Miracle-dz/UniFAR-FTUs huggingface dataset:
Optimization of Structure of Fuzzy-neural Systems using Coevolutionary Algorithm

This paper is related to a research of modelling fuzzy-neural systems using the coevolutionary algorithm, and has the focus on advantages of using the coevolutionary algorithm for system structure optimization. In the context of this work, the term fuzzy-neural system defines the system that can be used as the fuzzy system with all its functionalities or as the neural network with all its functionalities. The hybridization of fuzzy logic, neural networks and coevolutionary algorithm and its architecture are presented in general, and the role of the coevolutionary algorithm in structure optimization is described in details. Results of testing with Iris Database, from UCI Machine Learning Repository are also presented. Tests performed during the research supports the conclusion that usage of the coevolutionary algorithm for the fuzzy-neural system’s structure optimization is very efficient.
It's More Complicated than Myth Busting: Parents Deciding About Stimulant Use for their Children.

R the Journal published a letter to the Editor titled “Stimulant use in attention deficit hyperactivity disorder (ADHD) kids – triumph or tribulation? ” (Naguy, 2016). Although I appreciated the author’s intent to summarize psychoeducational points with which to combat perceived myths that may serve as barriers to parents moving forward in considering stimulants for their child’s ADHD, I believe there are both technical and conceptual problems in the letter.
Multilingual Document Classification via Transductive Learning

We present a transductive learning based framework for multilingual document classification, originally proposed in [7]. A key aspect in our approach is the use of a large-scale multilingual knowledge base, BabelNet, to support the modeling of different language-written documents into a common conceptual space, without requiring any language translation process. Results on real-world multilingual corpora have highlighted the superiority of the proposed document model against existing language-dependent representation approaches, and the significance of the transductive setting for multilingual document classification.
A Search for H/ACA SnoRNAs in Yeast Using MFE Secondary Structure Prediction

MOTIVATION Noncoding RNA genes produce functional RNA molecules rather than coding for proteins. One such family is the H/ACA snoRNAs. Unlike the related C/D snoRNAs these have resisted automated detection to date. RESULTS We develop an algorithm to screen the yeast genome for novel H/ACA snoRNAs. To achieve this, we introduce some new methods for facilitating the search for noncoding RNAs in genomic sequences which are based on properties of predicted minimum free-energy (MFE) secondary structures. The algorithm has been implemented and can be generalized to enable screening of other eukaryote genomes. We find that use of primary sequence alone is insufficient for identifying novel H/ACA snoRNAs. Only the use of secondary structure filters reduces the number of candidates to a manageable size. From genomic context, we identify three strong H/ACA snoRNA candidates. These together with a further 47 candidates obtained by our analysis are being experimentally screened.
Tooth Enamel Evaluation After Tooth Bleaching With Hydrogen Peroxide Assisted by a DC Nonthermal Atmospheric-Pressure Plasma Jet

The purpose of this study is to evaluate the changes in dental enamel (morphology, elemental composition, microhardness, and roughness) after applying hydrogen peroxide in conjunction with a nonthermal plasma to bleach the teeth. Extracted human teeth were randomly placed in six groups. Two control groups (one group with no bleaching agent and no plasma treatment of the teeth and another one with only hydrogen peroxide as the bleaching agent) and four plasma groups (receiving hydrogen peroxide of varying concentrations 6%, 15%, 25%, and 35%, in conjunction with a plasma treatment) were prepared. The surface morphology before and after treatment was assessed using a scanning electron microscope (SEM), and the change in the elemental composition was analyzed by an energy-dispersive X-ray spectroscopy system. A total of 36 extracted teeth were used to evaluate the change in enamel microhardness and surface roughness. The use of hydrogen peroxide as a bleaching agent, even in the absence of plasma exposure, causes various etching patterns that are attributable to demineralization during the treatment process. These patterns are more pronounced as the hydrogen peroxide concentration increases. The surface roughness tests confirmed the findings from the SEM analysis. We only found minor essentially insignificant changes in the elemental composition of the enamel and in the surface microhardness as a result of the treatment using hydrogen peroxide and a cold plasma. The use of a cold plasma in conjunction with hydrogen peroxide of varying concentrations in tooth bleaching causes minor changes in the tooth enamel changes that are comparable to those resulting from the standard treatment using 35 % hydrogen peroxide gel without a plasma.
Calculated and observed long term performance of Leneghans embankment

This paper presents the finite element (FE) analysis of the consolidation of the foundation of an embankment constructed over soft clay deposit which shows significant time dependent behaviour and was improved with prefabricated vertical drains. To assess the capability of a simple elastic viscoplastic (EVP) model to predict the long term performance of a geotechnical structure constructed on soft soils, a well documented (Leneghans) embankment was analyzed to predict its long term behaviour characteristics. Two fully coupled two dimensional (2D) plane strain FE analyses have been carried out. In one of these, the foundation of the embankment was modelled with a relatively simpler time dependent EVP model and in the other one, for comparison purposes, the foundation soil was modelled with elasto-plastic Modified Cam-clay (MCC) model. Details of the analyses and the results are discussed in comparison with the field performance. Predictions from the creep (EVP) model were found to be better than those from Elasto-plastic (MCC) analysis. However, the creep analysis requires an additional parameter and additional computational time and resources.
Multi-Target, Multi-Camera Tracking by Hierarchical Clustering: Recent Progress on DukeMTMC Project

Although many methods perform well in single camera tracking, multi-camera tracking remains a challenging problem with less attention. DukeMTMC is a large-scale, well-annotated multi-camera tracking benchmark which makes great progress in this field. This report is dedicated to briefly introduce our method on DukeMTMC and show that simple hierarchical clustering with well-trained person re-identification features can get good results on this dataset.
Locomotion of jointed figures over complex terrain

This thesis describes a system that allows the creation of arbitrary jointed figures that can be animated traveling over uneven terrain with forbidden zones. Creatures can be easily described that have any number of legs, each leg having any number of joints, using an interactive, graphical "figure editor". Locomotion can be automatically generated from a figure description using default locomotion parameters, and these parameters can be adjusted to achieve a variety of locomotion styles. Techniques such as inverse-kinematics, dynamic simulation, step planning, and trajectory planning have been used. Thesis Supervisor: David Title: Assistant Professor Zeltzer of Computer Graphics This work was supported in part by NHK (Japan Broadcasting Corporation), and by an equipment loan from Symbolics, Inc.
Presentation of the Developed Mechatronic Devices for Exhibition Purposes

Exhibiting at fairs is especially important for companies. Therefore, they need a well-organized and interesting exhibition booth. This paper presents the development of a mechatronic device that could be suitable for exhibition purposes. The device is developed based only on the defined general requirements by a specific company, which produces DC motors and corresponding components. The development process was organized as a competition project for students. In the paper, the development process is presented briefly, starting with the presentation of the project task and finishing with the presentation of some of the competition final results.
Stacked Learning to Search for Scene Labeling

Search-based structured prediction methods have shown promising successes in both computer vision and natural language processing recently. However, most existing search-based approaches lead to a complex multi-stage learning process, which is ill-suited for scene labeling problems with a high-dimensional output space. In this paper, a stacked learning to search method is proposed to address scene labeling tasks. We design a simplified search process consisting of a sequence of ranking functions, which are learned based on a stacked learning strategy to prevent over-fitting. Our method is able to encode rich prior knowledge by incorporating a variety of local and global scene features. In addition, we estimate a labeling confidence map to further improve the search efficiency from two aspects: first, it constrains the search space more effectively by pruning out low-quality solutions based on confidence scores and second, we employ the confidence map as an additional ranking feature to improve its prediction performance and thus reduce the search steps. Our approach is evaluated on both semantic segmentation and geometric labeling tasks, including the Stanford Background, Sift Flow, Geometric Context, and NYUv2 RGB-D data set. The competitive results demonstrate that our stacked learning to search method provides an effective alternative paradigm for scene labeling.
Excellent cross-cultural validity, intra-test reliability and construct validity of the Dutch Rivermead Mobility Index in patients after stroke undergoing rehabilitation.

OBJECTIVE To investigate the cross-cultural validity of international Dutch-English comparisons when using the Dutch Rivermead Mobility Index (RMI), and the intra-test reliability and construct validity of the Dutch RMI. METHODS Cross-cultural validity was studied in a combined data-set of Dutch and English patients undergoing rehabilitation after stroke, who were assessed with the Dutch version of the RMI and the original English RMI, respectively. Mokken scale analysis was used to investigate unidimensionality, monotone homogeneity model fit, and differential item functioning between the Dutch and the English RMI. Intra-test reliability and construct validity were studied in the Dutch patients by calculating the reliability coefficient and correlating the Dutch RMI and the Dutch Barthel Index. RESULTS The RMI was completed for Dutch (n = 200) and English (n = 420) patients after stroke. The unidimensionality and monotone homogeneity model fit of the RMI were excellent: combined Dutch-English data-set (coefficient H = 0.91); Dutch data-set (coefficient H = 0.93); English data-set (coefficient H = 0.89). No differential item functioning was found between the Dutch and the English RMI. The intra-test reliability of the Dutch RMI was excellent (coefficient rho = 0.97). In a sub-sample of patients (n = 91), the Dutch RMI correlated strongly with the Dutch Barthel Index (Spearman's correlation coefficient rho = 0.84). CONCLUSION The Dutch RMI allows valid international Dutch-English comparisons, and has excellent intra-test reliability and construct validity.
Mammalian muscle acetylcholine receptor purification and characterization.

Nicotinic acetylcholine receptor (AcChR) was purified from fetal calf muscle by an affinity chromatographic method utilizing alpha-neurotoxin from Naja naja siamensis as an immobilized ligand. Preparations of AcChR with an average specific activity of 5 nmol of alpha-toxin bound/mg of protein were obtained, i.e., 75% of the theoretical specific activity assuming identity with Torpedo AcChR. Sodium dodecyl sulfate-polyacrylamide gel electrophoresis of the purified AcChR consistently showed the presence of five polypeptides, having apparent Mr's of 42 000, 44 000, 49 000, 55 000, and 58 000, respectively. The peptide of Mr 44K was demonstrated to be actin. The amino acid composition of fetal calf AcChR was shown to be similar to that of Torpedo AcChR. In addition, calf AcChR contained large amounts of amino sugars. The sedimentation coefficient of the purified calf AcChR was found to be 9.25 +/- 0.25, i.e., similar to the monomeric form of electric organ AcChR. Determination of the isoelectric point of alpha-bungarotoxin/calf AcChR complexes revealed the presence of two charged forms, having pI values of 5.16 +/- 0.13 and 6.05 +/- 0.18, respectively.
Strategies for shotgun identification of integral membrane proteins by tandem mass spectrometry

Integral membrane proteins (IMPs) are difficult to identify, mainly for two reasons: the hydrophobicity of IMPs and their low abundance. Sample preparation is a key component in the large‐scale identification of IMPs. In this review, we survey strategies for shotgun identification of IMPs by MS/MS. We will discuss enrichment, solubilization, separation, and digestion of IMPs, and data analysis for membrane proteomics.
The Instability of the Thermohaline Circulation in a Low-Order Model

Abstract Although the instability of the thermohaline circulation has been widely observed in numerical ocean models, theoretical advances have been hindered by the nonlinearity of heat and salt transports, a circulation governed by lateral temperature, and salinity gradients. Because the instability occurs initially in polar waters through the formation of haloclines and the halt of convection, any explanatory model must have at least a surface and a deep layer. The model proposed here (two surface boxes above a deep one) reduces to a 2 degrees-of-freedom dynamical system when convection is active and 3 degrees when it is interrupted. The instability that is induced by a negative freshwater perturbation in polar waters has three stages. The first stage is a rapid 5-yr adjustment to a transient thermal attractor that results from an approximate balance between heat advection and air–sea heat fluxes. The second stage is a slow evolution that self-organizes near this attractor, which preconditions the insta.
Multiple sequence alignment in parallel on a workstation cluster

SUMMARY Multiple sequence alignment is the NP-hard problem of aligning three or more DNA or amino acid sequences in an optimal way so as to match as many characters as possible from the set of sequences. The popular sequence alignment program ClustalW uses the classical method of approximating a sequence alignment, by first computing a distance matrix and then constructing a guide tree to show the evolutionary relationship of the sequences. We show that parallelizing the ClustalW algorithm can result in significant speedup. We used a cluster of workstations using C and message passing interface for our implementation. Experimental results show that speedup of over 5.5 on six processors is obtainable for most inputs. AVAILABILITY The software is available upon request from the second author.
Partial reversal of experimental pulmonary hypertension by phosphodiesterase-3/4 inhibition

Phosphodiesterase (PDE) inhibitors are currently under investigation for the therapy of pulmonary hypertension. The present study was designed to investigate chronic effects of oral pumafentrine, a mixed selective PDE-3/4 inhibitor, in monocrotaline (MCT)-induced pulmonary hypertension in rats. Treatment with pumafentrine (10 mg·kg−1 daily) from week 4 to 6 after a single injection of MCT (60 mg·kg−1) partially reversed pulmonary hypertension and right heart hypertrophy in rats. In addition, small pulmonary arterial muscularisation, media hypertrophy and decrease in lumen area were largely reversed. Inhibition of smooth muscle proliferation under pumafentrine was demonstrated in vivo as was a pro-apoptotic effect of pumafentrine on vascular cells. Moreover, pumafentrine dose-dependently increased cyclic adenosine monophosphate levels and inhibited proliferation of cultured pulmonary arterial smooth muscle cells. In conclusion, oral pumafentrine partially reverses monocrotaline-induced pulmonary hypertension, lung vascular remodelling and right heart hypertrophy in rats.
Improved mass detection in 3D automated breast ultrasound using region based features and multi-view information

Breast cancer is one of the leading causes of cancer death for women. Early detection of breast cancer is crucial for reducing mortality rates and improving prognosis of patients. Recently, 3D automated breast ultrasound (ABUS) has gained increasing attentions for reducing subjectivity, operator-dependence, and providing 3D context of the whole breast. In this work, we propose a breast mass detection algorithm improving voxel-based detection results by incorporating 3D region-based features and multi-view information in 3D ABUS images. Based on the candidate mass regions produced by voxel-based method, our proposed approach further improves the detection results with three major steps: 1) 3D mass segmentation in geodesic active contours framework with edge points obtained from directional searching; 2) region-based single-view and multi-view feature extraction; 3) support vector machine (SVM) classification to discriminate candidate regions as breast masses or normal background tissues. 22 patients including 51 3D ABUS volumes with 44 breast masses were used for evaluation. The proposed approach reached sensitivities of 95%, 90%, and 70% with averaged 4.3, 3.8, and 1.6 false positives per volume, respectively. The results also indicate that the multi-view information plays an important role in false positive reduction in 3D breast mass detection.
3-D Rat Brain Phantom for High-Resolution Molecular Imaging

With the steadily improving resolution of novel small-animal single photon emission computed tomography (SPECT) and positron emission tomography devices, highly detailed phantoms are required for testing and optimizing these systems. We present a three-dimensional (3-D) digital and physical phantom pair to represent, e.g., cerebral blood flow, glucose metabolism, or neuroreceptor binding in small regions of the rat brain. The anatomical structures are based on digital photographs of the uncut part of a rat brain cryosection block. The photographs have been segmented into ventricles and gray and white matter and have been stacked afterwards. In the resulting voxelized digital phantom, tracer concentration in gray and white matter can be scaled independently. This is of relevance since, e.g., cerebral blood flow or metabolism are much higher in gray than in white matter. The physical phantom is based on the digital phantom and has been manufactured out of hardened polymer using rapid prototyping, a process in which complicated 3-D objects can be built up layer by layer. X-ray computed tomography and high-resolution SPECT images of the physical phantom are compared with the digital phantom. The detailed physical phantom can be filled bubble-free. Excellent correspondence is shown between details in the digital and physical phantom. Therefore, this newly developed brain phantom will enable the optimization of high-resolution imaging for recovery of complex shaped molecular distributions.
Timing Arc based logic analysis for false noise reduction

The problem of calculating accurate impact of crosstalk on a circuit considering its inherent logic and timing properties is very complex. Although it has been widely studied, it still lacks an efficient solution. As a result, state-of-the-art crosstalk calculators use simplistic and overly pessimistic models resulting in the over-estimation of crosstalk effects. Such pessimism in crosstalk analysis often leads to the triggering of false violations and consequently an inefficient use of design resources. The main contribution of this paper is a novel technique called Timing Arc Based Logic Analysis (TABLA) that serves as an efficient means to calculate realistic crosstalk bounds. TABLA uses timing arcs as basic elements to perform an efficient temporal logic analysis employing the min-max timing model using dedicated solvers for logic and timing. Additionally, a procedure to generate powerful conflict clauses is proposed to improve the run time of the overall analysis. The proposed technique has been tested in an industrial environment on benchmark circuits as well as on an industrial design, and results are provided.
Refine bigram PLSA model by assigning latent topics unevenly

As an important component in many speech and language processing applications, statistical language model has been widely investigated. The bigram topic model, which combines advantages of both the traditional n-gram model and the topic model, turns out to be a promising language modeling approach. However, the original bigram topic model assigns the same topic number for each context word but ignores the fact that there are different complexities to the latent semantics of context words, we present a new bigram topic model, the bigram PLSA model, and propose a modified training strategy that unevenly assigns latent topics to context words according to an estimation of their latent semantic complexities. As a consequence, a refined bigram PLSA model is reached. Experiments on HUB4 Mandarin test transcriptions reveal the superiority over existing models and further performance improvements on perplexity are achieved through the use of the refined bigram PLSA model.
Improving Hyperspectral Image Classification Using Spectral Information Divergence

In order to improve the classification performance for hyperspectral image (HSI), a sparse representation classifier based on spectral information divergence (SID) is proposed. SID measures the discrepancy of probabilistic behaviors between the spectral signatures of two pixels from the aspect of information theory, which can be more effective in preserving spectral properties. Thus, the new method measures the similarity between the reconstructed pixel and the true pixel by SID instead of by the L2 norm used in traditional sparse model. Moreover, the spatial coherency across neighboring pixels sharing a common sparsity pattern is taken into account during the construction of SID-based joint sparse representation model. We propose a new version of the orthogonal matching pursuit method to solve SID-based recovery problems. The proposed SID-based algorithms are applied to real HSI for classification. Experimental results show that our algorithms outperform the classical sparse representation based classification algorithms in most cases.
Interaction science SIG: overcoming challenges

Over the past 30 years science has played a key role in shaping and advancing research in Human-Computer Interaction. Informed in part by methods, theories and findings from the behavioral sciences and from computer science, scientific contributions to HCI have provided explanations of how and why people interact through and with technology. We argue that the contribution of science to HCI could be enhanced if key challenges are met. During a SIG meeting we will discuss the challenges and potential responses and set an agenda for the coming years.