Miracle-dz/UniFAR-FTUs huggingface dataset:
Les algues d ' eau douce : initiation d la systematique , 3 : les algues bleus

Bourrelly, P. C. 1970. Les algues d'eau douce: initiation d la systematique, 3: les algues bleus et rouges, les Eugliniens, Peridiniens et Cryptomonadines. Paris, Editions N. Boubee and Cie. Vol. 3, pp. 1-512, pls. 1-137. Drouet, F. 1968. Revision of the Classification of Oscillatoriaceae. Philadelphia, The Academy of Natural Sciences. pp. 1-370, figs. 1-130. 1973. Revision of the Nostocaceae with cylindrical trichomes. New York, Hafner Press. pp. 1-292, figs. 1-83. --. 1978. Revision of the Nostocaceae with constricted trichomes. Beih. Nova Hedwigia 57: 1258, figs. 1-42. 1981. Revision of the Stigonemataceae with a summary of the classification of the bluegreen algae. Beih. Nova Hedwigia 66: 1-221, figs. 1-190. and W. A. Daily. 1956. Revision of the coccoid Myxophyceae. Butler Univ. Bot. Stud. 12: 1-222, figs. 1-377. Stafleu, F. A. et al. 1978. International code of botanical nomenclature. Regnum Veg. 97: 1-457.
Visualization of Social Networks in Stata by Multi-dimensional Scaling ∗

Social network analysis (SNA) studies patterns of interaction between social entities (Wasserman and Faust, 1994; Scott, 2000). In the past few decades, SNA has emerged as a major research paradigm in the social sciences (including economics), and has also attracted attention in other fields (Newman et al., 2006). While dedicated software for SNA exists (e.g., UCInet (Borgatti et al., 1999) or Pajek (Bagatelj and Mrvar, 2009)), Stata currently lacks readily available facilities for SNA. In this paper, we illustrate how methods for SNA can be developed in Stata, using network visualization as an example. Visualization is one of the oldest methods in SNA and is still one of its most important and widely applied tools to uncover patterns of relations (Freeman, 2000). We describe a procedure for network visualization using Stata’s built-in procedures for multidimensional scaling and describe an implementation as a Stata command. While we believe that network visualization in itself can be highly useful, the example also illustrates how SNA problems can be handled in Stata more generally.
Hsp 90 as a Gatekeeper of Tumor Angiogenesis : Clinical Promise and Potential Pitfalls

Tumor vascularization is an essential modulator of early tumor growth, progression, and therapeutic outcome. Although antiangiogenic treatments appear promising, intrinsic and acquired tumor resistance contributes to treatment failure. Clinical inhibition of the molecular chaperone heat shock protein 90 (Hsp90) provides an opportunity to target multiple aspects of this signaling resiliency, which may elicit more robust and enduring tumor repression relative to effects elicited by specifically targeted agents. This review highlights several primary effectors of angiogenesis modulated by Hsp90 and describes the clinical challenges posed by the redundant circuitry of these pathways. The four main topics addressed include (1) Hsp90-mediated regulation of HIF/VEGF signaling, (2) chaperone-dependent regulation of HIF-independent VEGF-mediated angiogenesis, (3) Hsp90dependent targeting of key proangiogenic receptor tyrosine kinases and modulation of drug resistance, and (4) consideration of factors such as tumor microenvironment that pose several challenges for the clinical efficacy of anti-angiogenic therapy and Hsp90-targeted strategies.
Detecting changes in transient complex systems via dynamic network inference

Abstract Graph analytics methods have evoked significant interest in recent years. Their applicability to real-world complex systems is currently limited by the challenges of inferring effective graph representations of the high-dimensional, noisy, nonlinear and transient dynamics from limited time series outputs, as well as of extracting statistical quantifiers that capture the salient structure of the inferred graphs for detecting change. In this article, we present an approach to detecting changes in complex dynamic systems that is based on spectral-graph-theory and uses a single realization of time series data collected under specific, common types of transient conditions, such as intermittency. We introduce a statistic, γk, based on the spectral content of the inferred graph. We show that the γk statistic under high-dimensional dynamics converges to a normal distribution, and we employ the parameters of this distribution to construct a procedure to detect qualitative changes in the coupling structure of a dynamical system. Experimental investigations suggest that the γk statistic by itself is able to detect changes with modified area under curve (mAUC) of about 0.96 (for numerical simulation tests), and can, by itself, achieve a true positive rate of about 40% for detecting seizures from EEG signals. In addition, by incorporating this statistic with random forest, one of the best seizure detection methods, the seizure detection rate of the random forest method improves by 5% in 35% of the subjects. These studies of the network inferred from EEG signals suggest that γk can capture salient structural changes in the physiology of the process and can therefore serve as an effective feature for detecting seizures from EEG signals.
Atlas-Based Segmentation Pipelines on 3D Brain MR Images: A Preliminary Study

Three dimensional structural MR imaging is a high-resolution imaging technique used in the detection and follow up of neurological disorders. Rigid changes in the brain are usually interpreted and reported manually by radiologists using MR images. The results of manual interpretation may vary with respect to the experts. At the same time, measurement and segmentation of the brain regions and the manual evaluation of the volume changes are a difficult process. With the increase of numerical methods, automated and semi-automated package programs have been developed for the analysis of brain measurements. These programs use electronic brain atlases or tissue probability maps. However, since the package programs have a lot of analysis time and give only certain outputs, they may be disadvantaged in the use of segmentation and measurement of brain regions. Hence, special pipelines are needed especially to obtain valuable features for artificial intelligence and classification studies. In this study, we propose pipelines to segment 3D certain brain regions, which will help to find the basic features such as volume changes, intensity variations, symmetry deteriorations, and tissue changes. With these pipelines, 3D segmentation of the brain regions defined in the atlas can be performed and normalized. It is aimed to use these studies as a preliminary study in order to quantitatively determine the basic changes in the brain by performing the volume of interest methods and to formulate a decision support system.
CUMULATIVE RESEARCH KNOWLEDGE AND SOCIAL POLICY FORMULATION: The Critical Role of Meta-Analysis

For many years, policymakers expressed increasing frustration with social science research. On every issue there were studies arguing for diametrically opposed conclusions. Methods of meta-analysis that correct for the effects of sampling error have shown that almost all such conflicting results were caused by sampling error. Furthermore, the effects of sampling error are greatly exaggerated by using significance test methodology. In many areas, meta-analysis has now provided dependable answers to the original research questions. Meta-analysis is now increasingly being used by policymakers, by textbook writers, and by theorists to provide the basic facts needed to draw both practical and explanatory conclusions. Sophisticated meta-analysis procedures are now used to correct for the effects of other study imperfections, such as measurement error, range restriction, and artificial dichotomization. In domains where the data on artifacts are available, the effect sizes in necessarily imperfect studies have been found to be considerably understated. Path analysis can be applied to the findings from meta-analysis to yield improved causal analyses that result in both explanation of results and improved generalization of results to new settings.
Multimodal Deep Neural Networks for Pose Estimation and Action Recognition

In this work, we present a unified multimodal neural network for pose estimation from RGB images and action recognition from video sequences. We show that a multimodal approach benefits 3D pose estimation by mixing high precision 3D data and “in the wild” 2D annotated images, while action recognition also benefits from better visual features. Furthermore, we demonstrate by our experiments that end-to-end optimization results in better performance for action recognition than separated learning. We reported state-of-the-art results on 3D pose estimation and action recognition respectively on Human3.6M and NTU RGB+D datasets.
PGF2a Inhibits VEGF Expression in the Corpus Luteum in the Mid but not Early Luteal Phase of the sheep Estrous Cycle

We would like to thank The OARDC Research Enhancement Competitive Grants Program, The Ohio State Undergraduate Enrichment Grants Program, and William C. Hauk Memorial Scholarship Fund for funding this research. We would also like to thank Ann Ottobre, Laura Arbogast, Amanda Roberts, and Janelle Gaddis for their intellectual and technical contributions, Dr. Horacio Cardenas for donating the L-19 primers used for real-time PCR, and Dr. Normand St-Pierre for statistical consultation.
Monitoring poverty and social exclusion 2003

The New Policy Institute has produced its sixth annual report of indicators of poverty and social exclusion. This year's report focuses on regional variations across England, Scotland and Wales. With 5 years of data now available to measure progress since Labour came to office in 1997, it is becoming much clearer where the Government's strategy for combating poverty and social exclusion is being successful – and where it is not. With the number of people living in low-income households now on a steady downward trend, the latest figures (for 2001/2002) passed the notable milestone of taking income poverty lower than at any time in the 1990s. The main reason why the number of people in low-income households fell in the 5 years to 2001/2002 is that there were fewer people in workless households. But, over the same period, the number of people in low-income, working households did not fall. Out-of-work benefits to both working-age families with dependent children and to pensioners have risen by around 30% in real terms since 1998, faster than earnings. This, plus the rise in tax credits, will have had a significant impact on the severity of poverty suffered by some low-income households even when it has not taken them above the low-income threshold. In education, earlier progress in increasing the numbers of those with an adequate minimum level of qualification has stalled, with no further advance since 2000, compared with rapid progress during the second half of the 1990s. Around a quarter of young people at each of the ages of 11, 16 and 19 are still failing to reach a basic level of attainment. There is no sign of any reduction since 1997 in the health inequalities which leave people with low incomes more likely to suffer serious health-related problems. Across the range of indicators, problems of poverty and social exclusion are generally more prevalent in the North-east than in other areas of the country. London has particular problems centred on low income and work and Scotland has particular problems centred on health.
EVALUASI SISTEM E-SAMSAT BERBASIS MOBILE UNTUK LAYANAN MASYARAKAT KOTA PALEMBANG DENGAN TECHNOLOGY ACCEPTANCE MODEL

The development of science and information technology supports activities carried out by individuals in using technology, to support operational and management performance. Such as Mobile-based e-Samsat Service to serve vehicle taxation with two-wheeled or four-wheeled vehicles, especially the people of Palembang. Mobile tax payments that can make it easier and closer to densely populated locations or caused by busyness. Information systems help service income tax factors of successful application and use of information technology are user factors. The level of readiness of users to receive information technology has a major influence in determining whether or not the application of the technology is successful. The purpose of this study is to identify factors that influence users in using the mobile-based e-Samsat Information System in the city of Palembang. Data analysis was carried out with SPSS (Statistical package for the social science) with the TAM (Technology Acceptance Model) software which is a technology acceptance model that will be used by technology users. By evaluating e-Samsat, it is to find out whether the system has served motor vehicle tax payments properly and has met service quality standards. This study will evaluate the performance of e-Samsat with TAM instruments
Do Online Recommendations Matter?-A Multimodal Investigation of Amazon's Co-Purchase Network

Online recommendations are considered as a useful approach to encourage consumer purchases and drive product sales in e-commerce. This paper uses a multimodal approach to examine the effectiveness of online recommendations using the lenses of econometric modeling and text mining. Applying data on Amazon’s “customers who bought this item also bought” recommendation, commonly referred to as the co-purchase network, this study presents several findings. First, the effects of direct co-purchase recommendations on product sales are essentially strong, regardless of other potential factors that can also affect those sales. Second, the sales of one product can have positive effect on the sales of another, when the latter is suggested in co-purchase recommendations. Moreover, the similarity of the customer base between the two co-purchased products, which can be extracted using text mining from online reviews, will affect that product’s sales. This finding leads to the conclusion that online recommendations achieve by recommending related products to like-minded consumers, and that recommendation effect is significant. These results contribute to academics and practitioners by providing clear economic evidence of the value of using text mining approaches for online recommendations.
The basics of item response theory

Acknowledgments Over the past century, many people have contributed to the development of item response theory. Three persons deserve special recognition. D.N. Lawley of the University of Edinburgh published a paper in 1943 showing that many of the constructs of classical test theory could be expressed in terms of parameters of the item characteristic curve. This paper marks the beginning of item response theory as a measurement theory. The work of Dr. F.M. Lord of the Educational Testing Service has been the driving force behind both the development of the theory and its application for the past 50 years. Dr. Lord systematically defined, expanded and explored the theory as well as developed computer programs needed to put the theory into practice. This effort culminated in his classic books (with Dr. Melvin Novick, 1968; 1980) on the practical applications of item response theory. In the late 1960s, Dr. B.D. Wright of the University of Chicago recognized the importance of the measurement work by the Danish mathematician Georg Rasch. Since that time he has played a key role in bringing item response theory, the Rasch model in particular, to the attention of practitioners. Without the work of these three individuals, the level of development of item response theory would not be where it is today. The author is indebted to Mr. T. Seavey of Heinemann Educational Books for first suggesting that I do a small book on item response theory, which resulted in the first edition of this book in 1985. This suggestion allowed me to fulfill a long-standing desire to develop an instructional software package dealing with item response theory for the then-state-of-the-art APPLE II and IBM PC computers. An upgraded version of this software has now been made available on the World Wide Web When Frank Baker wrote his classic The Basics of Item Response Theory in 1985, the field of educational assessment was dominated by classical test theory based on test scores. Item response theory was an upstart whose popular acceptance lagged in part because the underlying statistical calculations were quite complex. Baker's contribution was to pair a well-written introductory text on IRT with software for the then state-of-the art Apple II and IBM personal computers. The software enabled readers to experiment with concepts of the theory in eight sequential sessions. Much has changed since 1985. IRT now powers the work of major U.S. test publishers and is used …
Accurate Ranging on Acoustic-Enabled IoT Devices

The enabling Internet-of-Things technology has inspired many innovative sensing mechanisms by repurposing the onboard sensors. Leveraging the built-in acoustic sensors for ranging is among one of the interesting applications. However, among the few studies on acoustic ranging, the one-way sensing method suffers from synchronization errors and requires cumbersome kernel modifications; the other two-way approaches overcome these shortcomings, but they are sensitive to system delays. In this case, this paper proposes a novel lightweight one-way sensing paradigm without the above drawbacks. The key insight of this paper is to perform ranging by estimating the propagation time of acoustic signals via linear frequency modulation signal mixing. Such a signal mix operation can translate range estimation into fine-grain frequency estimation, thereby enhancing ranging accuracy. In addition, our system can have multiple receivers co-exist and thus the measurement dimensions are boosted. We have implemented and evaluated our system prototype in real-world settings. The prototype demonstrated centimeter-level ranging performance.
Data mining techniques applied in educational environments: Literature Review

Abstract: Data Mining for Education is an emerging discipline which seeks to develop methods to explore large amounts of data from educational settings, in order to understand students better. In recent years there have been various works related with this specialty and have used multiple data mining techniques derived from this to address different educational problems. The aim of this publication is to present a review of the works in which data mining techniques were used to solve specific problems of education and to do a classification of these, associated with diverse scenarios in which it has been applied. Resumen: La mineria de datos para la educacion es una disciplina emergente la cual busca el desarrollo de metodos que permitan explorar grandes cantidades de datos provenientes de entornos educativos con el fin de entender mejor a los estudiantes. En los ultimos anos se han realizado diversos trabajos relacionados con esta disciplina y se han utilizado multiples tecnicas de mineria de datos para abordar diferentes problematicas educativas. El objetivo de esta publicacion es presentar una revision de los trabajos en los cuales se han utilizado tecnicas de minerias de datos para solucionar problematicas particulares de la educacion y realizar una clasificacion de estas asociadas a los diversos escenarios en los que se han aplicado.
Psychometric evaluation of Antonovsky's Sense of Coherence Scale.

The psychometric properties of Antonovsky's Sense of Coherence (SOC) Scale were examined. Subjects (N = 374) completed the SOC scale and a battery of theoretically relevant questionnaires. Principal-components analysis with a Varimax-Promax rotation produced a solution with 5 factors, which were further reduced to 1 factor, suggesting that the SOC scale is a unidimensional instrument. Additional analyses indicated satisfactory internal consistency as well as test-retest reliability at 1 and 2 weeks. Evidence for the validity of the SOC scale was obtained in that nonclinical subjects obtained higher SOC scores than did clinical subjects. Additional validity evidence was provided by negative correlations between SOC scores and self-reports of (a) perceived stress, (b) trait anxiety, and (c) current depression; Discriminant evidence for the validity of the SOC scale was mixed
Some Effects of Limited Feedback on Performance and Problem-Solving Strategy in a Logo Microworld

The effect of limiting the availability of immediate feedback in a Logo microworld was examined by observing children solve problems involving the reproduction of given rotations without the information provided by a rotating turtle. It was found that limiting the feedback in this way reduced the incidence of trial-and-error problem-solving strategies. There was also evidence that higher level problem-solving strategies, which took into account a wider range of problem features, were used to compensate for the restricted access to immediate feedback
Early Face-to-Face Interaction and Its Relation to Later Infant-Mother Attachment.

BLEHAR, MARY C. ; LIEBERMAN, ALICIA F. ; and AINSWORTH, MARY D. SALTER. Early Face-to-Face Interaction and Its Relation to Later Infant-Mother Attachment. CHILD DEVELOPMENT, 1977, 48, 182194. Face-to-face interaction between 26 infants and (a) their mothers and (b) a relatively unfamiliar figure was observed longitudinally between 6 and 15 weeks of age in the home environment. Highlights of normative findings are that infants became more responsive over this time period, whereas maternal behavior did not change. In the sample as a whole, infants were more responsive to the mother than to the unfamiliar figure on only 1 measure, bouncing. Individual differences in maternal behavior were stable throughout, but individual differences in infant behavior were not. Individual differences in interaction were analyzed and summarized by means of a factor analysis. Factor I opposed positive infant responsiveness to minimal response and maternal playfulness to impassiveness. Factor II contrasted maternal contingent pacing, infant delight, and prolonged interaction with routine maternal manner, abruptness, negative infant response, and brief interaction. Individual differences in interaction were found to be related to later differences in infant-mother attachment, as assessed by a strange-situation procedure at 51 weeks of age. Infants later identified as securely attached were more responsive in early en face encounters than infants judged to be anxiously attached, and their mothers were more contingently responsive and encouraging of interaction. Infants later identified as anxiously attached were more unresponsive and negative in early en face interaction than securely attached infants, and their mothers were more likely to be impassive or abrupt. Securely attached infants were more positively responsive to the mother than to an unfamiliar figure in early face-to-face episodes, while anxiously attached infants were not.
From Goods to Services Consumption: A Social Network Analysis on Sharing Economy and Servitization Research

The transition from consuming goods to consuming services is a topic of great interest for service researchers and has been examined from various perspectives. We provide an overview of how this field of research has been approached by systematically analyzing the current state of the academic literature. We report the results of a social network analysis of the sharing economy and servitization literature, which reveals the structure of the knowledge networks that have been formed as a result of the collaborative works of researchers, institutions, and journals that shape, generate, distribute, and pre-serve the domains’ intellectual knowledge. We shed light on the cohesion and fragmentation of knowledge and highlight the emerging and fading topics within the field. The results present a detailed analysis of the research field and suggest a research agenda on the transition of goods to services consumption. on the hotel industry, Journal of Marketing Research , 54 (5), 687–705.