Miracle-dz/UniFAR-FTUs huggingface dataset:
Albuminuria as a Predictor of Cardiovascular Outcomes in Patients With Acute Myocardial Infarction

Background In patients with myocardial infarction (MI), reduced kidney function is recognized as an important predictor of poor prognosis, but the impact of albuminuria, a representative measure of kidney damage, has not been extensively evaluated. Methods and Results In the SCREAM (Stockholm Creatinine Measurements) project (2006–2012), we identified 2469 patients with incident MI with dipstick proteinuria measured within a year before MI (427 patients also had urine albumin to creatinine ratio [ACR] measured concurrently) and obtained estimates for ACR with multiple imputation in participants with data solely on dipstick proteinuria. We quantified the association of ACR with the post‐MI composite and individual outcomes of all‐cause mortality, cardiovascular mortality, recurrent MI, ischemic stroke, or heart failure using Cox models and then evaluated the improvement in C statistic. During a median follow‐up of 1.0 year after MI, 1607 participants (65.1%) developed the post‐MI composite outcome. Higher ACR levels were independently associated with all outcomes except for ischemic stroke. Per 8‐fold higher ACR (eg, 40 versus 5 mg/g), the hazard ratio of composite outcome was 1.21 (95% CI, 1.08–1.35). The addition of the ACR improved the C statistic of the post‐MI composite by 0.040 (95% CI, 0.030–0.051). Largely similar results were obtained regardless of diabetic status and when ACR or dipstick was separately analyzed without imputation. Conclusions In patients with MI, albuminuria was a potent predictor of subsequent outcomes, suggesting the importance of paying attention to the information on albuminuria, in addition to kidney function, in this high‐risk population.
Online bipartite matching with random arrivals: an approach based on strongly factor-revealing LPs

In a seminal paper, Karp, Vazirani, and Vazirani show that a simple ranking algorithm achieves a competitive ratio of 1-1/e for the online bipartite matching problem in the standard adversarial model, where the ratio of 1-1/e is also shown to be optimal. Their result also implies that in the random arrivals model defined by Goel and Mehta, where the online nodes arrive in a random order, a simple greedy algorithm achieves a competitive ratio of 1-1/e. In this paper, we study the ranking algorithm in the random arrivals model, and show that it has a competitive ratio of at least 0.696, beating the 1-1/e ≈ 0.632 barrier in the adversarial model. Our result also extends to the i.i. d. distribution model of Feldman et al., removing the assumption that the distribution is known. Our analysis has two main steps. First, we exploit certain dominance and monotonicity properties of the ranking algorithm to derive a family of factor-revealing linear programs (LPs). In particular, by symmetry of the ranking algorithm in the random arrivals model, we have the monotonicity property on both sides of the bipartite graph, giving good "strength" to the LPs. Second, to obtain a good lower bound on the optimal values of all these LPs and hence on the competitive ratio of the algorithm, we introduce the technique of strongly factor-revealing LPs. In particular, we derive a family of modified LPs with similar strength such that the optimal value of any single one of these new LPs is a lower bound on the competitive ratio of the algorithm. This enables us to leverage the power of computer LP solvers to solve for large instances of the new LPs to establish bounds that would otherwise be difficult to attain by human analysis.
More Than a Numbers Game: A Brief History of Accounting

Preface. List of Figure and Tables. 1. Double-Entry. 2. Railroads. 3.Taxes. 4. Costs. 5. Disclosure. 6. Standards. 7. Science. 8. Inflation. 9. Volatility. 10. Intangibles. 11. Debt. 12. Options. 13. Earnings. 14. SOX. 15. Epilogue. Notes. Bibliography. Index. About the Author.
[Effect of catechin on bone marrow cell cycle and gene expression of hematopoietic growth factors].

AIM To study the effect of catechin, the active component of Spatholobus suberectus Dunn, on bone marrow cell cycle and the expression of IL-6 and GM-CSF mRNA in spleen cells of normal and marrow-depressed mice in order to clarify the mechanism of hematopoietic-supportive effect of catechin. METHODS Flow cytometry was adopted to investigate the influence of catechin on bone marrow cell cycle in mice and the expression of IL-6 and GM-CSF mRNA induced by catechin in spleen cells was detected by RT-PCR technique simultaneously. RESULTS The cell proportion of normal and marrow-depressed mice in G0/G1 phase was reduced significantly, while that in S + G2/M phase increased significantly. Being induced by catechin, IL-6 mRNA and GM-CSF mRNA in spleen cells were markedly up-regulated. CONCLUSION Catechin (2 g x L(-1), intraperitoneally injected to mice daily immediately after irradiation for 7 consecutive days) was shown to promote the expression of IL-6 mRNA and GM-CSF mRNA in spleen cells of mice, through which it can accelerate bone marrow cells of normal mice into cell cycle and help those of marrow-depressed mice to get out of "G1-phase-block", enter into cell cycle and radically accelerate the proliferation and differentiation of hematopoietic stem cell/hematopoietic progenitor cell (HSC/HPC).
Nurses' attitudes towards older people and working with older patients: an explanatory model.

AIM To establish an explanatory model of registered nurses' attitudes towards older people and working with older patients. BACKGROUND Increasing demands for health-care from an ageing population will require a higher proportion of nurses who have positive attitudes towards older people and like working with older patients. METHOD A convenience sample of registered nurses (n = 579; 79.3% response rate) attending continuing professional education courses within a large university in London was surveyed from October to December 2011. RESULTS Registered nurses expressed positive attitudes towards older people and 89.7% reported positive attitudes towards working with older patients. The variables of self-ageing anxiety, attitudes towards health-care resource allocation, knowledge of ageing, ethnic group, job title, attitudes towards older patients and interaction between ethnic group and attitudes towards working with older patients explained 42.6% of the variance in attitudes towards older people. Factors, including attitudes towards older people, self-ageing anxiety, commitment to nursing, attitudes towards health-care resources allocation among older people and clinical specialty explained 16.7-34.3% of the variance in attitudes towards older patients. CONCLUSION The models identified several related factors that may help in the selection and management of nurses for caring older people. IMPLICATIONS FOR NURSING MANAGEMENT Our findings highlight the importance of investing in continuing education related to gerontological nursing and the ageing process so that there is a growing pool of registered nurses who wish to care for older patients.
Optimal power allocation in server farms

Server farms today consume more than 1.5% of the total electricity in the U.S. at a cost of nearly $4.5 billion. Given the rising cost of energy, many industries are now seeking solutions for how to best make use of their available power. An important question which arises in this context is how to distribute available power among servers in a server farm so as to get maximum performance. By giving more power to a server, one can get higher server frequency (speed). Hence it is commonly believed that, for a given power budget, performance can be maximized by operating servers at their highest power levels. However, it is also conceivable that one might prefer to run servers at their lowest power levels, which allows more servers to be turned on for a given power budget. To fully understand the effect of power allocation on performance in a server farm with a fixed power budget, we introduce a queueing theoretic model, which allows us to predict the optimal power allocation in a variety of scenarios. Results are verified via extensive experiments on an IBM BladeCenter. We find that the optimal power allocation varies for different scenarios. In particular, it is not always optimal to run servers at their maximum power levels. There are scenarios where it might be optimal to run servers at their lowest power levels or at some intermediate power levels. Our analysis shows that the optimal power allocation is non-obvious and depends on many factors such as the power-to-frequency relationship in the processors, the arrival rate of jobs, the maximum server frequency, the lowest attainable server frequency and the server farm configuration. Furthermore, our theoretical model allows us to explore more general settings than we can implement, including arbitrarily large server farms and different power-to-frequency curves. Importantly, we show that the optimal power allocation can significantly improve server farm performance, by a factor of typically 1.4 and as much as a factor of 5 in some cases.
In What Sense is the Kolmogorov-Sinai Entropy a Measure for Chaotic Behaviour?—Bridging the Gap Between Dynamical Systems Theory and Communication Theory

On an influential account, chaos is explained in terms of random behaviour; and random behaviour in turn is explained in terms of having positive Kolmogorov-Sinai entropy (KSE). Though intuitively plausible, the association of the KSE with random behaviour needs justification since the definition of the KSE does not make reference to any notion that is connected to randomness. I provide this justification for the case of Hamiltonian systems by proving that the KSE is equivalent to a generalized version of Shannon's communication-theoretic entropy under certain plausible assumptions. I then discuss consequences of this equivalence for randomness in chaotic dynamical systems. 1. Introduction2. Elements of dynamical systems theory3. Entropy in communication theory4. Entropy in dynamical systems theory5. Comparison with other accounts6. Product versus process randomness Introduction Elements of dynamical systems theory Entropy in communication theory Entropy in dynamical systems theory Comparison with other accounts Product versus process randomness
A World Without Women: The Christian Clerical Culture of Western Science

Why is it that Western science evolved as a thoroughly male-dominated enterprise? As philosopher Sandra Harding has noted, "women have been more systematically excluded from doing serious science than performing any other social activity except, perhaps, frontline warfare. " In A World Without Women, David F. Noble provides the first full-scale investigation of the origins and implications of the masculine culture of Western science and technology, and in the process offers some surprising revelations. Noble begins by showing that, contrary to the widely held notion that the culture of learning in the West has always excluded women--an assumption that rests largely upon the supposed legacy of ancient Greece--men did not thoroughly dominate intellectual life until the beginning of the second millennium of the Christian era. At this time science and the practices of higher learning became the exclusive province of the newly celibate Christian clergy, whose ascetic culture denied women a place in any scholarly enterprise. By the twelfth century, papal reform movements had all but swept away the material and ideological supports of future female participation in the world of learning; as never before, women were on the outside looking in. Noble further demonstrates that the clerical legacy of a world without women remained more or less intact through the Reformation, and permeated the emergant culture of science. A World Without Women finally points to a dread of women at the core of modern scientific and technological enterprise, as these disciplines work to deprive one-half of humanity of its role in production (as seen in the Industrial Revolution's male appropriation of labor) and reproduction as well (the age-old quest for an artificial womb). It also makes plain the hypocrisy of a community that can honor a female scientist with a bronze bust, as England's Royal Society did for Mary Somerville in the mid-nineteenth century, yet deny her entry to the very meeting hall in which it enjoyed pride of place. An important and often disturbing book, A World Without Women is essential reading for anyone concerned not only about the world of science, but about the world that science has made.
Need-Press and Expectation-Press Indices as Predictors of College Achievement

WHEN a college applicant chooses a particular educational institution it may be assumed he does so largely because he expects it will most adequately satisfy his personal needs. If he is accepted he may or may not find the directive influences or &dquo;press&dquo; of the college in keeping with his needs or his expectations of the institution. It has been hypothesized that the extent of agreement (congruence) between one’s internal forces (needs) and the external environmental forces (press) he encounters is positively related to his adaptation to that environment (Stern, 1960; Pace, 1961). This may be referred to as the need-press hypothesis. It may be, however, that it is not necessarily so much the congruence of his needs and the press as it is the congruence of what he expects (expectations) and the press he subsequently encounters that more strongly influences his adaptation. This may be referred to as an expectation-press hypothesis. These hypotheses involve abstract concepts, i.e., press, needs, and expectations, and the defining and measurement of their referents pose certain difficulties; Getzels and Guba (1957), for example, have effectively stressed the need for establishing distinctions, classifying such terms, and stating their interrelationships with behavior. Of the three terms, the press of collegiate environments has perhaps been most successfully defined and measured, by such instruments as the College Characteristics Index (CCI) (Pace
DEVELOPING STUDENTS LEARNING ATTRIBUTES THROUGH COLLABORATIVE LEARNING BASED ON FLIPPED CLASSROOM

Educators and education practitioners should be able to respond educational shift by modify paradigm of learning in the classroom. The problem that frequently emerge were the lack of conceptual and practical understanding, experience sharing among the students, as well as spirit of collaboration in learning. The purpose of the study was to build and develop students’ learning character through collaborative learning based on flipped class. The study was done in the framework of lesson study, using three steps (plan, do, and see). The technical steps included socialization, identifying problem, designing learning process, implementation, evaluation and reflection, and follow up. The result showed that collaborative learning based on flipped classroom was effective in developing the spirit of cooperation, honesty, discipline, and openness as it prioritized on the ability to cooperate with the others. There were some obstacles regarding time and class size in conducting lesson study. Keywords: Collaborative Learning, Flipped Classroom, Learning Attributes. References Agustian, A. G. (2007). Rahasia Sukses Membangun Kecerdasan Emosi Dan Spiritual: ESQ. Jakarta: Arga. Karlsson, G. , and Sverker J. (2016). “The Flipped Classroom : A Model for Active Student Learning. ” : 127–36. Markuszewska, Iwona, Minna, T. , and Josep V. S. (2018). “New Ways To Learn Geography – Challenges Of The 21 St Century. ” Quaestiones Geographicae 37(1): 37–45. Nofrion, and Bayu, W. (2018). “learning activities in higher order thinking skill ( hots ) oriented learning context. ” 3(2): 122–30. Ozdamli, Fezile, and Gulsum, A. (2016). “Educational Technology : Current Issues. ” 8(2): 98–105. Pavanelli, R. (2018). “The Flipped Classroom : A Mixed Methods Study of Academic Performance and Student Perception in EAP Writing Context 4205 Bonaventure Blvd.” 5(2): 16–26. Ragg, Mark, and James, P. (2017). “Competency-Based Blended Learning : Flipping Professional Practice Classes to Enhance Competence Development Mark Ragg Eastern Michigan University , United States of America James Piers Hope College , United States of America. ” IAFOR Journal of Education 5: 47–66. Stoltman, J. P. (2012). “Perspective on Geographical Education in the 21 St Century. ” : 17–24. Suharwati, Sri, I.I. , Sumarmi, and Ruja, I. N. (2016). “Pengaruh Model Pembelajaran Resource Based Learning terhadap Minat dan Hasil Belajar Geografi Siswa SMA. ” Jurnal Pendidikan 1(2): 74–79. Zubaidah, S. (2017). “Lesson Study Sebagai Salah Satu Model Pengembangan. ” Makalah Pendidikan dan Pelatihan Nasional dengan Tema Peningkatan Profesionalisme Guru melalui Kegiatan Lesson Study (April 2010). Zuchdi, D. (2009). Pendidikan Karakter. ed. UNY Press. Yogyakarta. Copyright (c) 2018 Geosfera Indonesia Journal and Department of Geography Education, University of Jember This work is licensed under a Creative Commons Attribution-Share A like 4.0 International License
Social capital theory and self-initiated expatriates' intention to repatriate : German expatriate academics in the United Kingdom

As the number of global expatriates continues to rise, the need to understand factors that influence their decisions to remain in their host countries or to return home increases. Self-Initiated Expatriates (SIEs) are defined as individuals who relocate across a national border, for an extended period of time, of their own volition, for work purposes. SIEs are the most prevalent expatriates globally (Finaccord, 2014) but are also some of the least understood. Expatriate academics (EAs) form a subgroup of this wider SIE group, and whilst being fairly representative, face their own unique challenges. Interpersonal links and social networks are influential in EA decisions to stay in or leave their host country, yet little is known about the exact function of networks, and how access to resources through networks influences SIE or EA decisions to remain in their host country or return to their home country. Drawing on social capital theory, this thesis develops a theoretical model that links various characteristics of EAs' ego-networks to EAs' intention to repatriate. Specifically, the model suggests that homophily, density, and hierarchy affect EAs' intention to repatriate and that EAs' national identity and career embeddedness moderate these effects. The developed hypotheses are tested using data collected from surveys among German academic expatriates in the UK Higher Education sector. In total, 213 responses were analysed using multiple regression analyses. The empirical results underline the importance of similarity of nationality between an EA and their network partners as an influencing factor on their intention to repatriate. The similarity in location of the EA and their network connections did not have any significant impact. The network density, and the EAs hierarchical position within their network also had a direct influence on intention to repatriate. The thesis contributes to current research on EAs and SIEs by providing a theory-based explanation of the effect of ego-network characteristics on EAs' intention to repatriate. It also contributes to the development of social capital theory by applying social capital logic in a novel context, clarifying the mechanisms underlying this logic and identifying boundary conditions of this logic in the context of SIE academics. The findings of this research are also relevant for HR practitioners in the UK Higher Education sector, by highlighting factors that may help or hinder the retention of key foreign academics.
Genetic inviability is a major driver of type III survivorship in experimental families of a highly fecund marine bivalve

The offspring of most highly fecund marine fish and shellfish suffer substantial mortality early in the life cycle, complicating prediction of recruitment and fisheries management. Early mortality has long been attributed to environmental factors and almost never to genetic sources. Previous work on a variety of marine bivalve species uncovered substantial genetic inviability among the offspring of inbred crosses, suggesting a large load of early‐acting deleterious recessive mutations. However, genetic inviability of randomly bred offspring has not been addressed. Here, genome‐wide surveys reveal widespread, genotype‐dependent mortality in randomly bred, full‐sib progenies of wild‐caught Pacific oysters (Crassostrea gigas). Using gene‐mapping methods, we infer that 11–19 detrimental alleles per family render 97.9–99.8% of progeny inviable. The variable genomic positions of viability loci among families imply a surprisingly large load of partially dominant or additive detrimental mutations in wild adult oysters. Although caution is required in interpreting the relevance of experimental results for natural field environments, we argue that the observed genetic inviability corresponds with type III survivorship, which is characteristic of both hatchery and field environments and that our results, therefore, suggest the need for additional experiments under the near‐natural conditions of mesocosms. We explore the population genetic implications of our results, calculating a detrimental mutation rate that is comparable to that estimated for conifers and other highly fecund perennial plants. Genetic inviability ought to be considered as a potential major source of low and variable recruitment in highly fecund marine animals.
Influence Maximization in Independent Cascade Networks Based on Activation Probability Computation

Based on the concepts of <italic>“word-of-mouth”</italic> effect and <italic>viral marketing</italic>, the diffusion of an innovation may be triggered starting from a set of initial users. Estimating the influence spread is a preliminary step to determine a suitable or even optimal set of initial users to reach a given goal. In this paper, we focus on a stochastic model called the independent cascade model and compare a few approaches to compute activation probabilities of nodes in a social network, i.e., the probability that a user adopts the innovation. First, we propose the <italic>path method</italic> that computes the exact value of the activation probabilities but has high complexity. Second, an approximated method, called <italic>SSS-Noself</italic>, is obtained by the modification of the existing <italic>SteadyStateSpread</italic> algorithm, based on fixed-point computation, to achieve better accuracy. Finally, an efficient approach, also based on fixed-point computation, is proposed to compute the probability that a node is activated through a path of minimal length from the seed set. This algorithm, called <italic>SSS-Bounded-Path</italic> algorithm, can provide a lower bound for the computation of activation probabilities. Furthermore, these proposed approaches are applied to the influence maximization problem combined with the <italic>SelectTop</italic> <inline-formula> <tex-math notation="LaTeX">$K$ </tex-math></inline-formula> algorithm, the <italic>RankedReplace</italic> algorithm, and the greedy algorithm.