LLukas22/scidocs huggingface dataset:
Colony size predicts division of labour in attine ants

Division of labour is central to the ecological success of eusocial insects, yet the evolutionary factors driving increases in complexity in division of labour are little known. The size-complexity hypothesis proposes that, as larger colonies evolve, both non-reproductive and reproductive division of labour become more complex as workers and queens act to maximize inclusive fitness. Using a statistically robust phylogenetic comparative analysis of social and environmental traits of species within the ant tribe Attini, we show that colony size is positively related to both non-reproductive (worker size variation) and reproductive (queen-worker dimorphism) division of labour. The results also suggested that colony size acts on non-reproductive and reproductive division of labour in different ways. Environmental factors, including measures of variation in temperature and precipitation, had no significant effects on any division of labour measure or colony size. Overall, these results support the size-complexity hypothesis for the evolution of social complexity and division of labour in eusocial insects. Determining the evolutionary drivers of colony size may help contribute to our understanding of the evolution of social complexity.
Mapping the grounding zone of the Amery Ice Shelf, East Antarctica using InSAR, MODIS and ICESat

We use a combination of satellite techniques (interferometric synthetic aperture radar (InSAR), visible-band imagery, and repeat-track laser altimetry) to develop a benchmark map for the Amery Ice Shelf (AIS) grounding zone (GZ), including its islands and ice rises. The break-in-slope, as an indirect estimate of grounding line location, was mapped for the entire AIS. We have also mapped ,55% of the landward edge and ,30% of the seaward edge of the ice shelf flexure boundary for the AIS perimeter. Vertical ice motion from Global Positioning System receivers confirms the location of the satellite-derived GZ in two regions. Our map redefines the extent of floating ice in the south-western AIS and identifies several previously unmapped grounded regions, improving our understanding of the stresses supporting the current dynamical state of the ice shelf. Finally, we identify three along-flow channels in the ice shelf basal topography, approximately 10 km apart, 1.5 km wide and 300–500 m deep, near the southern GZ. These channels, which form at the suture zones between ice streams, may represent zones of potential weakness in the ice shelf and may influence sub-ice-shelf ocean circulation. Received 3 November 2008, accepted 27 April 2009
Stopping Criteria in Contrastive Divergence: Alternatives to the Reconstruction Error

Restricted Boltzmann Machines (RBMs) are general unsupervised learning devices to ascertain generative models of data distributions. RBMs are often trained using the Contrastive Divergence learning algorithm (CD), an approximation to the gradient of the data log-likelihood. A simple reconstruction error is often used to decide whether the approximation provided by the CD algorithm is good enough, though several authors (Schulz et al., 2010; Fischer & Igel, 2010) have raised doubts concerning the feasibility of this procedure. However, not many alternatives to the reconstruction error have been used in the literature. In this manuscript we investigate simple alternatives to the reconstruction error in order to detect as soon as possible the decrease in the log-likelihood during learning. Proceedings of the 2 International Conference on Learning Representations, Banff, Canada, 2014. Copyright 2014 by the author(s).
Introduction to In Situ Forming Hydrogels for Biomedical Applications

© Springer Science+Business Media Singapore 2015 X.J. Loh (ed.), In-Situ Gelling Polymers, Series in BioEngineering, DOI 10.1007/978-981-287-152-7_2 Abstract In situ gelling polymer aqueous solutions undergo sol-to-gel transition through chemical and/or physical crosslinking. The criterion on sol and gel is an important issue, therefore, rheology of hydrogel have been discussed in detail. The in situ gelling system has been investigated for minimally invasive drug delivery, injectable tissue engineering, gene delivery, and wound healing. In this chapter, in situ gelling systems and their various biomedical applications were briefly summarized.
Optimal Execution of Portfolio Transactions

We consider the execution of portfolio transactions with the aim of minimizing a combination of volatility risk and transaction costs arising from permanent and temporary market impact. For a simple linear cost model, we explicitly construct the e cient frontier in the space of time-dependent liquidation strategies, which have minimum expected cost for a given level of uncertainty. This analysis yields a number we call the \half-life" of a trade, the natural time for execution in the absence of exogeneous time constraints. We also construct optimal strategies for trading through scheduled news events such as earnings announcements. We thank Andrew Alford, Alix Baudin, Mark Carhart, Ray Iwanowski, and Giorgio De Santis (Goldman Sachs Asset Management), Robert Ferstenberg (ITG), Michael Weber (Merrill Lynch), Andrew Lo (Sloan School, MIT), and George Constaninides (Graduate School of Business, University of Chicago) for helpful conversations. This paper was begun while the second author was employed at Morgan Stanley Dean Witter The University of Chicago, Department of Mathematics, 5734 S. University Ave., Chicago IL 60637; almgren@math.uchicago.edu Goldman Sachs Asset Management and Courant Institute of Mathematical Sciences; Neil.Chriss@gs.com
Development of Social Media GIS to Support Information Utilization from Normal Times to Disaster Outbreak Times

The present study aims to design, develop, operate and evaluate a social media GIS (Geographical Information Systems) specially tailored to mash-up the information that local residents and governments provide to support information utilization from normal times to disaster outbreak times in order to promote disaster reduction. The conclusions of the present study are summarized in the following three points. (1) Social media GIS, an information system which integrates a Web-GIS, an SNS and Twitter in addition to an information classification function, a button function and a ranking function into a single system, was developed. This made it propose an information utilization system based on the assumption of disaster outbreak times when information overload happens as well as normal times. (2) The social media GIS was operated for fifty local residents who are more than 18 years old for ten weeks in Mitaka City of Tokyo metropolis. Although about 32% of the users were in their forties, about 30% were aged fifties, and more than 10% of the users were in their twenties, thirties and sixties or more. (3) The access survey showed that 260 pieces of disaster information were distributed throughout the whole city of Mitaka. Among the disaster information, danger-related information occupied 20%, safety-related information occupied 68%, and other information occupied 12%. Keywords—Social Media GIS; Web-GIS; SNS; Twitter; Disaster Information; Disaster Reduction; Support for Information Utilization
Hierarchical face parsing via deep learning

This paper investigates how to parse (segment) facial components from face images which may be partially occluded. We propose a novel face parser, which recasts segmentation of face components as a cross-modality data transformation problem, i.e., transforming an image patch to a label map. Specifically, a face is represented hierarchically by parts, components, and pixel-wise labels. With this representation, our approach first detects faces at both the part- and component-levels, and then computes the pixel-wise label maps (Fig.1). Our part-based and component-based detectors are generatively trained with the deep belief network (DBN), and are discriminatively tuned by logistic regression. The segmentators transform the detected face components to label maps, which are obtained by learning a highly nonlinear mapping with the deep autoencoder. The proposed hierarchical face parsing is not only robust to partial occlusions but also provide richer information for face analysis and face synthesis compared with face keypoint detection and face alignment. The effectiveness of our algorithm is shown through several tasks on 2, 239 images selected from three datasets (e.g., LFW [12], BioID [13] and CUFSF [29]).
Optimization and Evaluation of Torque-Sharing Functions for Torque Ripple Minimization in Switched Reluctance Motor Drives

Two improved torque-sharing functions for implementing torque ripple minimization (TRM) control are presented in this paper. The proposed torque-sharing functions are dependent on the turn-on angle, overlap angle, and the expected torque. This study shows that for a given torque the turn-on angle and the overlap angle have significant effects upon speed range, maximum speed, copper loss, and efficiency. Hence, genetic algorithm is used to optimize the turn-on angle and the overlap angle at various expected torque demands operating under the proposed TRM control in order to maximize the speed range and minimize the copper loss. Furthermore, four torque-sharing functions are used to derive the optimized results. At the same time, a fast and accurate online approach to compute the optimal turn-on and overlap angles is proposed. Therefore, this paper provides a valuable method to improve the performances of switched reluctance motor drives operating under TRM control.
Functional defecation disorders in children: comparing the Rome II with the Rome III criteria.

OBJECTIVES
To evaluate the prevalence of pediatric functional defecation disorders (FDD) using the Rome III criteria and to compare these data with those obtained using Rome II criteria.


STUDY DESIGN
A chart review was performed in patients referred to a tertiary outpatient clinic with symptoms of constipation and/or fecal incontinence. All patients received a standardized bowel questionnaire and physical examination, including rectal examination. The prevalence of pediatric FDD according to both Rome criteria sets was assessed.


RESULTS
Patients with FDD (n = 336; 61% boys, mean age 6.3 ± 3.5 SD) were studied: 39% had a defecation frequency ≤ 2/wk, 75% had fecal incontinence, 75% displayed retentive posturing, 60% had pain during defecation, 49% passed large diameter stools, and 49% had a palpable rectal fecal mass. According to the Rome III criteria, 87% had functional constipation (FC) compared with only 34% fulfilling criteria for either FC or functional fecal retention based on the Rome II definitions (P < .001). Of the patients with a rectal fecal mass, 95% would also have been correctly identified as having FC without a rectal examination. Twenty-nine patients (11%) fulfilled the criteria for functional nonretentive fecal incontinence according to both the Rome II and Rome III criteria.


CONCLUSION
The pediatric Rome III criteria for FC are less restrictive than the Rome II criteria. The Rome III criteria are an important step forward in the definition and recognition of FDD in children.
A machine learning framework for sport result prediction

Machine learning (ML) is one of the intelligent methodologies that have shown promising results in the domains of classification and prediction. One of the expanding areas necessitating good predictive accuracy is sport prediction, due to the large monetary amounts involved in betting. In addition, club managers and owners are striving for classification models so that they can understand and formulate strategies needed to win matches. These models are based on numerous factors involved in the games, such as the results of historical matches, player performance indicators, and opposition information. This paper provides a critical analysis of the literature in ML, focusing on the application of Artificial Neural Network (ANN) to sport results prediction. In doing so, we identify the learning methodologies utilised, data sources, appropriate means of model evaluation, and specific challenges of predicting sport results. This then leads us to propose a novel sport prediction framework through which ML can be used as a learning strategy. Our research will hopefully be informative and of use to those performing future research in this application area. 2017 The Authors. Production and hosting by Elsevier B.V. on behalf of King Saud University. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
The social brain hypothesis

The concensus view has traditionally been that brains evolved to process information of ecological relevance. This view, however, ignores an important consideration: Brains are exceedingly expensive both to evolve and to maintain. The adult human brain weighs about 2% of body weight but consumes about 20% of total energy intake.2 In the light of this, it is difficult to justify the claim that primates, and especially humans, need larger brains than other species merely to do the same ecological job. Claims that primate ecological strategies involve more complex problem-solving3,4 are plausible when applied to the behaviors of particular species, such as termite-extraction by chimpanzees and nut-cracking by Cebus monkeys, but fail to explain why all primates, including those that are conventional folivores, require larger brains than those of all other mammals. An alternative hypothesis offered during the late 1980s was that primates’ large brains reflect the computational demands of the complex social systems that characterize the order.5,6 Prima facie, this suggestion seems plausible: There is ample evidence that primate social systems are more complex than those of other species. These systems can be shown to involve processes such as tactical deception5 and coalition-formation,7,8 which are rare or occur only in simpler forms in other taxonomic groups. Because of this, the suggestion was rapidly dubbed the Machiavellian intelligence hypothesis, although there is a growing preference to call it the social brain hypothesis.9,10 Plausible as it seems, the social brain hypothesis faced a problem that was recognized at an early date. Specifically, what quantitative empirical evidence there was tended to favor one or the other of the ecological hypotheses,1 whereas the evidence adduced in favor of the social brain hypothesis was, at best, anecdotal.6 In this article, I shall first show how we can test between the competing hypotheses more conclusively and then consider some of the implications of the social brain hypothesis for humans. Finally, I shall briefly consider some of the underlying cognitive mechanisms that might be involved.
Clinical practice guideline: red blood cell transfusion in adult trauma and critical care.

OBJECTIVE
To develop a clinical practice guideline for red blood cell transfusion in adult trauma and critical care.


DESIGN
Meetings, teleconferences and electronic-based communication to achieve grading of the published evidence, discussion and consensus among the entire committee members.


METHODS
This practice management guideline was developed by a joint taskforce of EAST (Eastern Association for Surgery of Trauma) and the American College of Critical Care Medicine (ACCM) of the Society of Critical Care Medicine (SCCM). We performed a comprehensive literature review of the topic and graded the evidence using scientific assessment methods employed by the Canadian and U.S. Preventive Task Force (Grading of Evidence, Class I, II, III; Grading of Recommendations, Level I, II, III). A list of guideline recommendations was compiled by the members of the guidelines committees for the two societies. Following an extensive review process by external reviewers, the final guideline manuscript was reviewed and approved by the EAST Board of Directors, the Board of Regents of the ACCM and the Council of SCCM.


RESULTS
Key recommendations are listed by category, including (A) Indications for RBC transfusion in the general critically ill patient; (B) RBC transfusion in sepsis; (C) RBC transfusion in patients at risk for or with acute lung injury and acute respiratory distress syndrome; (D) RBC transfusion in patients with neurologic injury and diseases; (E) RBC transfusion risks; (F) Alternatives to RBC transfusion; and (G) Strategies to reduce RBC transfusion.


CONCLUSIONS
Evidence-based recommendations regarding the use of RBC transfusion in adult trauma and critical care will provide important information to critical care practitioners.
Bayesian reliability analysis for fuzzy lifetime data

Lifetime data are important in reliability analysis. Classical reliability estimation is based on precise lifetime data. It is usually assumed that observed lifetime data are precise real numbers. However, some collected lifetime data might be imprecise and are represented in the form of fuzzy numbers. Thus, it is necessary to generalize classical statistical estimation methods for real numbers to fuzzy numbers. Bayesian methods have proved to be very useful when the sample size is small. There is little study on Bayesian reliability estimation based on fuzzy lifetime data. Most of the reported works in this area is limited to single parameter lifetime distributions. In this paper, we propose a new method to determine the membership function of the estimates of the parameters and the reliability function of multi-parameter lifetime distributions. An artificial neural network is used to approximate the calculation process of parameter estimation and reliability prediction. The genetic algorithm is used to find the boundary values of the membership function of the estimate of interest at any cut level. This method can be used to determine the membership functions of the Bayesian estimates of multi-parameter distributions. The effectiveness of the proposed method is illustrated with normal and Weibull distributions. © 2005 Elsevier B.V. All rights reserved.
An enterprise application integration methodology for e-government

Purpose – Achieving goals of better integrated and responsive government services requires moving away from stand alone applications toward more comprehensive, integrated architectures. As a result there is a mounting pressure to integrate disparate systems to support information exchange and cross-agency business processes. There are substantial barriers that governments must overcome to achieve these goals and to profit from enterprise application integration (EAI). Design/methodology/approach – In the research presented here we develop and test a methodology aimed at overcoming the barriers blocking adoption of EAI. This methodology is based on a discrete-event simulation of public sector structure, business processes and applications in combination with an EAI perspective. Findings – The testing suggests that our methodology helps to provide insight into the myriad of existing applications, and the implications of EAI. Moreover, it helps to identify novel options, gain stakeholder commitment, let them agree on the sharing of EAI costs, and finally it supports collaborative decision-making between public agencies. Practical implications – The approach is found to be useful for making the business case for EAI projects, and gaining stakeholder commitment prior to implementation. Originality/value – The joint addressing of the barriers of public sector reform including the transformation of the public sector structure, gaining of stakeholders’ commitment, understanding EAI technology and dependencies between cross-agency business processes, and a fair division of costs and benefits over stakeholders.
MACROECONOMIC VARIABLES AND STOCK MARKET RETURNS IN GHANA: ANY CAUSAL LINK?

The purpose of the study is to examine the existence of causality between macroeconomic variables and stock returns in Ghana. The study employs monthly time series data spanning the period January 1995 to December 2010. Unit root test is performed using ADF, PP and KPSS tests. Then, Vector Error Correction (VECM) model is used to establish long-run and short-run relationship between stock performance and macroeconomic variables. In order to determine the existence or otherwise of causality, the Granger Causality tests is performed. Impulse response functions and forecast error variance decomposition are used to assess the stability of the relationship between stock returns and macroeconomic variables over time. The study reveals that a significant long run relationship exists between stock returns and inflation, money supply and Foreign Direct Investment (FDI). In the short-run, a significant relationship exists between stock returns and macroeconomic variables such as interest rate, inflation and money supply. In the short-run the relationship between stock returns and FDI is only imaginary. Our VECM coefficient shows that it takes approximately 20 months for the stock market to fully adjust to equilibrium position in case a macroeconomic shock occurs. Lastly, a causal relationship running from inflation and exchange rate to stock returns has been established. Then also, a causal relationship running from stock returns to money supply, interest rate and FDI has also been revealed. The findings imply that arbitrage profit opportunities exist in the Ghana stock market contrary to the dictates of the Efficient Market Hypothesis (EMH). In terms of original value,among the studies Asian Economic and Financial Review journal homepage: http://aessweb.com/journal-detail.php?id=5002 Asian Economic and Financial Review, 2013, 3(8):1044-1062 1045 done on the topic in Ghana so far, this is the only study that incorporates dividend in the computation of returns on the Ghana Stock Exchange.
Analysis and Review of Encryption and Decryption for Secure Communication

The Process of Encryption and Decryption is performed by using Symmetric key cryptography and public key cryptography for Secure Communication. In this paper, we studied that how the process of Encryption and Decryption is perform in case of Symmetric key and public key cryptography using AES and DES algorithms and modified RSA algorithm.
Randomized clinical trial to evaluate the effect of a supervised exercise training program on readmissions in patients with myocardial ischemia: a study protocol

BACKGROUND
In recent decades, several studies have assessed the value of cardiac rehabilitation as secondary prevention and have reported substantial reductions in readmissions. However, conclusive evidence is scarce. The present study aims to evaluate the efficacy of a supervised exercise training program for improving percentages of hospital readmission for cardiac causes in patients with myocardial ischemia in the first year after a cardiac event. The effect on all-cause readmission, all-cause mortality, functional capacity, quality of life and adherence to regular exercise is also discussed.


METHODS/DESIGN
This study will be conducted as a randomized controlled trial. Eligible patients will be randomly assigned to a control group receiving standard care or to an intervention group which, in addition to standard care, will take part in a supervised exercise training program consisting of three hours a week (spread over three alternate days) of supervised exercise training for 10 weeks. Both groups will perform an exercise stress test and a blood test during the first and third month after hospital discharge. The follow-up period will be 12 months after hospital discharge. The primary outcome measures will be the percentage of patients readmitted, total number of readmissions and length of hospitalization for cardiac disease during the first year after hospital discharge, and time to first hospital admission for cardiac disease.


DISCUSSION
A representative group of hospitalized patients after myocardial ischemia will be studied in order to provide comprehensive data on the potential impact of a supervised exercise training program on hospital readmission rates.


TRIAL REGISTRATION
Current Controlled Trials ISRCTN57634424.