Miracle-dz/UniFAR-FTUs huggingface dataset:
The effect of socio-economic status and food availability on first birth interval in a pre-industrial human population

Individual variation in nutritional status has direct implications for fitness and thus is crucial in shaping patterns of life-history variation. Nevertheless, it is difficult to measure in natural populations, especially in humans. Here, we used longitudinal data on individual life-histories and annual crop yield variation collected from pre-industrial Finnish populations experiencing natural mortality and fertility to test the validity of first birth interval (FBI; time between marriage and first birth) as a surrogate measure of nutritional status. We evaluated whether women with different socio-economic groups differ in length of FBI, whether women of poorer socio-economic status and experiencing lower crop yields conceive slower following marriage, and whether shorter FBI is associated with higher lifetime breeding success. We found that poorer women had longer FBI and reduced probability of giving birth in months with low food availability, while the FBI of richer women was not affected by variation in food availability. Women with shorter FBI achieved higher lifetime breeding success and a faster reproductive rate. This is, to our knowledge, the first study to show a direct relationship between environmental conditions and speed of childbirth following marriage, highlighting the value of FBI as an indicator of nutritional status when direct data are lacking.
Commentary on Sharek: adverse events and errors-important to differentiate and difficult to measure.

The paper by Sharek and colleagues in this issue of Health Services Research describes some of the characteristics of a method of measuring adverse events in hospitalized patients. The method was developed by the Institute for Healthcare Improvement (IHI) and is referred to in the paper by Sharek and colleagues as the IHI global trigger tool. This paper presents a large and well-designed reliability study and as such is an important contribution to the field of patient safety.
Cubature Kalman Filtering for Continuous-Discrete Systems: Theory and Simulations

In this paper, we extend the cubature Kalman filter (CKF) to deal with nonlinear state-space models of the continuous-discrete kind. To be consistent with the literature, the resulting nonlinear filter is referred to as the continuous-discrete cubature Kalman filter (CD-CKF). We use the Itô-Taylor expansion of order 1.5 to transform the process equation, modeled in the form of stochastic ordinary differential equations, into a set of stochastic difference equations. Building on this transformation and assuming that all conditional densities are Gaussian-distributed, the solution to the Bayesian filter reduces to the problem of how to compute Gaussian-weighted integrals. To numerically compute the integrals, we use the third-degree cubature rule. For a reliable implementation of the CD-CKF in a finite word-length machine, it is structurally modified to propagate the square-roots of the covariance matrices. The reliability and accuracy of the square-root version of the CD-CKF are tested in a case study that involves the use of a radar problem of practical significance; the problem considered herein is challenging in the context of radar in two respects- high dimensionality of the state and increasing degree of nonlinearity. The results, presented herein, indicate that the CD-CKF markedly outperforms existing continuous-discrete filters.
Scene Memory in Young Children.

The knowledge-base view of early memory development was tested by examining the importance of domain-specific knowledge about scenes as a predictor of scene memory in 3- to 6-year-old children. Multiple regression analyses were used to assess the relative importance of scene knowledge (knowing what and where objects belong in scenes) and control variables (categorical knowledge, age, and memory for unrelated objects) in predicting scene memory (recall and location memory). Scene knowledge accounted for approximately 30% of the variation in scene memory when considered individually. Although scene knowledge was an important predictor of scene memory, much of the predictive power was shared with the control variables. Further, age added significantly to the explained variance in recall, and location memory for unerelated objects added to the prediction of scene location memory
Depression and Stigma in Medical Students at a Private Medical College

Objectives: This study aimed to assess prevalence rate of depression and perceptions regarding stigma associated with depression amongst medical students. Materials and Methods: A cross-sectional survey was conducted amongst 331 undergraduate medical students at a private medical college in Gujarat. Data was collected, which comprised of socio-demographic details, Patient Health Questionnaire (PHQ-9), and a 22-item semi-structured questionnaire to assess personal, perceived, and help-seeking stigma. Univariate analysis and chi-square tests were used to test for association between variables. Results: Overall prevalence of depression was found to be 64%. Highest level of depression was seen in first year. Moderate to severe depression was found in 26.6% students. 73.3% students felt that having depression would negatively affect their education, and 52.3% saw depression as a sign of personal weakness. Females more strongly believed that students would not want to work with a depressed student (50.9% v/s 36.2%) and that if depressed, they would be unable to complete medical college responsibilities (61.9% v/s 44.1%). With increasing academic year, there was increase in stigma about disclosing depression to friends (P = 0.0082) and increase in stigma about working with a depressed student (P = 0.0067). Depressed students felt more strongly than non-depressed students on 10 items of the stigma questionnaire. Conclusions: High stigma exists among students about the causation of depression, and there exists an environment in which students discriminate fellow colleagues based on the presence of depression. This raises need for increasing awareness and support from peers and faculty.
Acute Versus Progressive Onset of Diabetes in NOD Mice: Potential Implications for Therapeutic Interventions in Type 1 Diabetes

Most natural history models for type 1 diabetes (T1D) propose that overt hyperglycemia results after a progressive loss of insulin-secreting β-cell mass and/or function. To experimentally address this concept, we prospectively determined morning blood glucose measurements every other day in multiple cohorts (total n = 660) of female NOD/ShiLtJ mice starting at 8 weeks of age until diabetes onset or 26 weeks of age. Consistent with this notion, a majority of mice that developed diabetes (354 of 489 [72%]) displayed a progressive increase in blood glucose with transient excursions >200 mg/dL, followed by acute and persistent hyperglycemia at diabetes onset. However, 135 of the 489 (28%) diabetic animals demonstrated normal glucose values followed by acute (i.e., sudden) hyperglycemia. Interestingly, diabetes onset occurred earlier in mice with acute versus progressive disease onset (15.37 ± 0.3207 vs. 17.44 ± 0.2073 weeks of age, P < 0.0001). Moreover, the pattern of onset (i.e., progressive vs. acute) dramatically influenced the ability to achieve reversal of T1D by immunotherapeutic intervention, with increased effectiveness observed in situations of a progressive deterioration in euglycemia. These studies highlight a novel natural history aspect in this animal model, one that may provide important guidance for the selection of subjects participating in human trials seeking disease reversal.
The Role of Teaching Poetry in Developing Literacy in Greek Primary School: A Case Study

THE PURPOSE OF THIS case study is to examine the ways in which the systematic teaching of poetry reading at Greek primary school enhances children's interest in reading and helps develop their oral skills by enriching their vocabulary and creative thinking. The present poetry project was implemented at a Greek public kindergarten in Rethymno, Crete in the school year 2010–2011. The sample consisted of 22 children (12 boys and 10 girls) aged five to six years. The teaching instruction design was based on Rosenblatt's Transactional theory. The data were collected through (1) an observation checklist, (2) an observation diary, (3) post-course interviews with the children, and (4) a post-course interview with the teacher of the class. The findings indicated that: (a) small children described the poetry program as the most enjoyable part of language arts, (b) children's reading engagement and motivation were increased and (c) through the poetry program children developed better literary and reading skills.
Infantile Spinal Muscular Atrophy With Respiratory Distress Type 1: A Case Report

The condition, currently known as spinal muscular atrophy with respiratory distress type 1, is an unusual variant of spinal muscular atrophy type 1 that is characterized by early respiratory failure due to diaphragmatic paralysis. The defective gene, the immunoglobulin μ-binding protein 2 (IGHMBP2 gene), of this autosomal recessive disorder is located on chromosome 11q13 and encodes immunoglobulin μ-binding protein 2. The natural history and phenotypic spectrum of the disease are still not clear. The authors present the first genetically proven case of spinal muscular atrophy with respiratory distress type 1 to be reported from Saudi Arabia. The parents are first cousins and the causative gene sequencing revealed mutation in exon 7 reported for the first time in a homozygous form. The clinical scenario of the case is discussed. The findings in the muscle magnetic resonance imaging (MRI) are presented.
Globalisation, Lifelong Learning and the Learning Society: Sociological Perspectives

Part 1: The Development of the Knowledge Economy 1. Globalisation 2. The Information and Knowledge Society Part 2: The Lifelong Learning and Learning Society 3. The Learning Society 4. Lifelong Learning 5. The Learning Organisation 6. The Learning City 7. Learning at a Distance 8. Providers of Learning Opportunities Part 3: Research and Lifelong learning 9. The Changing Nature of Research 10. Research as a Learning Process
Rise and fall patterns of information diffusion: model and implications

The recent explosion in the adoption of search engines and new media such as blogs and Twitter have facilitated faster propagation of news and rumors. How quickly does a piece of news spread over these media? How does its popularity diminish over time? Does the rising and falling pattern follow a simple universal law? In this paper, we propose SpikeM, a concise yet flexible analytical model for the rise and fall patterns of influence propagation. Our model has the following advantages: (a) unification power: it generalizes and explains earlier theoretical models and empirical observations; (b) practicality: it matches the observed behavior of diverse sets of real data; (c) parsimony: it requires only a handful of parameters; and (d) usefulness: it enables further analytics tasks such as fore- casting, spotting anomalies, and interpretation by reverse- engineering the system parameters of interest (e.g. quality of news, count of interested bloggers, etc.). Using SpikeM, we analyzed 7.2GB of real data, most of which were collected from the public domain. We have shown that our SpikeM model accurately and succinctly describes all the patterns of the rise-and-fall spikes in these real datasets.
Non-Markovian stochastic description of quantum transport in photosynthetic systems: The LH1-RC complex

We analyze several aspects of the transport dynamics in the LH1-RC core of purple bacteria, which consists basically in a ring of antenna molecules that transport the energy into a target molecule, the reaction center, placed in the center of the ring. We show that the periodicity of the system plays an important role to explain the relevance of the initial state in the transport eﬃciency. This picture is modiﬁed, and the transport enhanced for any initial state, when considering that molecules have diﬀerent energies, and when including their interaction with the environment. We study this last situation by using stochastic Schr¨odinger equations, both for Markovian and non-Markovian type of interactions.
The Cognitive Interview for Use with Adults: An Empirical Test of an Alternative Mnemonic and of a Partial Protocol

Summary Research showed that the four Cognitive Interview (CI) mnemonics used individually are unequally effective. We propose to test (i) their benefit when used within the same free recall phase and (ii) an original instruction, ‘guided peripheral focus’ (GPF). In two studies, 84 and 42 students were interviewed with Structured Interviews (SI), CIs or CI variations about a film viewed 1 week before. Results indicated that (i) if a CI variation with the GPF instead of the ‘perspective’ elicits more correct information than an SI or a CI, variations replacing the ‘perspective’ or the ‘order’ and ‘perspective’ with control instruction(s) do not; (ii) a partial CI integrating the ‘everything’, ‘context’ and GPF increases correct information compared with an SI, whereas the CI does not. We will discuss in which extent these results demonstrate the effectiveness of the ‘everything’, ‘context’ and ‘GPF’ and a potential lack of benefit of the ‘order’ and ‘perspective’. Copyright © 2011 John Wiley & Sons, Ltd.
Peer coaching for educators

Chapter 1 Foreword Chapter 2 Introduction Chapter 3 Why Peer Coaching? Chapter 4 Experiencing Peer Coaching Chapter 5 Peer Coaching/Peer Review Teams Chapter 6 Learning about Peer Coaching Chapter 7 The Teacher Requests a Visit for Peer Coaching Chapter 8 The VIsit Chapter 9 The Coach Reviews the Notes and Lists Some Possibilities Chapter 10 The Talk After the Visit Chapter 11 Process Review and Reflection on Peer Coaching Chapter 12 Selling and Buying into Peer Coaching Chapter 13 Putting Peer Coaching in Place in a School Chapter 14 Teaching Portfolios and Peer Coaching Chapter 15 Next Steps: Changing Teacher Preparation and Evaluation Systems Chapter 16 Appendix 1: Masters for Handouts and Transparencies Chapter 17 Appendix 2: A Training Agenda for Peer Coaching Chapter 18 Bibliography
Regulation of Gene Expression in Cardiomyocytes by Thyroid Hormone and Thyroid Hormone Analogs 3,5-Diiodothyropropionic Acid and CGS 23425 [N-[3,5-Dimethyl-4-(4′-hydroxy-3′-isopropylphenoxy)-phenyl]-oxamic Acid]

The heart is an important target of thyroid hormone actions. Only a limited number of cardiac target genes have been identified, and little is known about their regulation by T3 (3,3′,5-triiodothyronine) and thyroid hormone analogs. We used an oligonucleotide microarray to identify novel cardiac genes regulated by T3 and two thyroid hormone analogs, 3,5-diidodothyropropionic acid (DITPA) and CGS 23425 [N-[3,5-dimethyl-4-(4′-hydroxy-3′-isopropylphenoxy)-phenyl]-oxamic acid]. DITPA binds with lower affinity than T3 to thyroid hormone receptor α1 and β1 isoforms, whereas CGS 23425 binds selectively to β1. Fluorescent-labeled cDNA was prepared from cultured heart cells maintained in medium stripped of thyroid hormone (“hypothyroid” control) or treated with T3, DITPA, and CGS 23425 at concentrations 5 times their respective Kd values for 48 h. The arrays were scanned and analyzed using an analysis of variance program. Sixty-four genes were identified that were >1.5 times up- or down-regulated by one of the treatments with P < 0.05. The genes regulated by T3 and DITPA were nearly identical. Thirteen genes were differentially regulated by CGS 23425. Genes encoding contractile proteins, Ca2+-ATPase of sarcoplasmic reticulum and several proteins of mitochondrial oxidative phosphorylation, were up-regulated by T3 and DITPA but not by CGS 23425. These results indicate that some, but not all, of the actions of thyroid hormone analogs can be explained by differences in gene activation.
CherryPick: tracing packet trajectory in software-defined datacenter networks

SDN-enabled datacenter network management and debugging can benefit by the ability to trace packet trajectories. For example, such a functionality allows measuring traffic matrix, detecting traffic anomalies, localizing network faults, etc. Existing techniques for tracing packet trajectories require either large data collection overhead or large amount of data plane resources such as switch flow rules and packet header space. We present CherryPick, a scalable, yet simple technique for tracing packet trajectories. The core idea of our technique is to cherry-pick the links that are key to representing an end-to-end path of a packet, and to embed them into its header on its way to destination. Preliminary evaluation on a fat-tree topology shows that CherryPick requires minimal switch flow rules, while using header space close to state-of-the-art techniques.
Exploiting channel state information in slotted ALOHA with SINR capture

In this paper, we consider a channel-aware ALOHA network in which users have the knowledge of their own channel state information (CSI) and exploit this decentralized CSI by utilizing CSI-based transmission schemes. The system throughput is investigated with multi-region transmission schemes under the signal-to-interference-plus-noise ratio (SINR) capture model. We discover that the two-region transmission scheme performs well enough for maximizing the throughput.
O PLANEJAMENTO COMO PROCESSO DINÂMICO: A IMPORTÂNCIA DO ESTUDO PILOTO PARA UMA PESQUISA EXPERIMENTAL EM LINGUÍSTICA APLICADA

This paper aims to present some reflections on the dynamic process of planning, during the implementation of a pilot study of a Master’s degree project about working memory and simultaneous attention to form and meaning in foreign language reading (English). For this, the context of investigation, aims, research questions, instruments, and reflections from the pilot study are introduced. This movement of application, reflection, and re-organization is very important for the researcher, since she/he has the opportunity to “put hands on” and effectively experience moments of data collection, and, therefore, build knowledge for the research, derived from the pilot study.
Department of Economics Working Paper Series Analyzing Skilled and Unskilled Labor Efficiencies in the Us Analyzing Skilled and Unskilled Labor Efficiencies in the Us

In this paper, using a production framework in which skilled and unskilled labor are imperfect substitutes, I analyze the time paths of the efficiencies of skilled and unskilled labor and their implications for economic growth and wage inequality in the US between 1950 and 2005. There are two main findings. First, I find that skilled labor efficiency has grown more slowly since the mid 1970s. Second and more interestingly, I find that beginning in the early 1970s, there has been a considerable decline in the absolute level of the efficiency of unskilled labor, implying that the decline has played a significant role in the overall productivity slowdown and the substantial widening in the U.S. wage structure. Weil for useful discussions and suggestions. I thank Julie B. Cullen and Melissa Kearney for help with data.
The Niikawa‐Kuroki (Kabuki make‐up) syndrome in a Moslem Arab child

The Niikawa‐Kuroki “Kabuki Make‐Up” syndrome is a rare sporadic malformation syndrome, characterised by severe psychomotor and growth retardation, peculiar facies, including long palpabral fissures and large malformed ears and skeletal abnormalities. We report a 2‐year‐old Moslem Arab boy with 28 of the 32 originally described features of this syndrome and in addition with hyperelastic joints, hypospadias and scaphocephaly which were not previously described in association with the Kabuki make‐up syndrome. This is the fifth reported case of this syndrome in a non‐Japanese patient, and the second reported case in a patient of Arab descent.
Hybrid Ant Colony Optimization Using Memetic Algorithm for Traveling Salesman Problem

Ant colony optimization was originally presented under the inspiration during collective behavior study results on real ant system, and it has strong robustness and easy to combine with other methods in optimization. Although ant colony optimization for the heuristic solution of hard combinational optimization problems enjoy a rapidly growing popularity, but little research is conducted on the optimum configuration strategy for the adjustable parameters in the ant colony optimization, and the performance of ant colony optimization depends on the appropriate setting of parameters which requires both human experience and luck to some extend. Memetic algorithm is a population-based heuristic search approach which can be used to solve combinatorial optimization problem based on cultural evolution. Based on the introduction of these two meta-heuristic algorithms, a novel kind of adjustable parameters configuration strategy based on memetic algorithm is developed in this paper, and the feasibility and effectiveness of this approach are also verified through the famous traveling salesman problem (TSP). This hybrid approach is also valid for other types of combinational optimization problems
Breast cancer histopathological image classification using Convolutional Neural Networks

The performance of most conventional classification systems relies on appropriate data representation and much of the efforts are dedicated to feature engineering, a difficult and time-consuming process that uses prior expert domain knowledge of the data to create useful features. On the other hand, deep learning can extract and organize the discriminative information from the data, not requiring the design of feature extractors by a domain expert. Convolutional Neural Networks (CNNs) are a particular type of deep, feedforward network that have gained attention from research community and industry, achieving empirical successes in tasks such as speech recognition, signal processing, object recognition, natural language processing and transfer learning. In this paper, we conduct some preliminary experiments using the deep learning approach to classify breast cancer histopathological images from BreaKHis, a publicly dataset available at http://web.inf. ufpr.br/vri/breast-cancer-database. We propose a method based on the extraction of image patches for training the CNN and the combination of these patches for final classification. This method aims to allow using the high-resolution histopathological images from BreaKHis as input to existing CNN, avoiding adaptations of the model that can lead to a more complex and computationally costly architecture. The CNN performance is better when compared to previously reported results obtained by other machine learning models trained with hand-crafted textural descriptors. Finally, we also investigate the combination of different CNNs using simple fusion rules, achieving some improvement in recognition rates.
Organisational Creativity in Context: Learning from a Failing Attempt to Introduce IT Support for Creativity

As a much-needed quality in todayâ€™s businesses, creativity is an important area of research. While implementing and evaluating computer support for electronic brainstorming (EBS), it was noticed that the sheer presence of technology guarantees neither usage nor success. Contextual factors such as organisational culture and attitudes seem to have an equally important role, and this observation called for a more focused analysis of the motivational aspects of creativity management. Based on the empirical data from the electronic brainstorming system evaluation and literature on organisational creativity, three general pieces of managerial advice to promote corporate creativity are suggested: reconsider the use of extrinsic rewards, recognise creative initiatives, and allow redundancy.