Probing doubly charged Higgs in e+e−e^+ e^- Colliders in 3-3-1 Model

The SU(3)_L\otimesU(1)_N electroweak model predicts new Higgs bosons beyond the one of the standard model. In this work we investigate the signature and production of doubly charged Higgs bosons in the $e^-e^+$ International Linear Collider and in the CERN Linear Collider. We compute the branching ratios for the doubly charged gauge bosons of the model.Comment: 17 pages, 12 figure

Microswitches with Sputtered Au, AuPd,Au-on-AuPt, and AuPtCu Alloy Electric Contacts

This paper is the first to report on a new analytic model for predicting microcontact resistance and the design, fabrication, and testing of microelectromechanical systems (MEMS) metal contact switches with sputtered bimetallic (i.e., gold (Au)-on-Au-platinum (Pt), (Au-on-Au-(6.3at%)Pt)), binary alloy (i.e., Au-palladium (Pd), (Au-(3.7at%)Pd)), and ternary alloy (i.e., Au-Pt-copper (Cu), (Au-(5.0at%)Pt-(0.5at%)Cu)) electric contacts. The microswitches with bimetallic and binary alloy contacts resulted in contact resistance values between 1-2Omega. Preliminary reliability testing indicates a 3times increase in switching lifetime when compared to microswitches with sputtered Au electric contacts. The ternary alloy exhibited approximately a 6times increase in switch lifetime with contact resistance values ranging from approximately 0.2-1.8Omeg

Micro-Switches with Sputtered Au, AuPd, Au-on-AuPt, and AuPtCu Alloy Electric Contacts

This work is the first to report on a new analytic model for predicting micro-contact resistance and the design, fabrication, and testing of microelectromechanical systems (MEMS) metal contact switches with sputtered bi-metallic (i.e. gold (Au)-on-Au-platinum (Pt), (Au-on-Au-(6%)Pt)), binary alloy (i.e. Au-palladium (Pd), (Au-(2%)Pd)), and tertiary alloy (i.e. Au-Pt-copper (Cu), (Au-(5%)Pt-(0.5%)Cu)) electric contacts. The micro-switches with bi-metallic and binary alloy contacts resulted in contact resistance between 1-2 /spl Omega/ and, when compared to micro-switches with sputtered Au electric contacts, exhibited a 3.3 and 2.6 times increase in switching lifetime, respectively. The tertiary alloy exhibited a 6.5 times increase in switch lifetime with contact resistance ranging from 0.2-1.8 /spl Omega/

Quality of process modeling using BPMN: a model-driven approach

Dissertação para obtenção do Grau de Doutor em Engenharia InformáticaContext: The BPMN 2.0 specification contains the rules regarding the correct usage of the language’s constructs. Practitioners have also proposed best-practices for producing better BPMN models. However, those rules are expressed in natural language, yielding sometimes ambiguous interpretation, and therefore, flaws in produced BPMN models. Objective: Ensuring the correctness of BPMN models is critical for the automation of processes. Hence, errors in the BPMN models specification should be detected and corrected at design time, since faults detected at latter stages of processes’ development can be more costly and hard to correct. So, we need to assess the quality of BPMN models in a rigorous and systematic way. Method: We follow a model-driven approach for formalization and empirical validation of BPMN well-formedness rules and BPMN measures for enhancing the quality of BPMN models. Results: The rule mining of BPMN specification, as well as recently published BPMN works, allowed the gathering of more than a hundred of BPMN well-formedness and best-practices rules. Furthermore, we derived a set of BPMN measures aiming to provide information to process modelers regarding the correctness of BPMN models. Both BPMN rules, as well as BPMN measures were empirically validated through samples of BPMN models. Limitations: This work does not cover control-flow formal properties in BPMN models, since they were extensively discussed in other process modeling research works. Conclusion: We intend to contribute for improving BPMN modeling tools, through the formalization of well-formedness rules and BPMN measures to be incorporated in those tools, in order to enhance the quality of process modeling outcomes

Epigallocatechin-3-Gallate (EGCG) Suppresses Pancreatic Cancer Cell Growth, Invasion, and Migration partly through the Inhibition of Akt Pathway and Epithelial-Mesenchymal Transition: Enhanced Efficacy when Combined with Gemcitabine.

Most pancreatic cancers are usually diagnosed at an advanced stage when they have already metastasized. Epigallocatechin-3-gallate (EGCG), a major polyphenolic constituent of green tea, has been shown to reduce pancreatic cancer growth, but its effect on metastasis remains elusive. This study evaluated the capacity of EGCG to inhibit pancreatic cancer cell migration and invasion and the underlying mechanisms. EGCG reduced pancreatic cancer cell growth, migration, and invasion in vitro and in vivo. EGCG prevented "Cadherin switch" and decreased the expression level of TCF8/ZEB1, β-Catenin, and Vimentin. Mechanistically, EGCG inhibited the Akt pathway in a time-dependent manner, by suppressing IGFR phosphorylation and inducing Akt degradation. Co-treatment with catalase or N-Acetyl-L-cysteine did not abrogate EGCG's effect on the Akt pathway or cell growth. Moreover, EGCG synergized with gemcitabine to suppress pancreatic cancer cell growth, migration, and invasion, through modulating epithelial-mesenchymal transition markers and inhibiting Akt pathway. In summary, EGCG may prove beneficial to improve gemcitabine sensitivity in inhibiting pancreatic cancer cell migration and invasion, to some extent through the inhibition of Akt pathway and epithelial-mesenchymal transition

A data-driven approach to improve online consumer subscriptions by combining data visualization and machine learning methods

Effective online consumer research helps companies on defining a successful strategy to increase user loyalty and shape brand engagement. Digital innovation introduced a dramatic change in businesses, particularly in the online news industry. Content consumers have a wide offer across different channels which increases the digital challenge for online news media companies to retain their readers and convert them into online subscribers. Furthermore, digital news publishers often strive to balance revenue sources in online business models. Thus, this study fills a gap in the literature on media consumer research by proposing a data-driven approach that combines two machine learning models to allow managers dynamically improve their marketing and editorial strategies. Firstly, the authors present an online user profiling to identify consumer segments based on the interplay between several engagement’ variables substantiated in the literature research. Second, as few studies have explored the factors influencing users’ intention to pay for such services, the XGBoost machine learning algorithm identifies the predictors of consumer's willingness to pay. Third, a dashboard presents the key performance indicators across the audience funnel. Thus, practical implications and business suggestions are presented in a two-fold strategy to maximize revenue from digital subscriptions and advertising. Findings provide new insights into an engagement approach and the relation to acquire a digital subscription in online content platforms. We believe that the provided recommendations are potentially useful to help marketing and editorial teams to manage their customer engagement process across the funnel in a more efficient way.info:eu-repo/semantics/publishedVersio

Applying knowledge management strategies to economic development in sub-Saharan Africa

Sustainability looks to achieve best outcomes for human and natural environments both now and in the indefinite future. It relates to the continuity of economic, social, institutional and environmental aspects of human society, as well as the non-human environment. This paper examines economic development as one aspect of sustainability, with a focus on knowledge management as an economic development strategy. Using Grey’s categories of knowledge management, the authors address sustainable economic development in the context of sub-Saharan Africa. Production capability is no longer completely dependent on capital and equipment; information and knowledge assets are increasingly important. In this information economy, success comes from harnessing the information and knowledge of a community. Such “indigenous knowledge,” local and often tacit, exists in every community, every region and every country. This knowledge is useful in identifying new entrepreneurial opportunities, as well as for sustaining and advancing local businesses. Sub-Saharan Africa provides an excellent case study. No other region of the world is in more dire need of development. The 700 million people in this area face tremendous challenges, including the world’s highest incidence of HIV/AIDS, deep poverty, unemployment, political instability, and a host of related problems. Key factors for using knowledge management as an economic development strategy in the region will include ICT (Information and Communication Technologies) literacy; uncovering and developing local intellectual assets; capturing tacit knowledge; internal and external knowledge sharing; and managing political, social and technological barriers. Other specific recommendations include promoting ICT literacy through training programs; leveraging internet and email technologies for community building; investing financial resources in R & D; and developing metrics for outcome assessment.Keywords: Knowledge management, economic development, sub-Saharan Africa

The Food and Drug Administration\u27s Evolving Regulation of Press Releases: Limits and Challenges

The Food and Drug Administration (FDA) has developed an informal framework for regulating press releases by drug and medical device companies. FDA asserted jurisdiction over press releases based on its authority over labeling and advertising, and over the past 20 years, the agency has both broadened and scaled back its claims to authority over press statements. Despite a somewhat predictable framework for anticipating how FDA regulates press materials, the agency\u27s approach appears to be in flux. FDA will not tolerate false or misleading statements in press materials, but there are legal and practical limits to its regulation in this area. The agency has had to adjust its approach to account for First Amendment concerns and resource limitations, which has led FDA to cooperate with the Securities and Exchange Commission (SEC), and take more creative responses to allegedly violative press materials. This article discusses how FDA has regulated press materials in the past, and how recent developments may signal new directions in the agency\u27s regulatory approach. The article proposes a framework for evaluating whether FDA might assert jurisdiction, and what the rules are if it does. The article considers the legal theories behind FDA\u27s approach and the implications for manufacturers

A Sweeping Process Control Problem Subject To Mixed Constraints

In this study, we investigate optimal control problems that involve sweeping processes with a drift term and mixed inequality constraints. Our goal is to establish necessary optimality conditions for these problems. We address the challenges that arise due to the combination of sweeping processes and inequality mixed constraints in two contexts: regular and non-regular. This requires working with different types of multipliers, such as finite positive Radon measures for the sweeping term and integrable functions for regular mixed constraints. For non-regular mixed constraints, the multipliers correspond to purely finitely additive set functions.Comment: 6 page