3,968 research outputs found
The case of online trust
“The original publication is available at www.springerlink.com”. Copyright SpringerThis paper contributes to the debate on online trust addressing the problem of whether an online environment satisfies the necessary conditions for the emergence of trust. The paper defends the thesis that online environments can foster trust, and it does so in three steps. Firstly, the arguments proposed by the detractors of online trust are presented and analysed. Secondly, it is argued that trust can emerge in uncertain and risky environments and that it is possible to trust online identities when they are diachronic and sufficient data are available to assess their reputation. Finally, a definition of trust as a second-order property of first-order relation is endorsed in order to present a new definition of online trust. According to such a definition, online trust is an occurrence of trust that specifically qualifies the relation of communication ongoing among individuals in digital environments. On the basis of this analysis, the paper concludes by arguing that online trust promotes the emergence of social behaviours rewarding honest and transparent communications.Peer reviewe
Identification of subgroups of early breast cancer patients at high risk of nonadherence to adjuvant hormone therapy: results of an italian survey.
The aim of this study was the identification of subgroups of patients at higher risk of nonadherence to adjuvant
hormone therapy for breast cancer. Using recursive partitioning and amalgamation (RECPAM) analysis, the
highest risk was observed in the group of unmarried, employed women, or housewives. This result might be
functional in designing tailored intervention studies aimed at improvement of adherence.
Background: Adherence to adjuvant endocrine therapy (HT) is suboptimal among breast cancer patients. A high rate
of nonadherence might explain differences in survival between clinical trial and clinical practice. Tailored interventions
aimed at improving adherence can only be implemented if subgroups of patients at higher risk of poor adherence are
identified. Because no data are available for Italy, we undertook a large survey on adherence among women taking
adjuvant HT for breast cancer. Patients and Methods: Patients were recruited from 10 cancer clinics in central Italy.
All patients taking HT for at least 1 year were invited, during one of their follow-up visit, to fill a confidential questionnaire.
The association of sociodemographic and clinical characteristics of participants with adherence was
assessed using logistic regression. The RECPAM method was used to evaluate interactions among variables and to
identify subgroups of patients at different risk of nonadherence. Results: A total of 939 patients joined the study and
18.6% of them were classified as nonadherers. Among possible predictors, only age, working status, and switching
from tamoxifen to an aromatase inhibitor were predictive of nonadherence in multivariate analysis. RECPAM analysis
led to the identification of 4 classes of patients with a different likelihood of nonadherence to therapy, the lowest being
observed in retired women with a low level of education, the highest in the group of unmarried, employed women, or
housewives. Conclusion: The identification of these subgroups of “real life” patients with a high prevalence of
nonadherers might be functional in designing intervention studies aimed at improving adherenc
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The role of smart sensor networks for voltage monitoring in smart grids
The large-scale deployment of the Smart Grid paradigm will support the evolution of conventional electrical power systems toward active, flexible and self-healing web energy networks composed of distributed and cooperative energy resources. In a Smart Grid platform, distributed voltage monitoring is one of the main issues to address. In this field, the application of traditional hierarchical monitoring paradigms has some disadvantages that could hinder their application in Smart Grids where the constant growth of grid complexity and the need for massive pervasion of Distribution Generation Systems (DGS) require more scalable, more flexible control and regulation paradigms. To try to overcome these challenges, this paper proposes the concept of a decentralized non-hierarchal voltage monitoring architecture based on intelligent and cooperative smart entities. These devices employ traditional sensors to acquire local bus variables and mutually coupled oscillators to assess the main variables describing the global grid state
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Computational Intelligence Applications in Smart Grids: Enabling Methodologies for Proactive and Self Organizing Power Systems
This book considers the emerging technologies and methodologies of the application of computational intelligence to smart grids.
From a conceptual point of view, the smart grid is the convergence of information and operational technologies applied to the electric grid, allowing sustainable options to customers and improved levels of security. Smart grid technologies include advanced sensing systems, two-way high-speed communications, monitoring and enterprise analysis software, and related services used to obtain location-specific and real-time actionable data for the provision of enhanced services for both system operators (i.e. distribution automation, asset management, advanced metering infrastructure) and end-users (i.e. demand side management, demand response).
In this context, a crucial issue is how to support the evolution of existing electrical grids from static hierarchal systems to self-organizing, highly scalable and pervasive networks. Modern trends are oriented toward the employment of computational intelligence techniques for deploying advanced control, protection and monitoring architectures that move away from the older centralized paradigm to systems distributed across the field with an increasing pervasion of intelligence devices. The large-scale deployment of computational intelligence technologies in smart grids could lead to a more efficient tasks distribution amongst energy resources and, consequently, to a sensible improvement of the electrical grid flexibility
A new method to energy saving in a micro grid
Optimization of energy production systems is a relevant issue that must be
considered in order to follow the fossil fuels consumption reduction policies and CO2 emission
regulation. Increasing electricity production from renewable resources (e.g., photovoltaic
systems and wind farms) is desirable but its unpredictability is a cause of problems for the
main grid stability. A system with multiple energy sources represents an efficient solution,
by realizing an interface among renewable energy sources, energy storage systems, and
conventional power generators. Direct consequences of multi-energy systems are a wider
energy flexibility and benefits for the electric grid, the purpose of this paper is to propose
the best technology combination for electricity generation from a mix of renewable energy
resources to satisfy the electrical needs. The paper identifies the optimal off-grid option
and compares this with conventional grid extension, through the use of HOMER software.
The solution obtained shows that a hybrid combination of renewable energy generators at
an off-grid location can be a cost-effective alternative to grid extension and it is sustainable,
techno-economically viable, and environmentally sound. The results show how this innovative
energetic approach can provide a cost reduction in power supply and energy fees of 40%
and 25%, respectively, and CO2 emission decrease attained around 18%. Furthermore, the
multi-energy system taken as the case study has been optimized through the utilization of
three different type of energy storage (Pb-Ac batteries, flywheels, and micro—Compressed Air
Energy Storage (C.A.E.S.)
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An Overview of Campus Climate: Dimensions of Diversity in Higher Education
Higher education scholars have increasingly studied campus climate, a term used to denote the experiences of diverse students, faculty, and staff. This article inventories the literature on the topic, including definitions of campus climate, approaches to assessing climate, and future directions for climate inquiry.Educatio
Mic Check? Mic Check! Amplifying Our Voices
Content Warning: discrimination, suicidal ideation, violence
When I write about mental illness, I use the terms: disability, identity, and relationship. However, no word captures what mental illness means to me. Mental illness is somehow both a part of me and a separate, intangible entity. Every day is an exhausting struggle to live with and understand it, and during my first year of graduate school, I experienced covert ableism. This harm caused a long and tedious recovery process on top of ongoing unlearning and healing. Through recovery, I adopted the practice of “embracing the whole” of emotions, feelings, symptoms, and triggers. I questioned the concept of “professionalism” emphasized in my assistantship, which often included dehumanizing emotions. However, I will not expend additional emotional labor to educate those who committed ableist actions. Instead, I will write in depth about my mental illness experiences to relate to folx who have a mental illness. Through this article, I hope that folx with mental illness can empower themselves to embrace the whole of their emotions and the authenticity of their experiences, honoring their own bravery and vulnerability
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Enabling technologies and methodologies for knowledge discovery and data mining in smart grids
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