Miracle-dz/UniFAR-FTUs huggingface dataset:
Color, Structure, and Star Formation History of Dwarf Galaxies over the Last ~3 Gyr with GEMS and SDSS

We present a study of the colors, structural properties, and star formation histories for a sample of ~1600 dwarfs over look-back times of ~3 Gyr (z = 0.002-0.25). The sample consists of 401 distant dwarfs drawn from the Galaxy Evolution from Morphologies and SEDs (GEMS) survey, which provides high-resolution Hubble Space Telescope (HST) Advanced Camera for Surveys (ACS) images and accurate redshifts, and also 1291 dwarfs at 10-90 Mpc compiled from the Sloan Digital Sky Survey (SDSS). The sample is complete down to an effective surface brightness of 22 mag arcsec-2 in z and includes dwarfs with Mg = -18.5 to -14 mag. Rest-frame luminosities in Johnson UBV and SDSS ugr filters are provided by the COMBO-17 survey, and structural parameters have been determined by Sérsic fits. We find that the GEMS dwarfs are bluer than the SDSS dwarfs by ~0.13 mag in g - r, which is consistent with the color evolution over ~2 Gyr of star formation histories involving moderate starbursts and long periods of continuous star formation. The full color range of the samples cannot be reproduced by single starbursts of different masses or long periods of continuous star formation alone. Furthermore, an estimate of the mechanical luminosities needed for the gas in the GEMS dwarfs to be completely removed from the galaxies shows that a significant number of low-luminosity dwarfs are susceptible to such a complete gas loss, if they would experience a starburst. On the other hand, a large fraction of more luminous dwarfs is likely to retain their gas. We also estimate the star formation rates per unit area for the GEMS dwarfs and find good agreement with the values for local dwarfs.
DiverGene: Experiments on controlling population diversity in genetic algorithm with a dispersion operator

We present diverGene - a novel, diversity-aware population selection operator for genetic algorithm - to be used especially for particularly complex and multi-criteria optimisation problems. Genetic algorithm is one of the most known evolutionary algorithms for solving hard optimisation problems. Many attempts have been made to improve its convergence rate and quality of the result. In this paper we propose a novel extension of the selection operator that makes it possible to control the level of diversity in the population. We discuss its theoretical background, including its computational hardness and propose an efficient way of computing it. The approach is implemented and tested on three hard optimisation problems: Knapsack Problem, Travelling Salesman Problem and a relatively new Travelling Thief Problem that might be viewed as the composition of the latter two. We report experimental results that seem to indicate that the novel approach has a potential to improve the quality of the results for some hard optimisation problems.
Passive Network Discovery for Real Time Situation Awareness

Abstract : Network security analysts are confronted with numerous ambiguities when interpreting alerts produced by security devices. Even with the increased accuracy of these tools, analysts still have to sort through a tremendous number of potential security events in order to maintain the desired level of assurance. This paper describes how passive network discovery and persistent monitoring can provide significant contextual information valuable to network security professionals responsible for protecting the network. Techniques discussed include the capability to discover active nodes, their operating systems, the role they carry out, their system uptime, the services they offer, the protocols they support, and their IP network configuration. An attractive feature of this approach is that it focuses on mechanisms that do not rely on access to user data. While this is rarely a concern for the intruder, it can be of the utmost importance to the security analyst. One of the main interests in using a passive approach is that the information gathering process has no impact on the bandwidth or on the monitored assets. This is in contrast with active scanning techniques that are often noisy and intrusive. Passive techniques can be used at all times, allowing near real-time awareness of the security posture of ever-changing networks, and thus helping network administrators remain in control and anticipate upcoming security problems. A network monitoring prototype has been developed to test the techniques described in this paper.
Research and applications: Patient-level temporal aggregation for text-based asthma status ascertainment

OBJECTIVE To specify the problem of patient-level temporal aggregation from clinical text and introduce several probabilistic methods for addressing that problem. The patient-level perspective differs from the prevailing natural language processing (NLP) practice of evaluating at the term, event, sentence, document, or visit level. METHODS We utilized an existing pediatric asthma cohort with manual annotations. After generating a basic feature set via standard clinical NLP methods, we introduce six methods of aggregating time-distributed features from the document level to the patient level. These aggregation methods are used to classify patients according to their asthma status in two hypothetical settings: retrospective epidemiology and clinical decision support. RESULTS In both settings, solid patient classification performance was obtained with machine learning algorithms on a number of evidence aggregation methods, with Sum aggregation obtaining the highest F1 score of 85.71% on the retrospective epidemiological setting, and a probability density function-based method obtaining the highest F1 score of 74.63% on the clinical decision support setting. Multiple techniques also estimated the diagnosis date (index date) of asthma with promising accuracy. DISCUSSION The clinical decision support setting is a more difficult problem. We rule out some aggregation methods rather than determining the best overall aggregation method, since our preliminary data set represented a practical setting in which manually annotated data were limited. CONCLUSION Results contrasted the strengths of several aggregation algorithms in different settings. Multiple approaches exhibited good patient classification performance, and also predicted the timing of estimates with reasonable accuracy.
Baseband Equivalent Volterra Series for Digital Predistortion of Dual-Band Power Amplifiers

This paper proposes a new dual-band baseband equivalent (BBE) Volterra model devised to predict the behavior of dual-band power amplifiers (PAs) and/or to linearize their response. A series of derivations were applied to the original continuous passband Volterra-series expression to uncover a simple formulation that related the BBE envelopes of the output signals in each band to those at the input in the discrete domain. This yielded an inherently low-complexity dual-band Volterra-series model that does not require the empirical pruning commonly applied to the low-pass equivalent Volterra series. The proposed model was successfully applied to digitally predistort and linearize a dual-band 45-W class-AB GaN PA driven with different dual-band dual-standard test signals. For each band, the model necessitated less than 25 coefficients to reduce the adjacent channel leakage power ratio ACLR by up to 25 dB.
A energy efficient multi-dimension model for system control in smart environment systems

A smart environment system should automatically control the devices according to the sensing information and users' requirements so as to keep the environmental elements (e.g., temperature, light) within the desired range. System control with minimum power is one key issue in such a system. In this paper, we propose a multi-dimension model for system control. In this model, each environmental element is abstracted into a dimension, such that a service with conditions and targets can be formulated as a multi-dimensional service space, and a smart environment with many services may map to a comprehensive multi-dimensional service space through space computation. Based on this model, we propose a minimum power adjustment algorithm for energy-efficient scheduling in smart environment, which transforms the optimal control problem into the problem of the shortest weighted distance of point-to-polygonal in multi-dimensional space. Theoretical analysis and experimental results show that the proposed model is effective and efficient in energy-efficient system control. It is important to point out that the proposed algorithms are scalable when the number of dimensions or services increases.
A soccer field tracking method with wire frame model from TV images

This paper proposes a tracking method of soccer field area in a soccer video captured from TV. The camera taking the soccer game video is controlled by three parameters: its mount position, the angle, and the magnification. In order to estimate these three parameters, the proposed method designs a wire frame model, which represents the official layout of the soccer field lines; and by the wire frame model matching with the field area in the video, the above three parameters can be estimated, even if the soccer video includes the camera panning, zooming, etc. By using the estimated parameters, we can accurately obtain where the field area corresponds in the actual soccer field. Some experiments in tracking the field area in actual soccer videos are performed and their results verify the high performance of the proposed method.
University men's reactions to hypothetical confrontations of sexual harassment.

Confronting sexual harassers has been proposed as a method for responding to sexual harassment. However, research has found that women often do not confront perpetrators because they are afraid of experiencing negative social costs (Shelton & Stewart, 2004). In order to begin an examination of whether women’s fears of confronting are justified, this study investigated the effect of type of sexual harassment situation and type of confrontation style utilized in vignettes on men’s reported cognitive, emotional, and behavioural reactions. Additionally, factors thought to predict behavioural reactions to confrontations were analysed. Participants were one hundred and fifty university men. Type of sexual harassment was found to have an effect on men’s reported feelings, opinions of the confronter, avoiding/isolating behaviours and negative verbal behaviours. Type of confrontation style had an effect on avoiding/isolating behaviour. It was also found that men’s attitudes, feelings, and opinions of the confronter predicted their behavioural
The Pathologic Characteristics of Pingueculae on Autofluorescence Images

Purpose To analyze the autofluorescence (AF) properties of pinguecula using cobalt-blue and yellow filters and to investigate the nature and pathogenesis of pingueculae using histochemical and immunohistochemical staining. Methods Fifty pingueculae in 40 patients were included in this study. AF of the pingueculae was observed and analyzed using a cobalt-blue filter with an additional yellow filter on a slit-lamp. Hematoxylin-eosin and immunohistochemical stainings were performed on surgical specimens of pingueculae that were prepared from each patient. Immunohistochemical staining included Congo red, Oil Red O, periodic acid-Schiff (PAS), Masson's trichrome, transglutaminase-2 (TG-2), mesenchymal stem cell markers CD29 (β-1-integrin), and CD34. Results AF images revealed hyper-AF in the pinguecula area. The AF lesions of pingueculae showed superficial punctuate erosions and avascular lesions. Deposition of eosinophilic and amorphous materials in the subepithelial layer of the pinguecula were observed on hematoxylin-eosin staining. Historeactivities to Congo red, PAS, Oil Red O, alcian blue, and Masson's trichrome were not detected, but immunoreactivities to CD29, CD34, and TG-2 were detected in the pingueculae with AF. However, CD29, CD34, and TG-2 were not detected in the pingueculae without AF. Conclusions The AF of pingueculae may be related to CD29, CD34, and TG-2. We suggest that pingueculae with AF have a different pathogenesis compared to pingueculae without AF.
Does variation in quality scores result from variation in visual attention

Novel research in image quality assessment attempts to further improve the reliability of objective metrics by taking into account visual attention of the human visual system. Modeling visual attention in an objective metric, however, is not yet a trivial task, partly because earlier work has shown that the added value of including visual attention is content dependent. In this paper, we attempt to better understand the impact of human visual attention on image quality scoring by investigating the variation in visual attention between observers, and to what extent such variation affects the reliability of scoring the image quality. The results, however, show that the relationship between variation in visual attention and variation in quality scores is weak
Relieving hotspots in data center networks with wireless neighborways

Recent studies show that the 60GHz wireless technology could help resolving the hotspot issue in data center networks (DCNs). However, transmissions over 60GHz suffer from limitations of short transmission range and blockage, which makes it a new challenge how to appropriately establish wireless links in the DCN. In this paper, we propose to integrate wireless links into the DCN with the wireless neighborway scheme. Each top-of-rack switch (ToR) has multiple 60GHz wireless links connecting to its neighboring ToRs, which are termed as neighborways. The elephant flow from the sending ToR can be partially offloaded through neighborways, which are then delivered to the ToRs around the receiving ToR through wired links of the DCN, and finally converged to the receiving ToR. The fundamental challenge for the design is how to prevent the offloaded traffics from forming new hotspots in the network fabric. To this end, we developed a wireless network planning solution with corresponding IP address assignment and traffic engineering scheme, which can leverage the potential underutilized wired links in the DCN and meanwhile avoid forming new hotspots. The simulation results show that the proposed scheme can notably relieve the hotspots in the DCN.
Automatic Personalization in E-Learning Based on Recommendation Systems: An Overview

Web based learning environments are being increasingly used at a large scale in the education area. This situation has brought a dramatic growth in the amount of educational resources and services incorporated continuously in these systems, and related access and usage of this educational content by a diversity of learners. However, the delivery of this educational content is generally done in the same way for all learners without giving any special attention to the different consumption styles or differences between their profiles and individual needs. Therefore, providing personalization in e-learning systems has to be considered as a necessity and not an option. Recommending suitable links represents an instance of adaptive navigation support technology. E-learning recommender systems are used to locate relevant educational Web objects that better match the learner’s profile and interests, this requires the ability of a system to predict learner’s needs and preferences. Therefore, recommendation systems need to use Web mining techniques in one or more phases of the recommendation process, especially in the modelling and pattern discovery phase. Most emergent recommendation systems in e-learning tend to rely on automated detection of student’s preferences and needs since it is more efficient and attractive to provide needed support to students without requesting any explicit information from them. In this chapter, we present an overview of personalization in e-learning based on recommendation systems and Web mining techniques.
Outsourcing Relationships: Designing 'Optimal' Contracts: A Principal-Agent-Theoretic Approach

Information Systems literature emphasizes the importance of efficient contracts for managing outsourcing relationships. However, there is a lack of proven and tested contract designs in theory as well as in practice. With the help of Economic Theory we analyze the underlying dynamics of an outsourcing relationship. Based on mathematical Principal-Agent-Theory we aim at answering the following questions: (1) ‘what are the characteristics of an ‘optimal’ outsourcing contract? ’ and (2) ‘how can the Outsourcer contractually implement incentives for the Service Provider? ’. Our theoretical findings stress that within an ‘optimal’ contract the marginal utilities of both parties involved have to be proportional. For practical implications this means that an increase of the Service Provider’s profit has to be accompanied by a decrease in the Outsourcer’s costs. To accomplish this we show how incentives can contractually be implemented as suggested by Principal-Agent-Theory. We test our findings based on a single case study research.
A Segmental Approach to Imaging of Sports-Related Injuries of the Pediatric Elbow

Context: The imaging of pediatric sports injuries of the elbow requires an understanding of the interaction between biomechanical forces common in sports and the developing skeleton. Evidence Acquisition: A PubMed search was performed using the terms elbow, radiology, and sports with the search limited to children up to 18 years of age. No limits were set on the range of years searched. Articles were reviewed for relevance with an emphasis of the changing nature of sports injuries about the pediatric elbow. Results: A clear progression of injuries about the elbow can be identified as the skeleton matures. Sports most commonly associated with injuries in the pediatric age group were baseball and gymnastics. Conclusions: Most pediatric sports injuries result from overhand throwing, especially in baseball or gymnastics. The manifestation of the injuries shifts as the physes progress toward closure.
SVM-based Filtering of E-mail Spam with Content-specic Misclassication Costs

We address the problem of separating legitimate emails from uncolicited ones in the context of a large-scale operation, where the diversity of user accounts is very high, while misclassiÞcation costs are content-dependent and highly asymmetric. A category speciÞc cost model is proposed and several effective methods of training a cost sensitive Þlter are studied, using a Support Vector Machine (SVM) as the base classiÞer. Clear beneÞts of explictly accounting for varied misclassiÞcation costs, either during training or as a form of post-processing, are shown.
Garment Personalization via Identity Transfer

A new system provides a virtual experience akin to trying on clothing. It clones the user's photographic image into a catalog of images of models wearing the desired garments. Simple offline training extracts the user's head. Segmentation accurately separates the face, hair, and background, employing both a three-kernel statistical model and graph cuts. The system adjusts the resulting image's skin color according to a statistical model and relights the head via spherical harmonics. Finally, using a parametric model, the system warps the clone's body dimensions to fit the user's dimensions. This creates high-quality compositions of the user's image and the given garment.
Dynamic analysis of Clavel's Delta parallel robot

Some iterative matrix relations for the geometric, kinematic and dynamic analysis of a Delta parallel robot are established in this paper. The prototype of this manipulator is a three degree of freedom spatial mechanism, which consists of a system of parallel chains. Supposing that the position and the translation motion of the platform are known, an inverse dynamic problem is solved using the virtual powers method. Finally, some recursive matrix relations and some graphs for the moments and the powers of the three active couples are determined.
Bisphenol A and Adiposity in an Inner-City Birth Cohort

Background: Early-life exposure to the endocrine disruptor bisphenol A (BPA) may contribute to the development of obesity. Prospective evidence in humans on this topic is limited. Objectives: We examined prenatal and early-childhood BPA exposures in relation to childhood measures of adiposity in the Columbia Center for Children’s Environmental Health (CCCEH) New York City birth cohort. Methods: BPA concentrations were measured in prenatal (n = 375) and child ages 3 (n = 408) and 5 years (n = 518) spot urine samples. Childhood anthropometric and bioelectrical impedance outcomes included body mass index z-scores (BMIZ) at 5 and 7 years, and fat mass index (FMI), percent body fat (%BF), and waist circumference (WC) at 7 years. Associations were evaluated using multiple linear regression with continuous and tertile BPA concentrations. Results: Prenatal urinary BPA concentrations were positively associated with child age 7 FMI (β = 0.31 kg/m2; 95% CI: 0.01, 0.60, p = 0.04), %BF (β = 0.79; 95% CI: 0.03, 1.55, p = 0.04), and WC (β = 1.29 cm; 95% CI: 0.29, 2.30, p = 0.01), but not BMIZ, or change in BMIZ between ages 5 and 7 years (all p-values > 0.1). FMI results were sex-specific. Child urinary BPA concentrations were not associated with child anthropometric outcomes (all p-values > 0.05). Conclusions: Analyses of the CCCEH longitudinal birth cohort found associations between prenatal urinary BPA concentrations and FMI, %BF, and WC. Our results suggest that prenatal BPA exposure may contribute to developmental origins of adiposity. These findings are consistent with several prior studies, raising concern about the pervasiveness of BPA. Citation: Hoepner LA, Whyatt RM, Widen EM, Hassoun A, Oberfield SE, Mueller NT, Diaz D, Calafat AM, Perera FP, Rundle AG. 2016. Bisphenol A and adiposity in an inner-city birth cohort. Environ Health Perspect 124:1644–1650; http://dx.doi. org/10.1289/EHP205
A Study of Two Graph Algorithms in Topic-driven Summarization

We study how two graph algorithms apply to topic-driven summarization in the scope of Document Understanding Conferences. The DUC 2005 and 2006 tasks were to summarize into 250 words a collection of documents on a topic consisting of a few statements or questions. Our algorithms select sentences for extraction. We measure their performance on the DUC 2005 test data, using the Summary Content Units made available after the challenge. One algorithm matches a graph representing the entire topic against each sentence in the collection. The other algorithm checks, for pairs of open-class words in the topic, whether they can be connected in the syntactic graph of each sentence. Matching performs better than connecting words, but a combination of both methods works best. They also both favour longer sentences, which makes summaries more fluent.