Miracle-dz/UniFAR-FTUs huggingface dataset:
Responses of zooplankton to long-term environmental changes in a small boreal lake

1) University of Helsinki, Lammi Biological Station, FI-16900 Lammi, Finland (*corresponding author’s e-mail: lauri.arvola@helsinki.fi) 2) Department of Biological and Environmental Sciences/Aquatic sciences, P.O. Box 65, FI-00014 University of Helsinki, Finland 3) Finnish Game and Fisheries Research Institute, Evo Fisheries Research Station, Rahtijärventie 291, FI-16970 Evo, Finland 4) Department of Biology, FI-20014 University of Turku, Finland 5) Finnish Environmet Institute, P.O. Box 140, FI-00251 Helsinki, Finland
Enhanced Soil Washing. A study on Treatment of Copper Polluted Soil and Bark

According to a survey performed by the county administration boards in Sweden, there are over 80 000 sites where the levels of contamination vastly exceeds its surroundings. Many of these pollutants are the remains from former industrial operations, such as chemical industry, tree impregnation, mining and dry cleaning. When it comes to metal contamination, excavation followed by landfilling is the most commonly used treatment method. However, as a consequence of stricter EU legislations along with the fact that many of the landfills of today are beginning to reach their maximum capacity, the need for new remediation methods is substantial. In this study, a lab scale evaluation was made on the effectiveness of enhanced soil washing on soil and incinerated bark from a site at Långö outside Köpmannebro. The material at this site was heavily polluted by copper, which is the substance of interest in this study. The report focuses on the leaching capabilities in large samples compared to previous research conducted at Chalmers University of Technology. In the leaching experiments, the leaching agent consisted of an acidic process water, a waste product from the flue gas cleaning after waste incineration. After the initial experiments a precipitation test was conducted on the leachate in order to evaluate the possibilities to extract the copper from the solution. The leaching experiments showed a large variation in the success of copper removal from the solid material. In the soil samples 71-74 percent was successfully removed, while the ash leaching had a removal rate of 9-50 percent. An attempt to reach a higher removal rate on the ash was made, using a mix of process water and 3M HCl, which then successfully removed 87 percent initial copper. This gives a strong indication of the impact that pH has on the copper removal rate, which is why further investigations regarding optimal pH for this method is needed. A precipitation of copper was attempted in leachate. The attempt was more successful in the ash leachates, with ~99.9 percent effectiveness, while the soil leachates precipitated between 68-81 percent of the containing copper.
Prevalence of Ureaplasma urealyticum in Endocervical Specimens of Female Patients in Qazvin, Iran

Background: Ureaplasma urealyticum that is the smallest free-living bacterium does not have bacterial cell wall. These organisms cause different infections in respiratory and urinary tract system in close contact with epithelial cells. The current study aimed to determine the prevalence of U. urealyticum in endocervical samples of female patients referred to Kowsar hospital in Qazvin, Iran. Methods: The study was conducted on 232 married females aged 20 - 50 years. According to a gynecologist’s request, genital tract biopsies were taken from each individual using Dacron swabs. Each swab was placed into 4 mL of the pleural pneumonia-like organism (PPLO) broth media. Then 25 �L of the suspension was inoculated on the surface of PPLO agar. The remaining broth media and agar plates were incubated at 35°C in 5% CO2 atmosphere. Results: Out of 232 tested samples, 87 cases (37.5%) were positive for U. urealyticum and 145 (62.5%) were negative. Conclusions: Rapid laboratory detection of genital Ureaplasma in pregnant females is very important, mainly because of the ability of the bacteria to colonize the endocervical lining and cause injury to the fetus
Forms of memory: Investigating the computational basis of semantic-episodic memory interactions

The present thesis investigated how the memory systems related to the processing of semantic and episodic information combine to generate behavioural performance as measured in standard laboratory tasks. Across a series of behavioural experiment I looked at different types of interactions between semantic and episodic memory systems and discussed the results in light of current global models of memory. Chapter 2 presents the results of a series of experiments aimed at testing the hypothesis that the storage of information in long-term memory is necessarily dependent on the focus of attentional resources. Chapter 3 comprises of two main sections. The first section provides a short but detailed introduction (a sort of toolkit) of state-trace analysis along with its most recent developments in the framework of Bayesian statistics and some illustrative simulations. The second section presents the results from a state-trace experiment I conducted to examine the processing components underlying semantic and episodic memory interactions. Chapter 4 presents results from two behavioural studies aimed at investigating the functional organization of semantic memory. Both experiments were carried out in Dutch with the first looking at the existence of morphological priming and the second one at the effects of normative frequencies over word and letter priming. Chapter 5 provides a review of the current global models of memory and discusses how the results presented in this thesis can be explained within a unified formal framework. Lastly, Chapter 6 presents a short recap along with some final considerations.
Efficient Monte Carlo Algorithm Using Antithetic Variate and Brownian Bridge Techniques for Pricing the Barrier Options with Rebate Payments

The down-and-out call barrier option with rebate payment on dividend-paying stock is simulated using a new version of the Monte Carlo algorithm. The standard Monte Carlo method for simulating such an option suffers from two sources of errors: Hitting time error inherent from time stepping and the Monte Carlo statistical error. We present a modified version of Monte Carlo method that can reduce these errors efficiently using the Brownian bridge technique for the hitting time error and the antithetic variate approach for the statistical error. We found that the Brownian bridge technique is responsible for improving the order of convergence in hitting time from one half to one and the antithetic variate technique can speed up the Monte Carlo simulation by reducing the variance of the computed payoff, giving almost twice as much accuracy. The standard error and the coefficient of variation are applied in order to measure the effectiveness of the volatility of the underlying option.
Refusal Strategies: a proposal from a sociopragmatic approach

Resumen El objetivo de este artículo es presentar una taxonomía abierta de estrategias de rechazo, la cual puede ser usada para el análisis de la producción de negativas desde una perspectiva discursiva. En primer lugar revisaremos los primeros estudios llevados a cabo sobre las negativas para clasificar la producción de este acto de habla por hablantes no nativos. En segundo lugar describiremos la taxonomía que proponemos de una forma sistematizada teniendo en cuenta tanto el enfoque sociopragmático como el del análisis conversacional. Para finalizar, sugerimos que diversas variables sociales tales como poder, distancia social o grado de imposición juegan un papel fundamental en la producción de este acto de habla. Palabras clave: Negativas, actos de habla, pragmática del interlenguaje Abstract The aim of this paper is to present an open typology of refusal strategies which may be employed in the analysis of refusal performance from a discourse approach. We will first review previous research carried out on refusals in order to classify non-native speakers’ production of this speech act. Secondly, we will describe the suggested taxonomy in a systematised way from a sociopragmatic perspective and within a conversational analysis framework. Finally, we conclude that social variables such as power, social distance and ranking of imposition play an important role in the production of this face-threatening speech act of refusing.
The Use of Big Data in Regenerative Planning

With the increasing significance of Big Data sources and their reliability for studying current urban development processes, new possibilities have appeared for analyzing the urban planning of contemporary cities. At the same time, the new urban development paradigm related to regenerative sustainability requires a new approach and hence a better understanding of the processes changing cities today, which will allow more efficient solutions to be designed and implemented. It results in the need to search for tools which will allow more advanced analyses while assessing the planning projects supporting regenerative development. Therefore, in this paper, the authors study the role of Big Data retrieved from sensor systems, social media, GPS, institutional data, or customer and transaction records. The study includes an enquiry into how Big Data relates to the ecosystem and to human activities, in supporting the development of regenerative human settlements. The aim of the study is to assess the possibilities created by Big Data-based tools in supporting regenerative design and planning and the role they can play in urban projects. In order to do this, frameworks allowing for the assessment of planning projects were analyzed according to their potential to support a regenerative approach. This has been followed by an analysis of the accessibility and reliability of the data sources. Finally, Big Data-based projects were mapped upon aspects of regenerative planning according to the introduced framework.
Generation of sequential symbolic network functions for large-scale networks by circuit reduction to two-port

The major stumbling block in symbolic analysis of large-scale circuits is the exponential growth of expression complexity with the circuit size. Sequential techniques, introduced more than a decade ago, reduced that growth to quasi-linear. The fundamental assumption in all sequential methods developed so far is that the circuit must be decomposed in order to reduce the complexity or the final expression. In this paper we show conclusively that this is not the case. We describe a new algebraic approach to symbolic analysis of large-scale networks, based on the reduction of the compacted modified node admittance matrix to a two-port matrix. No circuit partitioning is required. Internal variables are suppressed one by one using Gaussian elimination. To minimize the number of symbolic operations we employ a locally optimal pivoting strategy. Formula complexity is estimated to grow quasi-linearly with circuit size. The technique is conceptually very simple and produces sequential formulae of significantly lesser complexity than any exact method published to date.
The Influence of Change in Instructional Effectiveness Upon the Affective Characteristics of Teachers

This study was designed to assess the influence of positive change in instructional effectiveness on several affective characteristics of teachers. Data were gathered from 117 intermediate and high school teachers, 52 of whom participated in an in-service workshop on Mastery Learning. Comparisons made through MANOVA procedures showed that those teachers who experienced positive change in the learning outcomes of their students expressed increased personal responsibility for both positive and negative student outcomes, increased affect toward teaching, but decreased confidence in their teaching abilities. Implications regarding the alterability of these teacher characteristics are discussed.
Sea Ice SAR Imagery Classification and Regression Based On Convolutional Neural Networks

Due to the global warming, there have been signficant reductions in the ice extent and ice thickness in the Arctic and marginal seas [57]. Monitoring these changes in sea ice is very important for human activities including weather forecasting, natural-resource extraction, and ship navigation [52]. Of the various sea ice monitoring activities, and sea ice and open water classification, sea ice concentration estimation has attracted significant attention due to the importance of this type of information. Satellite imagery is widely used for monitoring the ice cover. In this regard, images from synthetic aperture radar (SAR) are of interest due to their high spatial resolution. However, automated SAR imagery interpretation is a complex recognition task that requires algorithms with strong ability to learn complex features. Convolutional neural networks (CNNs) are the state-of-the-art in the image recognition field and CNNs have demonstrated an excellent ability to learn complicated image features. In this thesis, we first used a CNN-based transfer learning method to address sea ice and water classification challenge, which achieves an impressive classification accuracy (92.36%). Then sea ice concentration estimation from SAR image using CNNs is developed. The CNN models are trained from scratch using image analysis charts as ground truth. Based on the designed CNN, several studies are conducted. We first demonstrate the importance of including samples of intermediate ice concentration in our training data. Then experiments are carried out to increase the number of these samples in our dataset. The results from experiments indicate that model performance can be improved by adding more intermediate ice concentration samples from new datasets, regardless of the location, time, and sea ice features of new datasets. Another benefit of balancing the dataset is that the estimation results of intermediate ice concentrations from the CNN become more accurate. In addition, the CNN model we adopted is found to outperform other algorithms on distinguishing the marginal ice zone.
Megaspores and a Palynomorph from the Lower Potomac Group in Virginia

Hueber, Francis M. Megaspores and a Palynomorph from the Lower Potomac Group in Virginia. Smithsonian Contributions to Paleobiology, number 49, 69 pages, 1 figure, 24 plates, 1982. —A plant microfossil assemblage comprising seven species of megaspores; Verrutriletes carbunculus (Dijkstra) Potonie, Echitrdetes cf. E. lanatus (Dijkstra) Potonie, Erlansonisporites erlansonii (Miner) Potonie, Thylakosporites retiarius (Hughes) Potonie, Arcellites disciformis (Miner) Ellis and Tschudy, Arcellites cf. A. pyriformis (Dijkstra) Potter, and Paxillitriletes species Hall and Nicolson; two species of the microspore Crybelosporites Dettmann, C. striatus (Cookson and Dettmann) Dettmann adherent to specimens oi Arcellites disciformis, and Crybelosporites species adherent to specimens of Ech'itriletes cf. E. lanatus; and the palynomorph Dictyothylakos pesslerae Horst; is recorded from the Patuxent Formation, Potomac Group, Lower Cretaceous (BarremianAptian) in Virginia, USA. A preliminary analysis of the enclosing matrix for microspores and pollen has related the collection site closely to lowermost Zone I of the Potomac Group as described by Hickey and Doyle (1977). The megaspore assemblage supported by acceptance of the oldest possible date derived from the microspore and pollen analysis suggests correlation with the Barremian-Aptian horizons in the English Wealden, Lower Cretaceous, and specifically with the "Arcellites Flora" of Hughes. Megafossils comprising two seed cones belonging to the Pinaceae, Pityostrobus hueberi Robison and Miller and Pityostrobus virginiana Robison and Miller have been reported from the site. A fruit or cupule of Caytonia has been found along with numerous seeds, fern fragments, coniferous woods, and cycadopsid cuticles. This array of megafossils is not described or illustrated herein. A backswamp area of sedimentation and type of habitat is suggested on the basis of the lithofacies and generalized composition of the flora. The writer fully agrees with Tschudy (1976) as to the importance of searching for megaspores in continental Mesozoic rocks to aid in correlating and subdividing the deposits more effectively. OFFICIAL PUBLICATION DATE is handstamped in a limited number of initial copies and is recorded in the Institution's annual report, Smithsonian Year. SERIES COVER DESIGN: The trilobite Phacops rana Green. Library of Congress Cataloging in Publication Data Hueber, Francis M. Megaspores and a Palynomorph from the Lower Potomac Group in Virginia Smithsonian contributions to paleobiology ; no. 49 Bibliography: p. 1. Spores (Botany), Fossil. 2. Palynology. 3. Paleobotany—Cretaceous. 4. Paleobotany— Virginia. I. Title. II. Series. QE701.S56 no. 49 [QE996] 560s [561M3] 81-607852 AACR2
Iota-carrageenans from Solieria filiformis (Rhodophyta) and their effects in the inflammation and coagulation

Biochemical analyses are important tools for discovering new bioactive compounds for medical clinic. This study aimed at isolating iota -carrageenans (ι-CARs) from Solieria filiformis (Rhodophyta) by enzymatic extraction (EE), refined hot-water extraction (RHWE) and hot-water extraction (HWE), and test (EE, s.c.) their anti-inflammatory effects in the peritonitis model using the Lambda-carrageenan (700 µg cavity -1 , i.p.) as an inflammatory stimuli in rats. The activated partial thromboplastin time (APTT) was also evaluated in ι-CARs fractions, obtained by ion-exchange chromatography (DEAE-cellulose), using rabbit plasma and compared to heparin (193 IU mg -1 ). The results showed that the ι-CARs (EE) (3 or 9 mg kg -1 ) containing 89.92% total sugars, 29.02% sulfate and absence of contaminant proteins inhibited (p 0.05). Similar chromatography profiles were obtained among the methods; however, with fractions revealing different pattern on charge density by electrophoresis. Fractions had no virtually effects on APTT (1.16, 1.73 and 1.59 IU mg -1 for EE, RHWE and HWE, respectively). Further investigations to better understanding the actions of S. filiformis ι-CARs (EE) in the inflammatory response are suggested.
The level of representative underwriting and the underwriting costs of REIT SEOs

Purpose – The purpose of this paper is to investigate factors influencing the underwriting discount for US Real Estate Investment Trust (REIT) Seasoned Equity Offerings (SEOs). Design/methodology/approach – The study provides new evidence on determinants of underwriting discounts with a comprehensive dataset of 783 US REIT SEOs from 1996 until June 2010. Ordinary least squares regressions are performed to estimate the effect of the level of representative underwriting along with other potential factors on underwriting discounts.Findings – The study complements the well‐documented notion of the economies of scale in SEO underwriting discounts. The equally (value) weighted underwriting discounts averaged 4.21 per cent (4.10 per cent) with a declining trend over time. The findings of this study show the statistically and economically significant negative effect of the level of representative underwriting on the underwriting discounts, as well as the significance of the structure of underwriting syndicate in d.
Citizen scientist community engagement with the HiggsHunters project at the Large Hadron Collider

The engagement of citizen scientists with the HiggsHunters. org citizen science project is investigated through analysis of behaviour, discussion and survey data. More than 38,000 citizen scientists from 179 countries participated, classifying 1.5 million features of interest on about 39,000 distinct images. While most citizen scientists classified only a handful of images, some classified hundreds or even thousands. Analysis of frequently used terms on the dedicated discussion forum demonstrated that a high level of scientific engagement was not uncommon. Evidence was found for an emergent and distinct technical vocabulary developing within the citizen science community. A survey indicates a high level of engagement and an appetite for further citizen science projects related to the Large Hadron Collider.
A Hybrid Discrete Choice Model of Differentiated Product Demand with an Application to Personal Computers

In this paper I construct a new discrete choice model of differentiated product demand that combines the pure characteristics demand model and the random coefficient logit demand model. In this hybrid model consumers are exposed to an idiosyncratic taste shock when they make a brand choice but free from it when they make a product choice within a brand. The simplest version of this model describes an oligopoly market where firms sell vertically differentiated products. Simulations show that the hybrid model is closer to the random coefficient logit model with respect to markup, while it is closer to the pure characteristics model with respect to welfare changes. These three models are applied to data on personal computers to estimate consumer demand. The hybrid model is better identified than the other two models such that coefficients are statistically significant and the willingness to pay for quality improvement is more reasonable. Markup and consumer welfare are also compared to evaluate implications of each model.
State Legislative Response to Direct Democracy and the Politics of Partial Compliance

Over the last quarter-century, direct democracy has played an increasingly important role in state politics and policy. While limited attitudinal data show high levels of legislative approval for direct democracy, the most prominent piece of behavioral scholarship concludes that California legislators often attempt to steal the initiative by displacing ballot measure content and preventing full implementation. Results from an original web survey indicate that Oregon lawmakers are cautiously supportive of the initiative process and identify the conditions under which they support changes to voter-ratified bills. Case study evidence shows how legislators use their power to amend successful initiatives to clarify and improve flawed measures. I argue that institutional rules governing the initiative amendment process in Oregon allow legislators to engage in partial compliance while preserving voters core ideas. By drawing on new data sources and analyzing both behavior and attitudes, the findings shed new light on when, how, and under what conditions state government actors interfere in the initiative process and offer an important correction to the literature on legislative response to direct democracy.
The influence of previous host age on current host acceptance in Trichogramma

Trichogramma principium Sug. & Sor. females were sequentially offered two portions of the grain moth (Sitotroga cerealella Oliv.) eggs, either young (1‐day old) or old (eggs that had developed 6 days at a temperature of 20 °C). The probability of host acceptance depended not only on current host age, but also on the age of the previously offered host. Particularly, Trichogramma females more often oviposited in old host eggs when previously offered young eggs (35–45% of Trichogramma females laid eggs) compared to females which were sequentially offered two portions of old eggs (15–20% of Trichogramma females laid eggs). In other words, parasitization by Trichogramma was stable even when transferred from young (preferred) to old (usually rejected) eggs. Dissections showed that refusing females had significantly more mature eggs than ovipositing females, independent of host age. Among ovipositing females, wasps provided with young hosts had fewer mature ovarial eggs than wasps provided with old hosts. Supposedly, Trichogramma females offered old hosts require a higher motivation to oviposit and have a correspondingly higher egg load than females offered young (preferred) hosts.