With development of cloud computing new ways for easy, on-demand, Internet-based access to computing resources have emerged. In such context a Service Level Agreement (SLA) enables contractual agre ...

The emission of electrons from the surface of a material into vacuum depends strongly on the material’s work function, temperature, and the intensity of electric field. The combined effects of these give rise to a multitude of related phenomena, including Fowler-Nordheim tunneling and Schottky emission, which, in turn, enable several families of devices, ranging from vacuum tubes, to Schottky diodes, and thermionic energy converters. More recently, nanomembrane-based detectors have found applications in high-resolution mass spectrometry measurements in proteomics. Progress in all the aforementioned applications critically depends on discovering materials with effective low surface work functions. We show that a few atomic layer deposition (ALD) cycles of zinc oxide onto suspended diamond nanomembranes, strongly reduces the threshold voltage for the onset of electron field emission which is captured by resonant tunneling from the ZnO layer. Solving the Schroedinger equation, we obtain an electrical field- and thickness-dependent population of the lowest few subbands in the thin ZnO layer, which results in a minimum in the threshold voltage at a thickness of 1.08 nm being in agreement with the experimentally determined value. We conclude that resonant tunneling enables cost-effective ALD coatings that lower the effective work function and enhance field emission from the device.

In this paper, we introduce a transfer learning approach for our novel hybrid brain-computer interface in which electroencephalography and functional transcranial Doppler ultrasound are used simultaneously to record brain electrical activity and cerebral blood velocity respectively due to flickering mental rotation and word generation tasks. We reduced each trial into a scalar score using Regularized Discriminant Analysis (RDA). For each individual, class conditional probabilistic distribution of each mental task was estimated using RDA scores of the trials corresponding to that mental task. Similarities between class conditional distributions across individuals were measured using Kullback-Leibler divergence, Bhattacharyya, and Hellinger distances. Classification task was performed using Quadratic Discriminant Analysis (QDA), Linear Discriminant Analysis (LDA), and Support Vector Machines (SVM). We demonstrate that transfer learning can reduce calibration requirements up to %87.5. Moreover, it was found that QDA provides the most significant performance improvement compared to the case when no transfer learning is employed.

Abstract In order to counteract today’s sophisticated and increasing number of cyber threats the timely acquisition of information regarding vulnerabilities, attacks, threats, countermeasures and risks is crucial. Therefore, employees tasked with information security risk management processes rely on a variety of information security data sources, ranging from inter-organizational threat intelligence sharing platforms to public information security data sources, such as mailing lists or expert blogs. However, research and practice lack a comprehensive overview about these public information security data sources, their characteristics and dependencies. Moreover, comprehensive knowledge about these sources would be beneficial to systematically use and integrate them to information security processes. In this paper, a triangulation study is conducted to identify and analyze public information security data sources. Furthermore, a taxonomy is introduced to classify and compare these data sources based on the following six dimensions: (1) Type of information, (2) Integrability, (3) Timeliness, (4) Originality, (5) Type of Source,and (6) Trustworthiness. In total, 68 public information security data sources were identified and classified. The investigations showed that research and practice rely on a large variety of heterogeneous information security data sources, which makes it more difficult to integrate and use them for information security and risk management processes.

Objective: Histology is often used as a gold standard to evaluate noninvasive imaging modalities such as a magnetic resonance imaging (MRI). Spatial correspondence between histology and MRI is a critical step in quantitative evaluation of skeletal muscle in golden retriever muscular dystrophy (GRMD). Registration becomes technically challenging due to nonorthogonal histology section orientation, section distortion, and the different image contrast and resolution. Methods: This study describes a three-step procedure to register histology images with multiparametric MRI, i.e., interactive slice localization controlled by a three-dimensional mouse, followed by an affine transformation refinement, and a B-spline deformable registration using a new similarity metric. This metric combines mutual information and gradient information. Results: The methodology was verified using ex vivo high-resolution multiparametric MRI with a resolution of 117.19 μm (i.e., T1-weighted and T2-weighted MRI images) and trichrome stained histology images acquired from the pectineus muscles of ten dogs (nine GRMD and one healthy control). The proposed registration method yielded a root mean squares (RMS) error of 148.83 ± 34.96 μm averaged for ten muscle samples based on landmark points validated by five observers. The best RMS error averaged for ten muscles, was 128.48 ± 25.39 μm. Conclusion: The established correspondence between histology and in vivo MRI enables accurate extraction of MRI characteristics for histologically confirmed regions (e.g., muscle, fibrosis, and fat). Significance: The proposed methodology allows creation of a database of spatially registered multiparametric MRI and histology. This database will facilitate accurate monitoring of disease progression and assess treatment effects noninvasively.

Aim of this paper is to, by means of comparative analysis, demonstrate that contemporary pension systems are limitation factors of development of the Republic of Srpska, and that they should be reformed and improved. Ultimately, pension systems should be the basis for development of the Republic of Srpska. They should significantly improve strengthening of financial markets, enhancement of capital markets, higher growth rates of the Republic of Srpska, idecrease of unemployment. Private pension funds are to change the habits and ideas of every future insurance holder, aiming to make the pension rights a matter of concern of every individual, instead being the obligation and ballast of the society. Today, stabile financing of pension systems and their funds is becoming increasingly questionable. A gap is emerging between the area of rights gained by law and financial possibilities for their implementation. Pay-as-you-go (PAYG) systems, i.e. systems of inter-generation solidarityare particularly endangered. Adequate systematization of gathered data, i.e. evidence, should provide conclusions that pension systems are a limitation todevelopment of national economy. This claim is present in underdeveloped and developing countries, with developed economies also facing grave problems.

In software engineering courses with many students, it is often impossible for a professor to give a detailed review of the software project for each student. One solution is to give students a task to make reviews for a few projects. One review consists of a comment on a project and a score. The score represents an ordinal number of the project when student sorts all projects in order by quality. The comment can be used as feedback to their colleagues and the score can be used in the final grade prediction. Double-blind peer review is used to prevent favoritism and unfairness. In the paper methods for random projects distribution, reviews gathering and analysis are presented. Methods have been used on over 100 projects and data gathered from them show moderate to high correlation with final grades. Project rank and project points have correlation factors from r=-0.6 to r=-0.66 and significance p<0.001. Projects have been independently graded with automatic tests.

Klir-Yuan fuzzy implication, as fuzzy implication generated from the standard strong fuzzy negation, the probabilistic sum t-conorm, and the product t-norm, represents a classical example of QL-implication, where QL-implications are the short for quantum logic fuzzy implications. In this paper we prove that the recent results on equivalences between fuzzy formulas and fuzzy dependencies remain invariant with respect to QL-implications when considered through Klir-Yuan fuzzy implication.

In this paper we complement the most recent results on soundness of inference rules for new vague multivalued dependencies. Motivated by the fact that the inclusive and the augmentation rules are sound, we prove that: complementation, transitivity, replication, coalescence, union, pseudo-transitivity, decomposition, and mixed pseudo-transitivity rules are also sound. Our research relies on definitions of vague functional and vague multivalued dependencies based on appropriately selected similarity measures between vague values, vague sets, and tuples on sets of attributes.

This paper represents a natural continuation of our previous study. In our earlier research we proved that the inclusive inference rule and the union inference rule for new vague functional dependencies are sound, and sketched a proof of the fact that the set of the main inference rules is a complete set. In the present paper we rigorously prove that: reflexive, augmentation, transitivity, pseudo-transitivity, and decomposition inference rules are also sound. Some additional insights in completeness of the main inference rules are also provided.

The Editors’ Network of the European Society of Cardiology provides a dynamic forum for editorial discussions and endorses the recommendations of the International Committee of Medical Journal Editors (ICMJE) to improve the scientific quality of biomedical journals. Authorship confers credit and important academic rewards. Recently, however, the ICMJE emphasized that authorship also requires responsibility and accountability. These issues are now covered by the new (fourth) criterion for authorship. Authors should agree to be accountable and ensure that questions regarding the accuracy and integrity of the entire work will be appropriately addressed. This review discusses the implications of this paradigm shift on authorship requirements with the aim of increasing awareness on good scientific and editorial practices.

Abstract Education plays a central role in today’s understanding of growth and development dynamics. However, its relationship with other factors is complex. This paper aims to investigate the effect of different forms of education on youth employability in Bosnia and Herzegovina. This is done by using the USAID MEASURE – BiH National Youth Survey. Research has shown that formal education and non-formal education through internship programmes, volunteering, paid jobs other than internships are significant predictors of youth employment status. The study also has several implications for academics and practitioners since it provides new insights into both employment patterns and practices in one transition economy but also calls for further analysis of the link between education, formal and non-formal, and youth employment.

Breast cancer is the second most common cause of cancer-related deaths among women worldwide. It is a heterogeneous disease with four major molecular subtypes. One of the subtypes, human epidermal growth factor receptor 2 (HER2)-enriched (HER2-positive) is characterized by the absence of estrogen and progesterone receptors and overexpression of HER2 receptor, and accounts for 15–20% of all breast cancers. Despite the anti-HER2 and cytotoxic chemotherapy, HER2 subtype is an aggressive disease with significant mortality. Recent advances in molecular biology techniques, including gene expression profiling, proteomics, and microRNA analysis, have been extensively used to explore the underlying mechanisms behind human breast carcinogenesis and metastasis including HER2-positive breast cancer, paving the way for developing new targeted therapies. This review focuses on recent advances on gene expression and miRNA status in HER2-positive breast cancer.