranking and coordinated views to help users systematically examine numerous SNA measures. Users can (1) flexibly iterate through visualizations of measures to gain an overview, filter nodes, and find outliers, (2) aggregate networks using link structure, find cohesive subgroups, and focus on communities of interest, and (3) untangle networks by viewing different link types separately, or find patterns across different link types using a matrix overview. For each operation, a stable node layout is maintained in the network visualization so users can make comparisons. SocialAction offers analysts a strategy beyond opportunism, as it provides systematic, yet flexible, techniques for exploring social networks