130,499 research outputs found
Could Polyphenolic Food Intake Help in the Control of Type 2 Diabetes? A Narrative Review of the Last Evidence
No full textBackground: Diabetes is one of the largest global public health concerns, imposing a heavy global burden on public health as well as socio-economic development, and about 90% of adults with this condition have type 2 diabetes (T2D).
Introduction: Beyond the hereditary factor, there are several risk factors connected to the development of this syndrome; the lifestyles play, increasingly, a predominant role in the development of the metabolic complications related to T2D and a significant role in the onset of this syndrome is played from an unbalanced diet. Polyphenolic food is plant-based food including vegetables, fruits, whole grains, tea, coffee, and nuts. In recent years, there is growing evidence that plant-foods polyphenols, due to their biological properties, may be nutraceuticals and supplementary treatments for various aspects of T2D. Polyphenols may influence glycemia and T2D through hypoglycemic properties as reduction of insulin resistance, reduced fasting blood glucose, and glycosylated hemoglobin value. Based on several in vitro, animal models and some human studies, is has been detected that polyphenol-rich products modulate carbohydrate and lipid metabolism, attenuate hyperglycemia, dyslipidemia, and insulin resistance, improve adipose tissue metabolism, and alleviate oxidative stress and stress-sensitive signaling pathways and inflammatory processes.
Methods: This manuscript summarizes human clinical trials issued within the last 5 years linking dietary polyphenols to T2D, with a focus on polyphenolic-foods typical of the Mediterranean diet.
Results: Polyphenolic food can also prevent the development of long-term diabetes complications including cardiovascular disease, neuropathy, nephropathy, and retinopathy.
Conclusion: Further investigations as other human clinical studies are needed to obtain the best dose and duration of supplementation with polyphenolic food in T2D patients
Dynamic bi-level toll design approach for dynamic traffic networks
No full textThe subject of this thesis is the application of dynamic road pricing in dynamic networks.Both forms of dynamics represent the outstanding elements of this dissertation. Its objective is the formulation and testing of a design methodology for an optimized tolling system for road networks.Civil Engineering and Geoscience
MeSH term explosion and author rank improve expert recommendations
No full textInformation overload is an often-cited phenomenon that reduces the productivity, efficiency and efficacy of scientists. One challenge for scientists is to find appropriate collaborators in their research. The literature describes various solutions to the problem of expertise location, but most current approaches do not appear to be very suitable for expert recommendations in biomedical research. In this study, we present the development and initial evaluation of a vector space model-based algorithm to calculate researcher similarity using four inputs: 1) MeSH terms of publications; 2) MeSH terms and author rank; 3) exploded MeSH terms; and 4) exploded MeSH terms and author rank. We developed and evaluated the algorithm using a data set of 17,525 authors and their 22,542 papers. On average, our algorithms correctly predicted 2.5 of the top 5/10 coauthors of individual scientists. Exploded MeSH and author rank outperformed all other algorithms in accuracy, followed closely by MeSH and author rank. Our results show that the accuracy of MeSH term-based matching can be enhanced with other metadata such as author rank
The implementation of the ballast water management convention in the Adriatic Sea through States' cooperation. The contribution of environmental law and institutions
No full textThe Adriatic Sea, a semi-enclosed and vulnerable environment, deserves special attention regarding the risk of introducing Harmful Aquatic Organisms and Pathogens via ships' ballast water as new species findings occur at an alarming rate. This species introduction vector was addressed with the 2004 International Convention for the Control and Management of Ships' Ballast Water and Sediments, which entered into force in 2017. The efficient implementation of this convention calls for Adriatic States' cooperation on environmental specifics that have not been dealt with neither by national nor by international measures yet. Based on legal and institutional data gathered, and considering the regional maritime traffic and environmental specifics, this paper reveals that the integration of current environmental law commitments as well as a better dialogue between public institutions from shipping and environmental sectors may foster the implementation of ballast water management obligations through appropriate Adriatic States' cooperation
Analytics-based approach to the study of learning networks in digital education settings
No full textInvestigating howgroups communicate, build knowledge and expertise, reach consensus or collaboratively
solve complex problems, became one of the main foci of contemporary research in learning and
social sciences. Emerging models of communication and empowerment of networks as a form of social
organization further reshaped practice and pedagogy of online education, bringing research on learning
networks into the mainstream of educational and social science research. In such conditions, massive
open online courses (MOOCs) emerged as one of the promising approaches to facilitating learning
in networked settings and shifting education towards more open and lifelong learning. Nevertheless,
this most recent educational turn highlights the importance of understanding social and technological
(i.e., material) factors as mutually interdependent, challenging the existing forms of pedagogy and
practice of assessment for learning in online environments.
On the other hand, the main focus of the contemporary research on networked learning is primarily
oriented towards retrospective analysis of learning networks and informing design of future
tasks and recommendations for learning. Although providing invaluable insights for understanding
learning in networked settings, the nature of commonly applied approaches does not necessarily allow
for providing means for understanding learning as it unfolds. In that sense, learning analytics, as
a multidisciplinary research field, presents a complementary research strand to the contemporary research
on learning networks. Providing theory-driven and analytics-based methods that would allow
for comprehensive assessment of complex learning skills, learning analytics positions itself either as
the end point or a part of the pedagogy of learning in networked settings.
The thesis contributes to the development of learning analytics-based research in studying learning
networks that emerge fromthe context of learning with MOOCs. Being rooted in the well-established
evidence-centered design assessment framework, the thesis develops a conceptual analytics-based
model that provides means for understanding learning networks from both individual and network
levels. The proposed model provides a theory-driven conceptualization of the main constructs, along
with their mutual relationships, necessary for studying learning networks. Specifically, to provide
comprehensive understanding of learning networks, it is necessary to account for structure of learner
interactions, discourse generated in the learning process, and dynamics of structural and discourse
properties. These three elements – structure, discourse, and dynamics – should be observed as mutually
dependent, taking into account learners’ personal interests, motivation, behavior, and contextual
factors that determine the environment in which a specific learning network develops. The thesis also
offers an operationalization of the constructs identified in the model with the aim at providing learning analytics-methods for the implementation of assessment for learning. In so doing, I offered a redefinition
of the existing educational framework that defines learner engagement in order to account
for specific aspects of learning networks emerging from learning with MOOCs. Finally, throughout
the empirical work presented in five peer-reviewed studies, the thesis provides an evaluation of the
proposed model and introduces novel learning analytics methods that provide different perspectives
for understanding learning networks. The empirical work also provides significant theoretical and
methodological contributions for research and practice in the context of learning networks emerging
from learning with MOOCs
Going Beyond Counting First Authors in Author Co-citation Analysis
No full textThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
"Closing the R&D Gap, Evaluating the Sources of R&D Spending"
No full textBoth spending and tax policies have been implemented in the United States with the goal of stimulating private sector research and development (R&D). Karier questions whether current R&D policy, especially the research and experimentation tax credit, can contribute to closing the gap between nondefense expenditures on R&D in the United States and such expenditures in other countries, such as Japan and Germany. He also explores possible changes to our current R&D policy to make it more effective.
Dispelling the Myths Behind First-author Citation Counts
No full textWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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