Miracle-dz/UniFAR-FTUs huggingface dataset:
The effects of an acute bout of moderate intensity cycling on EEG activity during anger

Anger is associated with increased risk for cardiovascular diseases and is associated with aggressive and violent behavior thereby representing a considerable burden on public health and welfare. Laboratory methods that reliably manipulate anger are necessary to understand the neurobiology of anger and to aid tests of the efficacy of interventions, including exercise, designed to reduce anger. Recent evidence suggests that pictures of natural scenes can be used to elicit angry emotions and that hemispheric asymmetry in alpha oscillatory frequencies measured by electroencephalography (EEG) at anterior brain sites is a neural index of anger. In addition to evaluating cortical oscillations during emotion, event-related potentials (ERP), particularly the latepositive potential (LPP), are consistently associated with different aspects of emotion processing. There have been no studies, however, that evaluated ERP to anger-inducing pictures. The purpose of the initial study was to evaluate feelings of anger-intensity, arousal and pleasantness/unpleasantness, as well as oscillatory and ERP indices of emotion, during the presentation of pictures of natural scenes and emotional faces. The results suggest that pictures of natural scenes result in the highest feelings of anger intensity and the most intense emotional experience. In addition, the amplitude of the LPP is highest at central-parietal cites while viewing anger-inducing scenes. A second study was conducted to evaluate the effects an acute bout of moderate intensity cycling exercise on state anger and feelings of anger-intensity, arousal, and pleasantness/unpleasantness as well as oscillatory and ERP indices of emotion during picture viewing. The results of the second study suggest that acute exercise reduces state anger and protects against increases in an evoked angry mood. However, the exercise does not alter anger intensity or EEG correlates of anger during the viewing of pictures that elicit anger. Whereas exercise did not alter an angry emotional response using this paradigm, future studies should use other emotioninduction methods to elicit stronger anger responses and should also evaluate the effects of chronic exercise on trait anger. INDEX WORDS: anger expression, late-positive potential, electroencephalography THE EFFECTS OF AN ACUTE BOUT OF MODERATE INTENSITY CYCLING ON EEG ACTIVITY DURING ANGER
Periodic Orbits and Chaotic Sets in a Low-Dimensional Model for Shear Flows

We consider the dynamics of a low-dimensional model for turbulent shear flows. The model is based on Fourier modes and describes sinusoidal shear flow, in which fluid between two free-slip walls experiences a sinusoidal body force. The model contains nine modes, most of which have a direct hydrodynamical interpretation. We analyze the stationary states and periodic orbits for the model for two different domain sizes. Several kinds of bifurcations are identified, including saddle-node bifurcations, a period doubling cascade, and Hopf bifurcations of the periodic orbits. For both domain sizes, long-lived transient chaos appears to be associated with the presence of a large number of unstable periodic orbits. For the smaller minimal flow unit domain, it is found that a periodic solution is stable over a range of Reynolds numbers, and its bifurcations lead to the existence of a chaotic attractor. The model illustrates many phenomena observed and speculated to exist in the transition to turbulence in linearly .
Cloud Service Capability Maturity Model (Cs-Cmm): A Preliminary Study on Its Conceptual Design

As information technologies evolve and demands of enterprises on larger data and integrated info services keep growing, the market of cloud services (CS) attracts many more players nowadays. However, the quality of the services may vary due to different service capabilities and a service often requires integration with other services, CS providers need a standard way in implementing and improving the quality of their services. With the focus on process, this paper applies the concepts of CMMI (Capability Maturity Model Integration) and presents a CS quality implementation and improvement guidance model, called CS-CMM (Cloud Service Capability Maturity Model). Due to its novelty and preliminary status, this paper focuses on introducing the concepts and structural design of the model. This includes the concepts of CS process areas as the building blocks of the model, CS maturity and capability levels as the roadmap towards superior service quality, and the institutionalization design for sustaining the implementation results.
Phase Invariant Keypoint Detection

This paper introduces extensions to the complex wavelet keypoint detection paper [1], Keypoints are generated by finding local peaks in accumulated, interpolated maps of the product of magnitudes of directional complex filter responses, as in earlier work. Gradient vector fields derived from these maps are used for keypoint scale characterisation, but this is now performed so as to remove the directionality of gradient field sampling, thereby improving the stability of scale estimates. A new class of keypoints is also introduced: the circular measure (CM) keypoints, which are used to augment the locations found by the filter magnitude product (FMP) keypoints. This new keypoint class generates a higher proportion of keypoints in the interiors of objects, whilst simultaneously providing approximate object scale information, and appears appropriate for directing the attention of a vision system to the interiors of well-defined regions.
A very high accuracy handwritten character recognition system for Farsi/Arabic digits using Convolutional Neural Networks

In this paper, a new method is presented for recognizing the handwritten Farsi/Arabic digits by fusing the recognition results of a number of Convolutional Neural Networks with gradient descent training algorithm. Convolutional Neural Networks are a type of neural networks that are biologically inspired from human visual system which combines feature extraction and classification stages. This paper is concentrated on two main contributions. The first one is automatic extraction of input pattern's features by using a CNN for Farsi digits and the second one is fusing the results of boosted classifiers to compensate the recognizers' errors. The difference between competing systems is in the training set, which the frequency of samples that are “hard to recognize” were become higher in boosted classifiers. In addition, two rejection strategies were proposed and evaluated to find out “hard to recognize” samples. The experiments were conducted on extended IFH-CDB test database. The results reveal a very high accuracy classifier outperforming most of the previous systems. The achieved result shows 99.17% in recognition rate. In addition, the result was grown up to 99.98% after rejection of ten percents of “hard to recognize” samples.
Assessing the role of IKCa channels in generating the sAHP of CA1 hippocampal pyramidal cells

ABSTRACT Our previous work reported that KCa3.1 (IKCa) channels are expressed in CA1 hippocampal pyramidal cells and contribute to the slow afterhyperpolarization that regulates spike accommodation in these cells. The current report presents data from single cell RT-PCR that further reveals mRNA in CA1 cells that corresponds to the sequence of an IKCa channel from transmembrane segments 5 through 6 including the pore region, revealing the established binding sites for 4 different IKCa channel blockers. A comparison of methods to internally apply the IKCa channel blocker TRAM-34 shows that including the drug in an electrode from the onset of an experiment is unviable given the speed of drug action upon gaining access for whole-cell recordings. Together the data firmly establish IKCa channel expression in CA1 neurons and clarify methodological requirements to obtain a block of IKCa channel activity through internal application of TRAM-34.
Mobile Augmented Reality for the m-Worker

In the following paper, we introduce some ideas of future technologies to support mobile work. We understand by mobile work the activities taking place during engineering tasks done remotely and requiring to be available from anywhere at anytime. In particular, we investigate the devices that can be used and the user interfaces to support the concurrent engineering in this type of environment. The research has been focused on Augmented Reality, a technique that allows the computer to overlap the user environment with artificial graphics. By using this technique we predict that the user will have a better access and interaction to various information from non-desktop devices (i.e. mobile devices). This paper includes several applications in which the mobile work can be enhanced by the use of advanced user interfaces for mobile devices. Communities’ Topics addressed Collaboration@Work: Mobility@Work: Mobile workplace platforms and technologies
Order allocation in a multiple-vendor and quantity discount environment: A multi-objective decision making approach

Article history: Received: April 20, 2018 Received in revised format: June 21, 2018 Accepted: July 6, 2018 Available online: July 6, 2018 Integrated supplier selection and order allocation is a complex problem that is important for both designing and operating supply chains. It becomes especially complicated when quantity discounts are considered at the same time. Under such circumstances, most studies often formulate the problem as a Multi-Objective Linear Programming problem (MOLP), and then transform it to a Mixed Integer Programming problem (MIP) to handle the inherited multi-objectives, simultaneously. But, objectives are not of equal importance and in this approach scaling and subjective weighting often are not considered. In addition, some of the studies that use weighting method to solve the MOLP, usually ignore to normalize the coefficients. However, as different coefficients have different units such as cost or number coefficients, so weighted summation will be meaningless. Furthermore, in most of the studies only quantitative criteria are considered in mathematical model. But, the importance of some qualitative criteria persuade decision maker to consider other affective criteria as well as cost. In this study, in order to ease the problem and to obtain a more reasonable compromised solution for order allocating among suppliers, an integration of analytical hierarchy process and linear integer and multi-objective programming is proposed. The large number of criteria and attributes are employed in this problem and they are employed in a comprehensive model to solve the multi-objective problem and to find the most preferred non dominated solutions by considering decision maker’s (DM) preferences. Some illustrative examples are solved using LINGO and the results are compared. The sensitivity analysis and comparing the results with one of the well-known studies in the literature has demonstrated the flexibility and efficiency of the proposed model to deal with large sized problems and incorporate different purchasing policies, easily and in a short amount of time. © 2018 by the authors; licensee Growing Science, Canada
A Universal Interpreter for Nondeterministic Concurrent Programming Languages

Nondeterministic concurrent programming languages (ncpl) are languages which contain as primitive constructs nondeterministic choice and concurrent composition (inter-leaving). The best known are the languages based on CCS of Milner which are used as mathematical model of communication of concurrent processes. Concurrent constraint programming languages have been intensively studied during the last decade and reeect the eeorts directed to extend the constraint logic programming paradigm and also may be characterised as a subclass of ncpl. The universal interpreter for ncp languages under development is considered as a new uniied approach for the deenition of the operational semantics of these languages, their comparative study and the development of prototypes for new applications. This interpreter is a generic program which may be used as a mathematical model for diierent classes of programs. Several applications of universal interpreter for the study of ncpl languages have been considered and one of them is considered in detail in this paper. This application is checking the operational semantics of Scc language-the synchronous concurrent constraint language, of Namur. The experiments have been performed for ground term constraints with set theoretic inclusion as an entailment relation and for Herbrand universe as another entail-ment system. As a result of these experiments the soundness and eeciency of operational semantics for Scc has been basically connrmed. At the same time some gaps in the deeni-tion of operational semantics have been discovered and the improved semantics has been established and implemented by interpreter.
Spin equation and its solutions

The aim of the present article is to study in detail the so‐called spin equation (SE) and present both the methods of generating new solution and a new set of exact solutions. We recall that the SE with a real external field can be treated as a reduction of the Pauli equation to the (0+1)‐dimensional case. Two‐level systems can be described by an SE with a particular form of the external field. In this article, we also consider associated equations that are equivalent or (in one way or another) related to the SE. We describe the general solution of the SE and solve the inverse problem for this equation. We construct the evolution operator for the SE and consider methods of generating new sets of exact solutions. Finally, we find a new set of exact solutions of the SE.
Spindle Assembly Checkpoint Protein Dynamics Reveal Conserved and Unsuspected Roles in Plant Cell Division

Background In eukaryotes, the spindle assembly checkpoint (SAC) ensures that chromosomes undergoing mitosis do not segregate until they are properly attached to the microtubules of the spindle. Methodology/Principal Findings We investigated the mechanism underlying this surveillance mechanism in plants, by characterising the orthogolous SAC proteins BUBR1, BUB3 and MAD2 from Arabidopsis. We showed that the cell cycle-regulated BUBR1, BUB3.1 and MAD2 proteins interacted physically with each other. Furthermore, BUBR1 and MAD2 interacted specifically at chromocenters. Following SAC activation by global defects in spindle assembly, these three interacting partners localised to unattached kinetochores. In addition, in cases of ‘wait anaphase’, plant SAC proteins were associated with both kinetochores and kinetochore microtubules. Unexpectedly, BUB3.1 was also found in the phragmoplast midline during the final step of cell division in plants. Conclusions/Significance We conclude that plant BUBR1, BUB3.1 and MAD2 proteins may have the SAC protein functions conserved from yeast to humans. The association of BUB3.1 with both unattached kinetochore and phragmoplast suggests that in plant, BUB3.1 may have other roles beyond the spindle assembly checkpoint itself. Finally, this study of the SAC dynamics pinpoints uncharacterised roles of this surveillance mechanism in plant cell division.
Assisted Curation: Does Text Mining Really Help?

Although text mining shows considerable promise as a tool for supporting the curation of biomedical text, there is little concrete evidence as to its effectiveness. We report on three experiments measuring the extent to which curation can be speeded up with assistance from Natural Language Processing (NLP), together with subjective feedback from curators on the usability of a curation tool that integrates NLP hypotheses for protein-protein interactions (PPIs). In our curation scenario, we found that a maximum speed-up of 1/3 in curation time can be expected if NLP output is perfectly accurate. The preference of one curator for consistent NLP output and output with high recall needs to be confirmed in a larger study with several curators.
Fast Kernel-based method for anomaly detection

Anomaly detection (AD) involves detecting abnormality from normality and has a wide spectrum of applications in reality. Kernel-based methods for AD have been proven robust with diverse data distributions and offering good generalization ability. Stochastic gradient descent (SGD) method has recently emerged as a promising framework to devise ultra-fast learning methods. In this paper, we conjoin the advantages of Kernel-based method and SGD-based method to propose fast learning methods for anomaly detection. We validate the proposed methods on 8 benchmark datasets in UCI repository and KDD cup 1999 dataset. The experimental results show that the proposed methods offer a comparable one-class classification accuracy while simultaneously achieving a significantly computational speed-up.
The spectral sensitivity of the lens eyes of a box jellyfish, Tripedalia cystophora (Conant)

SUMMARY Box jellyfish, or cubomedusae (class Cubozoa), are unique among the Cnidaria in possessing lens eyes similar in morphology to those of vertebrates and cephalopods. Although these eyes were described over 100 years ago, there has been no work done on their electrophysiological responses to light. We used an electroretinogram (ERG) technique to measure spectral sensitivity of the lens eyes of the Caribbean species Tripedalia cystophora. The cubomedusae have two kinds of lens eyes, the lower and upper lens eyes. We found that both lens eye types have similar spectral sensitivities, which likely result from the presence of a single receptor type containing a single opsin. The peak sensitivity is to blue-green light. Visual pigment template fits indicate a vitamin A-1 based opsin with peak sensitivity near 500 nm for both eye types.
Onset detection algorithm in voice activity detection for Mandarin

Voice activity detection (VAD) is one of the most challenging problems in the field of speech signal processing. The statistical model based VADs have been widely studied in the recent literatures, which usually utilize hangover algorithms to prevent clipping of weak speech tails. However, little attention has been paid on the initial consonants, and non-negligible onset detection errors might be incurred especially when the SNR is low. Since most of the Mandarin syllables start with initial consonants, an onset detection algorithm is proposed in this paper to improve the performance of VAD for Mandarin. Although consonants are mostly noise-like, they produce spectral energy distributed more towards the higher frequencies. To this characteristic, the proposed algorithm makes decision whether the weak-start detection could possibly been dampened by noise based on the posterior SNR of high frequency band, and then it makes correction correspondingly after estimating whether the week-start speech frames mistaken for nonspeech frames exist. It shows that the proposed algorithm achieves a considerable performance improvement. Furthermore, this algorithm is independent of noise type.
MERTK as a novel therapeutic target in head and neck cancer

Although head and neck cancer (HNSCC) is the sixth most common tumor entity worldwide therapy options remain limited leading to 5-year survival rates of only 50 %. MERTK is a promising therapeutic target in several tumor entities, however, its role in HNSCC has not been described yet. The aim of our study was to investigate the biological significance of MERTK and to evaluate its potential as a novel therapeutic target in this dismal tumor entity. In two large HNSCC cohorts (n=537 and n=520) we found that MERTK is overexpressed in one third of patients. In-vitro, MERTK overexpression led to increased proliferation, migration and invasion whereas MERTK inhibition with the small molecule inhibitor UNC1062 or MERTK knockdown reduced cell motility via the small GTPase RhoA. Taken together, we are the first to show that MERTK is frequently overexpressed in HNSCC and plays an important role in tumor cell motility. It might therefore be a potential target for selected patients suffering from this dismal tumor entity.
Ownership, Productivity Change, and Financial Performance in Chinese Industry

This paper investigates Chinese industrial productivity from 1980 to 1996. Results include series for foreign-linked, shareholding, and private enterprises. We find long-term productivity increase, with growth rates declining during the 1990's. Productivity outcomes outside the state and collective sectors are modest, with shareholding enterprises suffering productivity declines. The paper examines differences in marginal factor productivity across ownership types, considers the impact of business cycles on the interpretation of productivity trends, and documents a statistical relationship among the profitability of state enterprises, the relative productivity performance of state firms, and the entry of new firms outside the state sector.J. Comp. Econom. , December 2000, 28(4), pp. 786–813. Brandeis University, Waltham, Massachusetts 02254; University of Pittsburgh, Pittsburgh, Pennsylvania 15260; Institute of Quantitative and Technical Economics, Chinese Academy of Social Sciences, 5 Jianguomennei Street, Beijing, China 100732.
Ensembl 2008

The Ensembl project (http://www.ensembl.org) is a comprehensive genome information system featuring an integrated set of genome annotation, databases and other information for chordate and selected model organism and disease vector genomes. As of release 47 (October 2007), Ensembl fully supports 35 species, with preliminary support for six additional species. New species in the past year include platypus and horse. Major additions and improvements to Ensembl since our previous report include extensive support for functional genomics data in the form of a specialized functional genomics database, genome-wide maps of protein–DNA interactions and the Ensembl regulatory build; support for customization of the Ensembl web interface through the addition of user accounts and user groups; and increased support for genome resequencing. We have also introduced new comparative genomics-based data mining options and report on the continued development of our software infrastructure.
Universities’ attractiveness to students: The Darwinism effect

Due to significant government cuts to Higher Education funding in Southern European systems, their already underfunded universities were forced to increasingly compete for students as sources of additional revenue. Concurrently, families and students that continued to afford participation in Higher Education became more selective when choosing a university, realising the riskier investment that Higher Education participation had become. Through a competing destinations model and relying on all Italian private and public universities, this study finds that the competition forces characterising universities’ attractiveness over the last decade have changed since the financial crisis of 2008. In a context of lower demand for Higher Education, the competition for students grew and universities in close proximity were better prepared to face the new challenges, leading to the growth of Higher Education clusters.