384 research outputs found
The Story of Sor Juana Ines de la Cruz
No full textabstract: The story of Sor Juana Ines de la Cruz is one of a woman who defied the odds of her time. Sor Juana was a nun born in the 1600's in Mexico. From an early start, she had an endless passion for knowledge and always strove to learn as much as she could. She went on to become a nun at the Convent of Santa Paula and used her intellect to advocate for women's rights. Though met with opposition, she wrote many poems, letters, and even plays which included her strong push for women's equality. However, the name Sor Juana Ines de la Cruz is almost never mentioned in popular feminist discourse, despite Sor Juana being credited as one of the first feminist authors. This paper works to not only tell the story of Sor Juana Ines de la Cruz in detail, but also works to answer the question, "Why do people not know about Sor Juana". By diving into the origins of the Feminist movement in the United States, the dark underbelly of Feminism is uncovered. Primarily, the topic of how racism in feminism has plague the civil rights movement, what damage has been done to people of color because of feminism's history, and how does that pertain to modern day feminism and Sor Juana. By telling her story through both written and visual aids, the voice of Sor Juana Ines de la Cruz is no longer silenced but free to tell her tale and move a generation
Neutron diffractometer INES for quantitative phase analysis of archaeological objects
No full textApplied Science
Rad na ulozi Eme u predstavi Kontrakcije
No full textTekst Kontrakcije britanskog autora Mike Bartletta, naslov je diplomske ispitne predstave studentice Ines Zmazek pod mentorstvom izv. prof. Roberta Raponje i sumentorice Katice Šubarić na Umjetničkoj akademiji u Osijeku, na Odsjeku za kazališnu umjetnost, smjer gluma i lutkarstvo. U diplomskoj predstavi sudjeluje i studentica Ivana Vukićević koja igra ulogu menadžerice. U ovom pismenom radu studentica opisuje proces rada na predstavi od prve čitaće probe do diplomskog ispita. Također, govori o tome kakvo je iskustvo za nju bilo studiranje glume, te s kojim se problemima susretala tijekom rada na ulozi Eme. Donosi zaključak da joj je uloga Eme bila jedan od najvećih izaozva tijekom njenog studiranja, te da joj je taj zadatak pomogao da se još više kreativno razvije i sazrije kao glumica i osoba.The text Contractions of the British author Mike Bartlett, is the title of the graduate exam presentation of the student Ines Zmazek under the mentorship of prof. Roberta Raponja and assistant Katica Šubarić at the Academy of Art in Osijek, at the theater department, acting and puppetry. The graduate show also includes student Ivana Vukićević who plays the role of a manager. In this written work the student describes the work process on the play from the first reading test to the graduate exam. She also talks about her experience of her acting as an actress and the problems she encountered during her work on roll Ema. Shee concludes that her role as Eme was one of the greatest achievements during her studies, and that her task helped her develop more and more creatively as an actress and a person
Rad na ulozi Eme u predstavi Kontrakcije
No full textTekst Kontrakcije britanskog autora Mike Bartletta, naslov je diplomske ispitne predstave studentice Ines Zmazek pod mentorstvom izv. prof. Roberta Raponje i sumentorice Katice Šubarić na Umjetničkoj akademiji u Osijeku, na Odsjeku za kazališnu umjetnost, smjer gluma i lutkarstvo. U diplomskoj predstavi sudjeluje i studentica Ivana Vukićević koja igra ulogu menadžerice. U ovom pismenom radu studentica opisuje proces rada na predstavi od prve čitaće probe do diplomskog ispita. Također, govori o tome kakvo je iskustvo za nju bilo studiranje glume, te s kojim se problemima susretala tijekom rada na ulozi Eme. Donosi zaključak da joj je uloga Eme bila jedan od najvećih izaozva tijekom njenog studiranja, te da joj je taj zadatak pomogao da se još više kreativno razvije i sazrije kao glumica i osoba.The text Contractions of the British author Mike Bartlett, is the title of the graduate exam presentation of the student Ines Zmazek under the mentorship of prof. Roberta Raponja and assistant Katica Šubarić at the Academy of Art in Osijek, at the theater department, acting and puppetry. The graduate show also includes student Ivana Vukićević who plays the role of a manager. In this written work the student describes the work process on the play from the first reading test to the graduate exam. She also talks about her experience of her acting as an actress and the problems she encountered during her work on roll Ema. Shee concludes that her role as Eme was one of the greatest achievements during her studies, and that her task helped her develop more and more creatively as an actress and a person
Random regression models for the estimation of genetic and environmental covariance functions for growth traits in Santa Ines sheep.
No full textAbstract: Polynomial functions of different orders were used to model random effects associated with weight of Santa Ines sheep from birth to 196 days. Fixed effects included in the models were contemporary groups, age of ewe at lambing, and fourth-order Legendre polynomials for age to represent the average growth curve. In the random part, functions of different orders were included to model variances associated with direct additive and maternal genetic effects and with permanent environmental effects of the animal and mother. Residual variance was fitted by a sixth-order ordinary polynomial for age. The higher the order of the functions, the better the model fit the data. According to the Akaike information criterion and likelihood ratio test, a continuous function of order, five, five, seven, and three for direct additive genetic, maternal genetic, animal permanent environmental, and maternal permanent environmental effects (k = 5573), respectively, was sufficient to model changes in (co)variances with age. However, a more parsimonious model of order three, three, five, and three (k = 3353) was suggested based on Schwarz's Bayesian information criterion for the same effects. Since it was a more flexible model, model k = 5573 provided inconsistent genetic parameter estimates when compared to the biologically expected result. Predicted breeding values obtained with models k = 3353 and k = 5573 differed, especially at young ages. Model k = 3353 adequately fit changes in variances and covariances with time, and may be used to describe changes in variances with age in the Santa Ines sheep studied
High-intensity interval training is feasible, credible and clinically effective in the early subacute stroke stage in the low-income country of Benin
No full textThe author(s) reported that there is no funding associated with the work featured in this article
Prevention: From the cradle to the grave and beyond
No full textPresent cardiac prevention mainly focuses on risk reduction later in life, and focuses also mainly on reducing risk factors for coronary heart disease. However, multiple studies have gathered evidence that the development risk of cardiovascular disease starts early in life and that even preconceptional influences play an important role in lifetime risk. Therefore, the importance of well-timed prevention strategies to reduce cardiovascular disease is well established. In this article, we discuss different risk factors for future cardiac disease, and how we can respond to lesser known cardiac risk factors in the different stages of life.The author(s) received no financial support for the research,
authorship and/or publication of this article
Twisted mass QCD thermodynamics: first results on apeNEXT
No full textCopyright owned by the author(s) under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike Licence.Ernst-Michael Ilgenfritz, Michael Müller-Preussker and Andre Sternbeck, Karl Jansen and Ines Wetzorke, Maria Paola Lombardo, Owe Philipsenhttp://pos.sissa.it/cgi-bin/reader/conf.cgi?confid=3
Travel demand matrix estimation methods integrating the full richness of observed traffic flow data from congested networks
No full textIn strategic transport models, road travel demand matrices are usually estimated using estimation methods that fuse prior or synthetic travel demand matrices with flow data observed on individual roads (‘links’) in the network. On the one hand, ever more data on flows, speeds and/or densities on link level is available, driven by technological advances (e.g. PnD’s, smartphones, IoT), trends in transport policy towards smarter usage instead of expansion of the network and the smart mobility concepts arising from them. On the other hand, the urgency of robust and sound estimation procedures is triggered by rising congestion levels on these networks that are at an all-time high.In this paper we address the known difficulties when estimating travel demand using link flows observed on a network with high levels of congestion. Such a network incorporates at least several active bottlenecks, which influence flow values both upstream (queues will form) and downstream (flow is metered). This implies that, on such a network, observed link flow values may represent either 1) the unconstrained travel demand for that link, 2) a proportion of the capacity of a set of upstream links, 3) the capacity of the normative (in terms of capacity deficit) downstream link or 4) a combination of these quantities. Which quantity each observed link flow represents depends on the specific traffic conditions in the network. Note that in practice a very large portion of observed flows is affected by flow metering (2) whereas only a small portion is unaffected (1) or affected by queues (3 or 4).Demand matrix estimation methods use a traffic assignment model to assess the relationship between travel demand and link flow in intercept information. If the assignment model that provides the intercept information does not strictly adhere to link capacity constraints, as with static traffic assignment models, flow metering effects of bottlenecks (2) are not taken into account and all traffic is considered unaffected (1), thereby forcing incorrect assumptions upon the estimation. Therefore, matrix estimation methods using these models should only be applied on observed flows values that are unaffected (1), rendering them mostly useless on networks with high congestion levels. Note that by nature these assignment models should actually not be applied on study areas with congestion altogether.Current practice to use observed flows affected by congestion (2, 3 or 4) is to derive unconstrained link demand values from the observed flow values, for example using the ‘Tonenmethodiek’ (used in the Dutch LMS/NRM models), or similar techniques that shift observed flows to upstream unconstrained links. Then, instead of the actual observed flows, these post-processed link demand values are used during matrix estimation. As such, these methods exhibit poor tractability and robustness and do not integrate any information from the assignment model about the composition of routes on the observed links.This paper describes and compares three novel demand matrix estimation methods for large scale strategic congested transport models that use assignment models that strictly adhere to link capacity constraints, allowing them to explicitly consider the conditions under which link flows are observed. It compares these methods to the current practice and gives practical insights from applications, thereby demonstrating that these methods allow for usage of (big) data sources such as floating car data, congestion patterns and (route) travel time observations. Using these novel approaches, the need to post-process synthetic link demands is taken away, thereby increasing tractability and robustness of the matrix estimation methods and allowing for use of observed congestion patterns as additional input. Furthermore, these methods more efficiently reveal inconsistencies between model link capacities and observed congestion patterns and inconsistencies between count values, allowing the modeler to correct the model network and other matrix estimation input.Authors continue research on the topic, the next goal being to extent the methods to support estimation of OD demand covering multiple time period(s), which should eventually lead to a method that supports 24 hour estimation.Transport and Plannin
Random regression models for the estimation of genetic and environmental covariance functions for growth traits in Santa Ines sheep
No full textPolynomial functions of different orders were used to model random effects associated with weight of Santa Ines sheep from birth to 196 days. Fixed effects included in the models were contemporary groups, age of ewe at lambing, and fourth-order Legendre polynomials for age to represent the average growth curve. In the random part, functions of different orders were included to model
variances associated with direct additive and maternal genetic effects and with permanent environmental effects of the animal and mother. Residual variance was fitted by a sixth-order ordinary polynomial for age. The higher the order of the functions, the better the model fit the
data. According to the Akaike information criterion and likelihood ratio test, a continuous function of order, five, five, seven, and three for direct additive genetic, maternal genetic, animal permanent environmental, and maternal permanent environmental effects (k = 5573), respectively, was sufficient to model changes in (co)variances with age. However, a more parsimonious model of order three, three, five, and three (k = 3353) was suggested based on Schwarz’s Bayesian information criterion for the same effects. Since it was a more flexible model, model k = 5573
provided inconsistent genetic parameter estimates when compared to the biologically expected result. Predicted breeding values obtained with models k = 3353 and k = 5573 differed, especially at young ages. Model k = 3353 adequately fit changes in variances and covariances with time, and may be used to describe changes in variances with age in the Santa Ines sheep studie
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