Miracle-dz/UniFAR-FTUs huggingface dataset:
Adaptive Decomposition Of Time

In this paper we introduce design principles for unsupervised detection of regularities (like causal relationships) in temporal sequences. One basic idea is to train an adaptive predictor module to predict future events from past events, and to train an additional condence module to model the reliability of the predictor's predictions. We select system states at those points in time where there are changes in prediction reliability, and use them recur-sively as inputs for higher-level predictors. This can be benecial foràdaptive sub-goal generation' as well as for`conventional' goal-directed (supervised and reinforcement) learning: Systems based on these design principles were successfully tested on tasks where conventional training algorithms for recurrent nets fail. Finally we describe the principles of the rst neural sequencèchunker' which collapses a self-organizing multi-level predictor hierarchy into a single recurrent network. This paper is based on thèprinciple of reduced history description': As long as an adaptive sequence processing dynamic system is able to predict future environmental inputs from previous ones, no additional knowledge can be obtained by observing these inputs in reality. Only unpredicted inputs deserve attention ([7][4][9]). This paper demonstrates that it can be very ecient to focus on unexpected inputs and ignore expected ones. First we motivate this work by describing a major problem of`conventional' learning algorithms for time-varying inputs, namely, the problem of long time lags between relevant inputs. Then we introduce a principle for unsupervised detection of causal chains in streams of input events. Short representations of`presumed causal chains' recursively serve as inputs for`higher-level' detec
Roadmap for cardiovascular circulation model

Computational models of many aspects of the mammalian cardiovascular circulation have been developed. Indeed, along with orthopaedics, this area of physiology is one that has attracted much interest from engineers, presumably because the equations governing blood flow in the vascular system are well understood and can be solved with well‐established numerical techniques. Unfortunately, there have been only a few attempts to create a comprehensive public domain resource for cardiovascular researchers. In this paper we propose a roadmap for developing an open source cardiovascular circulation model. The model should be registered to the musculo‐skeletal system. The computational infrastructure for the cardiovascular model should provide for near real‐time computation of blood flow and pressure in all parts of the body. The model should deal with vascular beds in all tissues, and the computational infrastructure for the model should provide links into CellML models of cell function and tissue function. In this work we review the literature associated with 1D blood flow modelling in the cardiovascular system, discuss model encoding standards, software and a model repository. We then describe the coordinate systems used to define the vascular geometry, derive the equations and discuss the implementation of these coupled equations in the open source computational software OpenCMISS. Finally, some preliminary results are presented and plans outlined for the next steps in the development of the model, the computational software and the graphical user interface for accessing the model.
Production , Manufacturing and Logistics The value of real time yield information in multi-stage inventory systems – Exact and heuristic approaches

We consider a random yield inventory system, where a company has access to real time information about the actual yield realizations. To contribute to a better understanding of the value of this information, we develop a mathematical model of the inventory system and derive structural properties. We build on these properties to develop an optimal solution approach that can be used to solve small to medium sized problems. To solve large problems, we develop two heuristics. We conduct numerical experiments to test the performances of our approaches and to identify conditions under which real time yield information is particularly beneficial. Our research provides the approaches that are necessary to implement inventory control policies that utilize real time yield information. The results can also be used to estimate the cost savings that can be achieved by using real time yield information. The cost savings can then be compared against the required investments to decide if such an investment is profitable. 2014 Elsevier B.V. All rights reserved.
Poly (lactic acid)/Spartium junceum fibers biocomposites: effects of the fibers content and surface treatments on the microstructure and thermomechanical properties

ABSTRACT The aim of this work was to study the effects of alkali and alkali-silane surface treatments on Spartium junceum (Sj) fibers characteristics. Then, untreated and surface treated fibers were incorporated into a poly(lactic acid) matrix and the properties of the composites were studied. To improve the adhesion at the interface between the PLA matrix and alkali-silane treated fibers, maleic anhydride-grafted poly (lactic acid) (PLA-g-MA) was added as a compatibilizer. FTIR and TGA analysis proved the efficiency of the alkali treatment in removing some non-cellulosic components, namely hemicelluloses and lignin. Also, XRD results showed that the applied chemical treatments contribute to the increase in the crystallinity index of the Sj fibers. The incorporation of Sj fibers was found to decrease notably the impact strength of PLA and to affect its thermal behavior by increasing the melting temperature of the composites. However, it has been observed that the treatments increased notably the composites impact properties. These results have been confirmed by scanning electron microscopy (SEM) observations of the composites fractured surfaces which revealed a more intimate contact between the Sj fibers and the PLA matrix after surface modification. Also, the PLA-g-MA acted positively on the adhesion in the interfacial region. Graphical Abstract
Evaluating Convolutional Neural Network and Hidden Markov Model for Recognising Surgical Phases in Sigmoid Resection

Abstract Surgical workflow analysis in laparoscopic surgeries has been studied widely during last years because of its various applications. For example, optimising the schedule of operating rooms (OR) and developing a context-aware system that supports surgical team during the intervention. Surgical phase recognition has been applied to various kinds of laparoscopic procedures, mainly of type cholecystectomy. Sigmoid resection procedures are considered more complex than cholecystectomy, and they have not been extensively studied. Therefore, the focus of this work is to study phase recognition in sigmoid resection. In this paper, a convolutional neural network (CNN) architecture and Hidden Markov Model (HMM) were evaluated for performing phase recognition in sigmoid resection videos. The CNN is an extension of a pretrained model, and it was fine-tuned to perform the recognition. To consider the temporal aspect of the phase sequences, confidences obtained by the CNN were then provided into a HMM to release final classification. Experimental results show a low performance of the proposed method to recognise surgical phases in such complex procedures. Therefore, the dataset used for the evaluation was also reviewed, and statistics of each phase were generated.
De novo ACTA2 mutation causes a novel syndrome of multisystemic smooth muscle dysfunction

Smooth muscle cells (SMCs) contract to perform many physiological functions, including regulation of blood flow and pressure in arteries, contraction of the pupils, peristalsis of the gut, and voiding of the bladder. SMC lineage in these organs is characterized by cellular expression of the SMC isoform of α‐actin, encoded by the ACTA2 gene. We report here on a unique and de novo mutation in ACTA2, R179H, that causes a syndrome characterized by dysfunction of SMCs throughout the body, leading to aortic and cerebrovascular disease, fixed dilated pupils, hypotonic bladder, malrotation, and hypoperistalsis of the gut and pulmonary hypertension. © 2010 Wiley‐Liss, Inc.
Frequency of the cholesteryl ester storage disease common LIPA E8SJM mutation (c.894G>A) in various racial and ethnic groups

Cholesteryl ester storage disease (CESD) and Wolman disease are autosomal recessive later‐onset and severe infantile disorders, respectively, which result from the deficient activity of lysosomal acid lipase (LAL). LAL is encoded by LIPA (10q23.31) and the most common mutation associated with CESD is an exon 8 splice junction mutation (c.894G>A; E8SJM), which expresses only ∼3%‐5% of normally spliced LAL. However, the frequency of c.894G>A is unknown in most populations. To estimate the prevalence of CESD in different populations, the frequencies of the c.894G>A mutation were determined in 10,000 LIPA alleles from healthy African‐American, Asian, Caucasian, Hispanic, and Ashkenazi Jewish individuals from the greater New York metropolitan area and 6,578 LIPA alleles from African‐American, Caucasian, and Hispanic subjects enrolled in the Dallas Heart Study. The combined c.894G>A allele frequencies from the two cohorts ranged from 0.0005 (Asian) to 0.0017 (Caucasian and Hispanic), which translated to carrier frequencies of 1 in 1,000 to ∼1 in 300, respectively. No African‐American heterozygotes were detected. Additionally, by surveying the available literature, c.894G>A was estimated to account for 60% (95% confidence interval [CI]: 51%‐69%) of reported mutations among multiethnic CESD patients. Using this estimate, the predicted prevalence of CESD in the Caucasian and Hispanic populations is ∼0.8 per 100,000 (∼1 in 130,000; 95% CI: ∼1 in 90,000 to 1 in 170,000). Conclusion: These data indicate that CESD may be underdiagnosed in the general Caucasian and Hispanic populations, which is important since clinical trials of enzyme replacement therapy for LAL deficiency are currently being developed. Moreover, future studies on CESD prevalence in African and Asian populations may require full‐gene LIPA sequencing to determine heterozygote frequencies, since c.894G>A is not common in these racial groups. (HEPATOLOGY 2013;53:958–965)
Recommendations from the INHAND Apoptosis/Necrosis Working Group

Historically, there has been confusion relating to the diagnostic nomenclature for individual cell death. Toxicologic pathologists have generally used the terms “single cell necrosis” and “apoptosis” interchangeably. Increased research on the mechanisms of cell death in recent years has led to the understanding that apoptosis and necrosis involve different cellular pathways and that these differences can have important implications when considering overall mechanisms of toxicity, and, for these reasons, the separate terms of apoptosis and necrosis should be used whenever differentiation is possible. However, it is also recognized that differentiation of the precise pathway of cell death may not be important, necessary, or possible in routine toxicity studies and so a more general term to indicate cell death is warranted in these situations. Morphological distinction between these two forms of cell death can sometimes be straightforward but can also be challenging. This article provides a brief discussion of the cellular mechanisms and morphological features of apoptosis and necrosis as well as guidance on when the pathologist should use these terms. It provides recommended nomenclature along with diagnostic criteria (in hematoxylin and eosin [H&E]-stained sections) for the most common forms of cell death (apoptosis and necrosis). This document is intended to serve as current guidance for the nomenclature of cell death for the International Harmonization of Nomenclature and Diagnostic Criteria Organ Working Groups and the toxicologic pathology community at large. The specific recommendations are: Use necrosis and apoptosis as separate diagnostic terms. Use modifiers to denote the distribution of necrosis (e.g., necrosis, single cell; necrosis, focal; necrosis, diffuse; etc.). Use the combined term apoptosis/single cell necrosis when There is no requirement or need to split the processes, or When the nature of cell death cannot be determined with certainty, or When both processes are present together. The diagnosis should be based primarily on the morphological features in H&E-stained sections. When needed, additional, special techniques to identify and characterize apoptosis can also be used.
Genetic local search for multicast routing

We describe a population-based search algorithm for cost minimization of multicast routing. The algorithm utilizes the partially mixed crossover operation (PMX) and a landscape analysis in a pre-processing step. The aim of the landscape analysis is to estimate the depth Γ of the deepest local minima in the landscape generated by the routing tasks and the objective function. The analysis employs simulated annealing with a logarithmic cooling schedule (LSA). The local search performs alternating sequences of descending and ascending steps for each individual of the population, where the length of a sequence with uniform direction is controlled by the estimated value of Γ. We present results from computational experiments on a synthetic routing tasks, and we provide experimental evidence that our genetic local search procedure, that combines LSA and PMX, performs better than algorithms using either LSA or PMX only.
Build a Chinese Treebank as the test suite for Chinese parser

This paper will introduce our current work to build a Chinese treebank that can be used as a test suite for Chinese parser. The treebank will consist of 10,000 Chinese sentences extracted from a Chinese balanced corpus with about 2,000,000 Chinese characters. The corpus has already been annotated with correct segmentation and Part-Of-Speech(POS) information. The following issues will be discussed in the paper : the survey of the balanced corpus, the strategies and methods for sampling the treebank sentences, the processing schemes and tools for treebank construction.
SeXX Matters in Infectious Disease Pathogenesis

We often use the terms “sex” and “gender” interchangeably in infectious diseases research, which is incorrect because these terms refer to different aspects of biology and behavior. The term “sex” refers to biological characteristics that define males and females, including the basic organization of chromosomes, reproductive organs, and circulating sex steroid hormone concentrations. Gender refers to the roles, behaviors, and activities that are defined by social or cultural norms, including gender norms associated with education, occupation, and healthseeking behaviors [1]. If we consider infectious diseases in the context of sex and gender, then we could hypothesize that sex results in physiological differences (e.g., hormonal regulation of immune responses) that contribute to male–female differences in the control and clearance of a pathogen as well as anatomical differences that may affect exposure and transmission of a pathogen. Gender is likely associated with behaviors that influence differential exposure to pathogens. Gender also contributes to the norms that affect access to health care and health-seeking behaviors, which could influence male–female differences in the duration and severity of infection in some countries [1]. By and large, both the intensity (i.e., pathogen load within an individual) and prevalence (i.e., number of infected individuals within a population) of infections are often higher for males than females, illustrating that both sex and gender play roles in male–female differences in infectious disease pathogenesis.
Estimating the effective number of breeders from heterozygote excess in progeny.

The heterozygote-excess method is a recently published method for estimating the effective population size (Ne). It is based on the following principle: When the effective number of breeders (Neb) in a population is small, the allele frequencies will (by chance) be different in males and females, which causes an excess of heterozygotes in the progeny with respect to Hardy-Weinberg equilibrium expectations. We evaluate the accuracy and precision of the heterozygote-excess method using empirical and simulated data sets from polygamous, polygynous, and monogamous mating systems and by using realistic sample sizes of individuals (15-120) and loci (5-30) with varying levels of polymorphism. The method gave nearly unbiased estimates of Neb under all three mating systems. However, the confidence intervals on the point estimates of Neb were sufficiently small (and hence the heterozygote-excess method useful) only in polygamous and polygynous populations that were produced by <10 effective breeders, unless samples included > approximately 60 individuals and 20 multiallelic loci.
Interrater reliability: the kappa statistic

The kappa statistic is frequently used to test interrater reliability. The importance of rater reliability lies in the fact that it represents the extent to which the data collected in the study are correct representations of the variables measured. Measurement of the extent to which data collectors (raters) assign the same score to the same variable is called interrater reliability. While there have been a variety of methods to measure interrater reliability, traditionally it was measured as percent agreement, calculated as the number of agreement scores divided by the total number of scores. In 1960, Jacob Cohen critiqued use of percent agreement due to its inability to account for chance agreement. He introduced the Cohen’s kappa, developed to account for the possibility that raters actually guess on at least some variables due to uncertainty. Like most correlation statistics, the kappa can range from −1 to +1. While the kappa is one of the most commonly used statistics to test interrater reliability, it has limitations. Judgments about what level of kappa should be acceptable for health research are questioned. Cohen’s suggested interpretation may be too lenient for health related studies because it implies that a score as low as 0.41 might be acceptable. Kappa and percent agreement are compared, and levels for both kappa and percent agreement that should be demanded in healthcare studies are suggested.
Mildly Non-Projective Dependency Structures

Syntactic parsing requires a fine balance between expressivity and complexity, so that naturally occurring structures can be accurately parsed without compromising efficiency. In dependency-based parsing, several constraints have been proposed that restrict the class of permissible structures, such as projectivity, planarity, multi-planarity, well-nestedness, gap degree, and edge degree. While projectivity is generally taken to be too restrictive for natural language syntax, it is not clear which of the other proposals strikes the best balance between expressivity and complexity. In this paper, we review and compare the different constraints theoretically, and provide an experimental evaluation using data from two treebanks, investigating how large a proportion of the structures found in the treebanks are permitted under different constraints. The results indicate that a combination of the well-nestedness constraint and a parametric constraint on discontinuity gives a very good fit with the linguistic data.
The application of information fusion in the real-time monitoring system

This paper studies the feasibility of information analysis processing technology, which fuses speech and image together in the real-time monitoring system. It emphasizes particularly on speech analysis and fuses these two technologies in terms of scoring strategy. It also makes some improvement on MFCC feature extraction and proposes a quick MFCC algorithm. The proposed algorithm can reach the requirement of real-time system in case of the high precision. To prove it, this paper compares its algorithm with LPC and FFT. The experiment indicates that the EER of LPC is 13.9% and the EER of FFT is 11.1%, but by using the Quick MFCC the EER is only 4.2%. And compared with the traditional MFCC algorithm, the quick MFCC algorithm reduces the run time greatly while maintaining recognition accuracy of the system. Finally the rate of fusion recognition is about 97.8%, which is a good result for the real-time monitoring system.
Design considerations for ease of access and maneuverability of OCT imaging platforms in the oral cavity

With the advent of instruments incorporating elements of confocal microscopy and Optical Coherence Tomography (OCT), optical technologies are steadily gaining usage in a variety of biomedical applications. They offer tissue visualization both at the superficial level and in depth, they operate using non-ionizing radiation at a relatively low cost, and the procedures are easily tolerated by patients. One area of growth for optical imaging is in the oral cavity, which has excellent optical accessibility both for dental tissue and oral mucosa. The need to image features accurately (both as part of oral mapping and as part of investigating the underlying tooth structure) requires producing 3-D volumes with sufficiently good lateral and vertical resolution to allow identification of features of interest. Although a few types of intraoral optical scanners are already successfully commercialized for surface mapping, the examination of optical design considerations that are particular to scanned beam imaging in the oral cavity does highlight particular challenges of interest to both clinicians and optical engineers engaged in designing the next generation of optical instruments.
Tree Kernel Engineering in Semantic Role Labeling Systems

Recent work on the design of automatic systems for semantic role labeling has shown that feature engineering is a complex task from a modeling and implementation point of view. Tree kernels alleviate such complexity as kernel functions generate features automatically and require less software development for data extraction. In this paper, we study several tree kernel approaches for both boundary detection and argument classification. The comparative experiments on Support Vector Machines with such kernels on the CoNLL 2005 dataset show that very simple tree manipulations trigger automatic feature engineering that highly improves accuracy and efficiency in both phases. Moreover, the use of different classifiers for internal and pre-terminal nodes maintains the same accuracy and highly improves efficiency.