Miracle-dz/UniFAR-FTUs huggingface dataset:
THE ZURICH ENVIRONMENTAL STUDY OF GALAXIES IN GROUPS ALONG THE COSMIC WEB. III. GALAXY PHOTOMETRIC MEASUREMENTS AND THE SPATIALLY RESOLVED COLOR PROPERTIES OF EARLY- AND LATE-TYPE SATELLITES IN DIVERSE ENVIRONMENTS

We present photometric measurements for the galaxies—and when possible their bulges and disks—in the 0.05 < z < 0.0585 groups of the Zurich Environmental Study (ZENS); these measurements include (B − I) colors, color gradients and maps, color dispersions, as well as stellar masses and star formation rates. The ZENS galaxies are classified into quenched, moderately star-forming, and strongly star-forming using a combination of spectral features and far-UV-to-optical colors; this approach optimally distinguishes quenched systems from dust-reddened star-forming galaxies. The latter contribute up to 50% to the (B − I) “red sequence” at ∼1010 M☉. At fixed morphological or spectral type, we find that galaxy stellar masses are largely independent of environment, and especially of halo mass. As a first utilization of our photometric database, we study, at fixed stellar mass and Hubble type, how (B − I) colors, color gradients, and color dispersion of disk satellites depend on group mass MGROUP, group-centric distance R/R200, and large-scale structure overdensity δLSS. The strongest environmental trend is found for disk-dominated satellites with MGROUP and R/R200. At M ≲ 1010 M☉, disk-dominated satellites are redder in the inner regions of the groups than in the outer parts. At M ≳ 1010 M☉, these satellites have shallower color gradients in higher mass groups and in the cores of groups compared with lower mass groups and the outskirts of groups. Stellar population analyses and semi-analytic models suggest that disk-dominated satellites undergo quenching of star formation in their outer disks, on timescales τquench ∼ 2 Gyr, as they progressively move inside the group potential.
Creative clusters in Europe: a microdata approach

Creative industries are highly concentrated forming clusters. One of the main problems for the identification of clusters of creative industries in Europe is the lack of data, constrained in practice to regions (NUTS 2) and influenced by the heterogeneity in the definition of NUTS across countries. This research uses firm-level data geo-referenced at address level and geostatistical modeling to identify clusters of creative industries in fifteen European countries. The procedure is independent of administrative divisions and national boundaries and allows to produce a precise geography of the clusters of creative industries in Europe.
Phyto-Mediated Photo Catalysed Green Synthesis of Silver Nanoparticles Using Durio Zibethinus Seed Extract: Antimicrobial and Cytotoxic Activity and Photocatalytic Applications

In the present study, we have developed a green approach for the synthesis of silver nanoparticles (DSAgNPs) using aqueous extract of Durio zibethinus seed and determined its antibacterial, photocatalytic and cytotoxic effects. Surface plasmon resonance confirmed the formation of DSAgNPs with a maximum absorbance (λmax) of 420 nm. SEM and TEM images revealed DSAgNPs were spherical and rod shaped, with a size range of 20 nm and 75 nm. The zeta potential was found to be −15.41 mV. XRD and EDX analyses confirmed the nature and presence of Ag and AgCl. DSAgNPs showed considerable antibacterial activity, exhibited better cytotoxicity against brine shrimp, and shown better photocatalytic activity against methylene blue. Based on the present research work, it can be concluded that DSAgNPs could be used in the field of water treatment, pharmaceuticals, biomedicine, biosensor and nanotechnology in near future.
Relationship between asphalt composition and thermal behaviour for solar energy collection

Using asphalt to harvest solar energy is an ideal and sustainable solution to the problems involved with increasing energy demand and using fossil fuels. Asphalt has the most heat absorbent colour and is already covering large surfaces in and between urban areas. Asphalt solar collection systems have not been implemented on a large scale worldwide. This is because the current energy/heat collection efficiency does not outweigh the costs involved in constructing on road level and under/within adjacent buildings which can use the energy. This paper is based on testing and evaluation of variations in asphalt composition which can provide a greater quantity of energy/heat in a given time, to increase effectiveness of energy collection to make this system more feasible. Also there is a discussion of other research on asphalt thermal properties, characteristics and factors other than asphalt involved in energy collection. The potential application of this research is also discussed in this paper. The results showed that an increase of 1% in bitumen can increase the maximum temperature of asphalt by almost 14%. In addition, decreasing void ratio, using other aggregates and larger aggregate sizes can increase the maximum temperature and thermal conductivity.
Evidence for a southward autumn migration of nocturnal noctuid moths in central Europe

ABSTRACT Insect migrations are spectacular natural events and resemble a remarkable relocation of biomass between two locations in space. Unlike the well-known migrations of daytime flying butterflies, such as the painted lady (Vanessa cardui) or the monarch butterfly (Danaus plexippus), much less widely known are the migrations of nocturnal moths. These migrations – typically involving billions of moths from different taxa – have recently attracted considerable scientific attention. Nocturnal moth migrations have traditionally been investigated by light trapping and by observations in the wild, but in recent times a considerable improvement in our understanding of this phenomenon has come from studying insect orientation behaviour, using vertical-looking radar. In order to establish a new model organism to study compass mechanisms in migratory moths, we tethered each of two species of central European Noctuid moths in a flight simulator to study their flight bearings: the red underwing (Catocala nupta) and the large yellow underwing (Noctua pronuba). Both species had significantly oriented flight bearings under an unobscured view of the clear night sky and in the Earth's natural magnetic field. Red underwings oriented south-southeast, while large yellow underwings oriented southwest, both suggesting a southerly autumn migration towards the Mediterranean. Interestingly, large yellow underwings became disoriented on humid (foggy) nights while red underwings remained oriented. We found no evidence in either species for a time-independent sky compass mechanism as previously suggested for the large yellow underwing. Summary: During autumn in central Europe, red underwing and large yellow underwing moths make a southward oriented nocturnal migration, although on foggy evenings, the latter species becomes disoriented.
Cavitation analysis of a double acting podded drive during ice milling

Propeller ice interaction is a complex phenomenon, which relies on innovative and complex experimental research in dedicated ice tank facilities. Whilst the ice tanks model the contact forces with good agreement, the hydrodynamic loading is often only assumed due to the inability to scale atmospheric pressure during these experiments. A small amount of research is however being conducted in cavitation tunnels using innovative methods to represent full scale ice milling conditions. Propulsor ice interaction tests in a cavitation tunnel are therefore both novel and uncommon due to their complexity. The Emerson Cavitation Tunnel at the University of Newcastle (ECT) has pioneered a series of ice milling tests within a cavitation tunnel using model ice. These ice milling tests allow an ice propulsor to experience correctly scaled cavitation numbers as a propeller interacts with ice. In all of the conditions tested, the current research observed presence and influence of cavitation and showed it to be a significant factor, something that is missing from standard ice tank tests. The work published in this paper forms part of a PhD research into the topic by the principal author [1]. INTRODUCTION The design and construction of ice capable vessels is currently undergoing rapid expansion. At the forefront of this boom are the ice-capable double acting ships (DAS) outfitted with podded drives as reported by Sasaki et al. [2]. Since the launch of the double acting tanker, the DAS design has matured to include, container ships, tug boats and unconventional vessels like the USCG Mackinaw shown in Figure 1. The DAS concept is innovative; it allows vessels to advance stern first through level ice up to 1.5m thick at relatively even speeds of up to 3 knots. This continuous advance minimizes ice damage to the propulsor by avoiding the usual “back and ram” maneuvers that conventional shaft driven icebreakers must perform. Figure 1: Double Acting ship USCG Mackinaw [3] Despite the numerous benefits to this technology, the podded drives operate in a low-pressure wake of ice covered flows, which increases the likelihood of cavitation during ice blockage and ice milling. Under these circumstances the effect of cavitation during milling will be an essential factor for the performance and design of podded propulsors. To mitigate against these complex design conditions of low-pressure ice interaction, designers rely on physical model testing to make
Accuracy, certainty and surprise: a prediction market on the outcome of the 2002 FIFA World Cup

In this chapter, we present our empirical investigation of the forecasting accuracy of a prediction market experiment drawn on the outcome of the World Cup 2002. We analyse the predictive accuracy of 64 markets and compare to bookmakers’ quotes and chance as benchmarks. We revisit the evaluation of Schmidt and Werwatz (Chapter 16) and compare our results directly to their findings. In addition, we propose a new method for testing predictive accuracy by means of a non-parametric test for the similarity of probability distributions and we evaluate the incorporation of information in market prices by comparing pre-match and half-time price data. We find a reversed favourite-longshot bias when analysing market prices before the start of the match and this bias does not disappear with the inflow of new information until half-time. Unlike the market based predictions bookmakers appear to be perfectly calibrated. Since there were substantial deviations in outcome between the 2000 European Championship and our data, we offer possible explanations for the much worse performance of the 2002 World Cup prediction market. Consistent with Schmidt and Werwatz (Chapter 16) prediction markets do assign relatively higher probabilities to the favourite when compared to the odds-setters. Together with a long streak of surprising outcomes this fact appears most likely to be responsible for the predictive inaccuracy.
WEIGHTING QUERY TERMS USING WORDNET ONTOLOGY

Term-weighting techniques are responsible for giving a weight for each query term to determine its significance. This term significance is based on the generality or specificity of that term. Traditional weighting models, such as the Inverse Document Frequency (IDF), measure the generality/specificity of terms through document collection statistics. This paper presents a technique that employs the WordNet ontology to determine the significance of query terms without depending on document collection statistics. The experiments are carried out on the WT2g document collection under the Terrier Information Retrieval Platform.
Belowground annual ring growth coordinates with aboveground phenology and timing of carbon storage in two tallgrass prairie forb species.

PREMISE OF THE STUDY Herb chronology, the study of belowground annual growth rings in perennial forbs, has much potential as a tool for monitoring plant growth as a function of environment. To harness this potential, understanding of the coordination between ring ontogeny, aboveground phenology, and the temporal allocation of carbon products belowground in herbaceous forbs must be improved. METHODS We investigated these relationships in two southern United States tallgrass prairie perennial forb species, Asclepias viridis and Lespedeza stuevei, making monthly excavations for a year. KEY RESULTS Belowground xylogenesis began when starch reserves were at their seasonal low in the spring as shoots reached maximum height. The highest relative radial growth of the ring occurred concurrently with replenishment of root starch reserves in early summer. Xylogenesis concluded with leaf senescence in late summer and belowground starch reserves near saturation. CONCLUSIONS By demonstrating that ring ontogeny is tied to early summer starch replenishment, our results illustrate the mechanisms behind previous findings where ring width was highly correlated with summer climatic conditions for these two species. This study provides a new physiological link between how ring chronologies in herbs often accord with growing-season environment; further dissecting this phenomenon is vital in unlocking the potential of herb chronology.
Frequently recorded sensor data may correctly provide health status of cows if data are handled carefully and errors are filtered away

Description of the subject. The implementation of sensor based decision support in commercial dairy herds is highly dependent on having reliable systems. Problems with sensors give missing and noisy data hampering their use. Also, the presentation of results needs to be in a form which is simple and useful. These issues were addressed using a mastitis sensor and decision support as example. Objectives. This study aims at providing and evaluating a modular system applicable to the pipeline from sensor to decision support. Method. The case of mastitis was chosen as it is of economic importance and also affects welfare of cows, and because we have worked with a commercial sensor. The problems with sensors causing missing data and noise are described and a range of filtering and monitoring modules are shown to be important to make systems functional for herd management purposes. On top of this a solid method needs to be used to interpret and present data to end users, in terms of easy to read categories. Results. Filtering and pre-adjustments of raw data are important in making algorithms robust and reliable for daily use. Re-definition of traits is needed going from traditional few groups to continuous definitions, and then to new action oriented health classes. Also, for this case focusing on mastitis, assignment to “permanently sick” groups can be helpful in keeping focus on new acute cases. Conclusions. The combined use of filtering, fix-up routines and time series models leading into action oriented categories is needed to provide simple and robust decision support. The systems may be vastly improved by opening for transmission of data between user groups and to common databases – also with a few to use data in genetic selection.
Genetic similarity and variation in the cultured and wild crucian carp (Carassius carassius) estimated with random amplified polymorphic DNA

Random amplified polymorphic DNA (RAPD) analysis based on numerous polymorphic bands have been used to investigate genetic similarity and diversity among and within two cultured and wild populations represented by the species crucian carp (Carassius carassius). From RAPD analysis using five primers, a total of 442 polymorphic bands were obtained in the two populations and 273 were found to be specific to a wild population. 169 polymorphic bands were also produced in wild and cultured population. According to RAPD-based estimates, the average number of polymorphic bands in the wild population was approximately 1.5 times as diverse as that in cultured. The average number of polymorphic bands in each population was found to be different and was higher in the wild than in the cultured population. Comparison of banding patterns in the cultured and wild populations revealed substantial differences supporting a previous assessment that the populations may have been subjected to a long period of geographical isolation from each other. The values in wild population altered from 0.21 to 0.51 as calculated by bandsharing analysis. Also, the average level of bandsharing values was 0.40±0.05 in the wild population, compared to 0.69±0.08 in the cultured. With reference to bandsharing values and banding patterns, the wild population was considerably more diverse than the cultured. Knowledge of the genetic diversity of crucian carp could help in formulating more effective strategies for managing this aquacultural fish species and also in evaluating the potential genetic effects induced by hatchery operations. (Asian-Aust. J. Anim. Sci. 2002. Vol 15, No. 4 : 470-476)
CONTINUOUS WORKBENCH OF SIMULATION & DESIGN SOFTWARE TOOLS FOR EDUCATIONAL APPLICATIONS

The state-of-the-art MOS models for simulation and device simulators are depicted. The design workflow from process via device to circuit simulation is shown. Comparison between the simulation results of the device simulator Minimos-NT and the circuit simulator Spectre are provided. On the example of a ring oscillator circuit the coherence between these simulators is demonstrated. The existence of such continuous workbench is beneficial for both educational and industrial purposes.
A Statistical Framework for DiscreteVisual Features Modeling and Classification

Multimedia contents are mostly described in discrete forms, so analyzing discrete data becomes an important task in many image processing and computer vision applications. One of the most used approaches for discrete data modeling is the finite mixture of multinomial distributions, considering that the events to model are independent. It, however, fails to capture the true nature in the case of sparse data and leads generally to poor biased estimates. Different smoothing techniques that reflect prior background knowledge are proposed to overcome this issue. Generalized Dirichlet distribution has suitable covariance structure, so it offers flexibility in parameter estimation; therefore, it has become a favorable choice as a prior. This specific choice, however, has its problems mainly in the estimation of the parameters, which appears to be a laborious task and can deteriorate the estimates accuracy when we consider the maximum likelihood (ML) approach. In this thesis, we propose an unsupervised statistical approach to learn structures of this kind of data. The central ingredient in our model is the introduction of the generalized Dirichlet distribution mixture as a prior to the multinomial. An estimation algorithm for the parameters based on leave-one-out (LOO) likelihood and empirical Bayesian inference is developed. This estimation algorithm can be viewed as a hybrid expectation-maximization (EM) which alternates EM iterations with Newton-Raphson iterations using the Hessian matrix. We also propose the use of our model as a parametric basis for support vector machines (SVM) within a hybrid Generative/discriminative framework. Through a series of experiments involving scene modeling and classification using visual words and color texture modeling, we show the efficiency of the proposed approaches.
A Spatial Analytic Approach to Examining Property Tax Equity After Assessment Reform in Indiana

Scholars, public officials, and property owners have debated the administration of the property tax for decades. Scholars generally contend that the property tax is a good local revenue source while public officials and property owners loathe it. Much of the contention regarding the tax comes from equity issues related to assessment practices. This study examines an assessment process that was revamped from a decidedly unfair formula-based assessment to a market-value-in-use assessment. The objective of the study is to evaluate the new process through traditional measures and contemporary spatial analytic measures. The study contributes to the literature through its introduction of “spatial equity” measures.
The Green Bank Ammonia Survey: Unveiling the Dynamics of the Barnard 59 Star-forming Clump

Understanding the early stages of star formation is a research field of ongoing development, both theoretically and observationally. In this context, molecular data have been continuously providing observational constraints on the gas dynamics at different excitation conditions and depths in the sources. We have investigated the Barnard 59 core, the only active site of star formation in the Pipe Nebula, to achieve a comprehensive view of the kinematic properties of the source. This information was derived by simultaneously fitting ammonia inversion transition lines (1, 1) and (2, 2). Our analysis unveils the imprint of protostellar feedback, such as increasing line widths, temperature, and turbulent motions in our molecular data. Combined with complementary observations of dust thermal emission, we estimate that the core is gravitationally bound following a virial analysis. If the core is not contracting, another source of internal pressure, most likely the magnetic field, is supporting it against gravitational collapse and limits its star formation efficiency.
Hemodynamic analysis of patients in intensive care unit based on diffuse optical spectroscopic imaging system

Diffuse optical spectroscopic imaging (DOSI) is a technique to assess the spatial variation in absorption and scattering properties of the biological tissues and provides the monitoring of changes in concentrations of oxy-hemoglobin and deoxy-hemoglobin. In our preliminary study, the temporal tracings of hemodynamic oxygenation are measured with DOSI and venous occlusion test (VOT) from normal subjects, patients with heart failure and patients with sepsis in intensive care unit (ICU). In experiments, the obvious differences of hemodynamic signals can be observed among the three groups. The physiological relevance of VOT hemodynamics with respect to diseases is also discussed in this paper.
Machine Translation : From Statistical to modern Deep-learning practices

Machine translation (MT) is an area of study in Natural Language processing which deals with the automatic translation of human language, from one language to another by the computer. Having a rich research history spanning nearly three decades, Machine translation is one of the most sought after area of research in the linguistics and computational community. In this paper, we investigate the models based on deep learning that have achieved substantial progress in recent years and becoming the prominent method in MT. We shall discuss the two main deep-learning based Machine Translation methods, one at component or domain level which leverages deep learning models to enhance the efficacy of Statistical Machine Translation (SMT) and end-to-end deep learning models in MT which uses neural networks to find correspondence between the source and target languages using the encoder-decoder architecture. We conclude this paper by providing a time line of the major research problems solved by the researchers and also provide a comprehensive overview of present areas of research in Neural Machine Translation.