Dissipativity analysis of stochastic fuzzy neural networks with randomly occurring uncertainties using delay dividing approach

This paper focuses on the problem of delay-dependent robust dissipativity analysis for a class of stochastic fuzzy neural networks with time-varying delay. The randomly occurring uncertainties under consideration are assumed to follow certain mutually uncorrelated Bernoulli-distributed white noise sequences. Based on the Itô's differential formula, Lyapunov stability theory, and linear matrix inequalities techniques, several novel sufficient conditions are derived using delay partitioning approach to ensure the dissipativity of neural networks with or without time-varying parametric uncertainties. It is shown, by comparing with existing approaches, that the delay-partitioning projection approach can largely reduce the conservatism of the stability results. Numerical examples are constructed to show the effectiveness of the theoretical results

Subgroup Discovery in MOOCs: A Big Data Application for Describing Different Types of Learners

The aim of this paper is to categorize and describe different types of learners in massive open online courses (MOOCs) by means of a subgroup discovery approach based on MapReduce. The final objective is to discover IF-THEN rules that appear in different MOOCs. The proposed subgroup discovery approach, which is an extension of the well-known FP-Growth algorithm, considers emerging parallel methodologies like MapReduce to be able to cope with extremely large datasets. As an additional feature, the proposal includes a threshold value to denote the number of courses that each discovered rule should satisfy. A post-processing step is also included so redundant subgroups can be removed. The experimental stage is carried out by considering de-identified data from the first year of 16 MITx and HarvardX courses on the edX platform. Experimental results demonstrate that the proposed MapReduce approach outperforms traditional sequential subgroup discovery approaches, achieving a runtime that is almost constant for different courses. Additionally, thanks to the final post-processing step, only interesting and not-redundant rules are discovered, hence reducing the number of subgroups in one or two orders of magnitude. Finally, the discovered subgroups are easily used by courses' instructors not only for descriptive purposes but also for additional tasks such as recommendation or personalization

Combinations of methods for collaborative evaluation of the usability of interactive software systems

Usability is a fundamental quality characteristic for the success of an interactive system. It is a concept that includes a set of metrics and methods in order to obtain easy-to-learn and easy-to-use systems. Usability Evaluation Methods, UEM, are quite diverse; their application depends on variables such as costs, time availability, and human resources. A large number of UEM can be employed to assess interactive software systems, but questions arise when deciding which method and/or combination of methods gives more (relevant) information. We propose Collaborative Usability Evaluation Methods, CUEM, following the principles defined by the Collaboration Engineering. This paper analyzes a set of CUEM conducted on different interactive software systems. It proposes combinations of CUEM that provide more complete and comprehensive information about the usability of interactive software systems than those evaluation methods conducted independentl

Combinations of Methods for Collaborative Evaluation of the Usability of Interactive Software Systems

Usability is a fundamental quality characteristic for the success of an interactive system. It is a concept that includes a set of metrics and methods in order to obtain easy-to-learn and easy-to-use systems. Usability Evaluation Methods, UEM, are quite diverse; their application depends on variables such as costs, time availability, and human resources. A large number of UEM can be employed to assess interactive software systems, but questions arise when deciding which method and/or combination of methods gives more (relevant) information. We propose Collaborative Usability Evaluation Methods, CUEM, following the principles defined by the Collaboration Engineering. This paper analyzes a set of CUEM conducted on different interactive software systems. It proposes combinations of CUEM that provide more complete and comprehensive information about the usability of interactive software systems than those evaluation methods conducted independently

Combinations of Methods for Collaborative Evaluation of the Usability of Interactive Software Systems

Usability is a fundamental quality characteristic for the success of an interactive system. It is a concept that includes a set of metrics and methods in order to obtain easy-to-learn and easy-to-use systems. Usability Evaluation Methods, UEM, are quite diverse; their application depends on variables such as costs, time availability, and human resources. A large number of UEM can be employed to assess interactive software systems, but questions arise when deciding which method and/or combination of methods gives more (relevant) information. We propose Collaborative Usability Evaluation Methods, CUEM, following the principles defined by the Collaboration Engineering. This paper analyzes a set of CUEM conducted on different interactive software systems. It proposes combinations of CUEM that provide more complete and comprehensive information about the usability of interactive software systems than those evaluation methods conducted independently

7-O-methylpunctatin, a novel homoisoflavonoid, inhibits phenotypic switch of human arteriolar smooth muscle cells

Remodeling of arterioles is a pivotal event in the manifestation of many inflammation-based cardio-vasculopathologies, such as hypertension. During these remodeling events, vascular smooth muscle cells (VSMCs) switch from a contractile to a synthetic phenotype. The latter is characterized by increased proliferation, migration, and invasion. Compounds with anti-inflammatory actions have been successful in attenuating this phenotypic switch. While the vast majority of studies investigating phenotypic modulation were undertaken in VSMCs isolated from large vessels, little is known about the effect of such compounds on phenotypic switch in VSMCs of microvessels (microVSMCs). We have recently characterized a novel homoisoflavonoid that we called 7-O-methylpunctatin (MP). In this study, we show that MP decreased FBS-induced cell proliferation, migration, invasion, and adhesion. MP also attenuated adhesion of THP-1 monocytes to microVSMCs, abolished FBS-induced expression of MMP-2, MMP-9, and NF-?B, as well as reduced activation of ERK1/2 and FAK. Furthermore, MP-treated VSMCs showed an increase in early (myocardin, SM-22?, SM-?) and mid-term (calponin and caldesmon) differentiation markers and a decrease in osteopontin, a protein highly expressed in synthetic VSMCs. MP also reduced transcription of cyclin D1, CDK4 but increased protein levels of p21 and p27. Taken together, these results corroborate an anti-inflammatory action of MP on human microVSMCs. Therefore, by inhibiting the synthetic phenotype of microVSMCs, MP may be a promising modulator for inflammation-induced arteriolar pathophysiology. - 2019 by the authors. Licensee MDPI, Basel, Switzerland.Funding: This work was supported by the American University of Beirut (Grant # MPP 320133 to A.E.), University of Petra (Grant #: 5/4/2019) to A.B., E.B., and A.E., and the National Council for Scientific Research (CNRS) to M.F.Scopu

Ziziphus nummularia attenuates the malignant phenotype of human pancreatic cancer cells: Role of ros

Pancreatic cancer (PC) is the fourth leading cause of all cancer-related deaths. Despite major improvements in treating PC, low survival rate remains a major challenge, indicating the need for alternative approaches, including herbal medicine. Among medicinal plants is Ziziphus nummu-laria (family Rhamnaceae), which is a thorny shrub rich in bioactive molecules. Leaves of Ziziphus nummularia have been used to treat many pathological conditions, including cancer. However, their effects on human PC are still unknown. Here, we show that the treatment of human pancreatic ductal adenocarcinoma cells (Capan-2) with Ziziphus nummularia ethanolic extract (ZNE) (100–300 µg/mL) attenuated cell proliferation in a time-and concentration-dependent manner. Pretreatment with N-acetylcysteine, an ROS scavenger, attenuated the anti-proliferative effect of ZNE. In addition, ZNE significantly decreased the migratory and invasive capacity of Capan-2 with a concomitant downregulation of integrin α2 and increased cell–cell aggregation. In addition, ZNE inhibited in ovo angiogenesis as well as reduced VEGF and nitric oxide levels. Furthermore, ZNE downregulated the ERK1/2 and NF-κB signaling pathways, which are known to drive tumorigenic and metastatic events. Taken together, our results suggest that ZNE can attenuate the malignant phenotype of Capan-2 by inhibiting hallmarks of PC. Our data also provide evidence for the potential anticancer effect of Ziziphus nummularia, which may represent a new resource of novel anticancer compounds, especially ones that can be utilized for the management of PC