This study examines the psychological distress of ghosting victims among early adults. Ghosting is a break-up strategy by suddenly disappearing that is popular among early adults because it is thought to cause several negative effects for the recipient. This study involved 160 early adults aged 18-25 years old who experienced ghosting in past one month by undergoing intense relationships through social media for at least 2 months. The result shows that early adults who were ghosted, experienced psychological distress on a moderate scale. Penelitian ini mengkaji mengenai gambaran psychological distress korban ghosting pada usia dewasa awal. Ghosting merupakan suatu strategi pemutusan hubungan dengan menghilang secara tiba-tiba yang sedang populer di kalangan usia dewasa muda dan dianggap menyebabkan beberapa efek negatif bagi penerimanya. Penelitian ini melibatkan 160 orang dewasa awal usia 18-25 tahun yang pernah mengalami ghosting dalam satu bulan terakhir dengan menjalani hubungan intens melalui media sosial selama minimal 2 bulan. Hasilnya menunjukkan bahwa individu dewasa awal korban ghosting mengalami psychological distress pada skala sedang.
The ecosystem service (ES) concept is becoming mainstream in policy and planning, but operational influence on practice is seldom reported. Here, we report the practitioners' perspectives on the practical implementation of the ES concept in 27 case studies. A standardised anonymous survey (n = 246), was used, focusing on the science-practice interaction process, perceived impact and expected use of the case study assessments. Operationalisation of the concept was shown to achieve a gradual change in practices: 13% of the case studies reported a change in action (e.g. management or policy change), and a further 40% anticipated that a change would result from the work. To a large extent the impact was attributed to a well conducted science-practice interaction process (>70%). The main reported advantages of the concept included: increased concept awareness and communication; enhanced participation and collaboration; production of comprehensive science-based knowledge; and production of spatially referenced knowledge for input to planning (91% indicated they had acquired new knowledge). The limitations were mostly case-specific and centred on methodology, data, and challenges with result implementation. The survey highlighted the crucial role of communication, participation and collaboration across different stakeholders, to implement the ES concept and enhance the democratisation of nature and landscape planning. (C) 2017 Published by Elsevier B.V.
Introduction: Fabry disease is a rare inherited X-linked disorder resulting from the absence or deficient activity of the α-galactosidase A enzyme. Objetive: To provide the first guideline on the best time to start enzyme replacement therapy to treat classic Fabry disease, based on the knowledge and experience of experts from ten Latin American countries: Argentina, Brazil, Colombia, Costa Rica, Chile, Ecuador, Mexico, Peru, Uruguay and Venezuela. Methods: The project coordinator designed a survey based on the criteria for starting the treatment which are established in different international guidelines published to date. This document was later sent to all the participants for its evaluation. Results: Fifty experts responded to the survey, whose criteria was divided into 5 sections according to specialty, and they arrived at a consensus. Discussion: The criteria for an early treatment were defined given the growing evidence of a better response and prognosis associated with it. Conclusion: We believe that the importance of this guideline relies on the participation of experts from ten Latin American countries. However, as it deals with a systemic disease whose physiopathological mechanisms and complications are still being described, some manifestations have not been included in the criteria, making it necessary to revise this guideline in order to report any changes that may arise in the future.
Next generation real-time applications demand big-data infrastructures to process huge and continuous data volumes under complex computational constraints. This type of application raises new issues on current big-data processing infrastructures. The first issue to be considered is that most of current infrastructures for big-data processing were defined for general purpose applications. Thus, they set aside real-time performance, which is in some cases an implicit requirement. A second important limitation is the lack of clear computational models that could be supported by current big-data frameworks. In an effort to reduce this gap, this article contributes along several lines. First, it provides a set of improvements to a computational model called distributed stream processing in order to formalize it as a real-time infrastructure. Second, it proposes some extensions to Storm, one of the most popular stream processors. These extensions are designed to gain an extra control over the resources used by the application in order to improve its predictability. Lastly, the article presents some empirical evidences on the performance that can be expected from this type of infrastructure. Model combining stream processing technology and real-time.Extensions to the Storm processor.Performance evaluation of the extension on a cluster.
