Miracle-dz/UniFAR-FTUs huggingface dataset:
Educators' Intervention, Communication and Peers' Conflict in Nurseries

The aim of the present study is to assess the role of educators' interventions and communications in peer conflicts between preschoolers. Ninety-nine children (47 females and 52 males) aged from zero to three years were observed in seven Italian nurseries during free-play, mealtime and structured activity. Their interactions (verbal and non-verbal behaviour) were video-recorded and transcribed. Event sampling with continuous recording rules was followed and a conflict coding system was used to analyse conflict episodes. Specifically, conflict antecedents, origins, unfolding, resolution, outcomes (solitary play, parallel play and together outcomes) and educators' intervention (direct, indirect or no intervention) were analysed. In addition, educators' communicative functions (tutorial, conversational, didactic, control and asynchronous) were assessed. Fifty-five peer conflicts emerged from analysis of the data, most of them between two males in the older group during free-play. Educators' interventions were associated with a lower frequency of together outcomes and educators' tutorial utterances, and with a higher frequency of educators' control utterances. The study emphasises the importance of a natural resolution of conflict and the role of the educator as a “tutor” with children younger than three years old. It could, therefore, offer useful suggestions to educators, stimulating them to encourage a spontaneous resolution to conflict, and thus to promote children's autonomy. Further research is needed to clarify the influence of other variables, such as friendship relationships, contextual aspects (e.g. composition of the classes, composition of the group) and cultural aspects.
Before Death Do Us Part : On Efficient Contract Breakup and Partial Property Rights ∗

Parties to a repeat transaction contract are assigned a property rights bundle with partial ex-post decision rights. I show for an investing buyer with incomplete bargaining power, that granting her the right to terminate the contract after seller’s delivery in the previous period allows for opportunistic rent-seeking: Holding up the seller in renegotiations yields additional breakup rents that increase the buyer’s returns on investment and induce efficient ex-ante incentives where she would otherwise underinvest. The buyer’s opportunism thus generates social value. The exit option complements incomplete property rights and serves as contractual solution to the hold-up problem. Legal implications for U.S. and international contract law are discussed. JEL classification: D86, K12, L14.
Generation of a Skeleton Corpus of Digital Objects for the Validation and Evaluation of Format Identification Tools and Signatures

To preserve digital information it is vital that the format of that information can be identified, in-perpetuity. This is the major focus of research within the field of Digital Preservation. The National Archives of the UK called for the Digital Preservation and Digital Curation communities to develop a test corpus of digital objects to help further develop tools to aid this purpose. Following that call, an attempt has been made to develop the suite. This paper initially outlines a methodology to generate a skeleton corpus using simple user-generated digital objects. It then explores the lessons learnt in the generation of a corpus using scripting language techniques from the file format signatures described in The National Archives PRONOM technical registry. It will also discuss the use of the digital signature for this purpose, the benefits of developing a test corpus using this technique. Finally, this paper will outline a methodology for future research before exploring how the community can best make use of the output of this project and how this project needs to be taken forward to completion.
A Propositional Inventory for New Diffusion Research

The diffusion theory literature offers a fairly well-developed conceptual framework for the study of communications. As developed across a number of disciplines, diffusion applies to the flow of information, ideas, and products; its uniqueness is its focus on interpersonal communication transfer. This paper offers new theoretical propositions to advance consumer diffusion research and to provide a foundation for diffusion modeling.
Native Language Identification on Text and Speech

This paper presents an ensemble system combining the output of multiple SVM classifiers to native language identification (NLI). The system was submitted to the NLI Shared Task 2017 fusion track which featured students essays and spoken responses in form of audio transcriptions and iVectors by non-native English speakers of eleven native languages. Our system competed in the challenge under the team name ZCD and was based on an ensemble of SVM classifiers trained on character n-grams achieving 83.58% accuracy and ranking 3rd in the shared task.
On Asymptotic Stability of Solitary Waves in Schrödinger Equation Coupled to Nonlinear Oscillator

The long-time asymptotics is analyzed for finite energy solutions of the 1D Schrödinger equation coupled to a nonlinear oscillator. The coupled system is invariant with respect to the phase rotation group U(1). For initial states close to a solitary wave, the solution converges to a sum of another solitary wave and dispersive wave which is a solution to the free Schrödinger equation. The proofs use the strategy of Buslaev and Perelman (1993): the linerization of the dynamics on the solitary manifold, the symplectic orthogonal projection, method of majorants, etc.
Smart home context awareness based on Smart and Innovative Cities

In the emerging Smart Cities - Smart Homes computing paradigms developing a formalization for context information is increasingly important. In the present paper, basedon the EU FIRE research project "Social and Smart" we aim to formalize and build a complete formal definition of context in both home and city scale. Using sensors as a Smart City service and local sensors installed locally in Smart Homes, it is possible to collect continuously context data, such as temperature, humidity, noise and pollution levels. This context information can be used to adapt to user-specific needs in the Smart Home environment via the incorporation of user defined home rules. Semantic web technologies are used to support the knowledge representation of this ecosystem. The overall architecture has been experimentally verified using input from the SmartSantander Smart City project and applying it to the SandS Smart Home within the FIRE and FIWARE framework. Finally, two examples are presented in order to stress how the smart home appliances adapt their function to home rules and context information.
Observation on Poterioochromonas sp. (Chrysophyte)

Poterrioochromonas sp. , isolated from Microcystis cultures in 2002, was described with LM, SEM, TEM. The grazing characteristics of this strain were also observed in laboratory experiments. The results showed that this strain has the representative features of the genus except for the lorica, and the most conspicuous feature of Poterioochromonas sp. was about the chromatophores.
Learning Chinese as a heritage language in Australia and beyond: the role of capital

The benefits of learning and retaining heritage languages are well documented in the literature. Chinese heritage language learners’ commitment to their heritage language learning has gained significant research ground in social psychological and post-structural schools, with empirical evidence predominantly emerging from the North American contexts. There is scant sociological examination of similar problems conducted outside North America. The current study aims to make a contribution in this regard. The use of Bourdieu's sociological notion of capital in the Australian context complements the social psychological and post-structural work predominantly produced in the North American contexts. The initial quantitative sub-study analyses the impacts of various resources on the Chinese heritage language proficiency of 230 snowball-sampled Chinese Australian respondents to an online survey. The subsequent qualitative sub-study explores the profits of learning Chinese heritage language through interviews with a subset of the survey sample. Findings indicate that cultural, social, and symbolic capital significantly positively contributes to Chinese Australians’ Chinese heritage language proficiency, which, in return, produces profits in different forms of capital. The study suggests a reciprocal relationship between ‘capital’ and Chinese heritage language proficiency.
Maximum Likelihood Model Selection for 1-Norm Soft Margin SVMs with Multiple Parameters

Adapting the hyperparameters of support vector machines (SVMs) is a challenging model selection problem, especially when flexible kernels are to be adapted and data are scarce. We present a coherent framework for regularized model selection of 1-norm soft margin SVMs for binary classification. It is proposed to use gradient-ascent on a likelihood function of the hyperparameters. The likelihood function is based on logistic regression for robustly estimating the class conditional probabilities and can be computed efficiently. Overfitting is an important issue in SVM model selection and can be addressed in our framework by incorporating suitable prior distributions over the hyperparameters. We show empirically that gradient-based optimization of the likelihood function is able to adapt multiple kernel parameters and leads to better models than four concurrent state-of-the-art methods.
Recognizing cardiovascular risk from photoplethysmogram signals using ELM

In this paper, photoplethysmogram (PPG) signals, 30 healthy and 30 pathological, are classified as `healthy' or `at risk' of cardiovascular diseases (CVDs) using extreme learning machine (ELM), a supervised learning algorithm. Additionally, two other supervised learning algorithms, backpropagation and support vector machine are used for classification to compare their results with that of ELM and hence validate its performance. Based on the results obtained, ELM gives the best accuracy, a sensitivity of 89.33% and a specificity of 90.33%, with minimum training time and minimum number of features as input.
A unified approach to labeling graphical features

The automatic placement of text or symbol labels corresponding to graphical objects is critical in several application areas such as Cartography, Geographical Information Systems, and Graph Drawing. In this paper we present a general framework for solving the problem of assigning text or symbol labels to a set of graphical features in two dimensional drawings or maps. Our approach does not favor the labeling of one type of graphical feature (such as a node, edge, or area) over another. Additionally, the labcls arc allowed to have arbitrary size and orientation. We have applied our framework to drawings of graphs. We have implemented our techniques and have performed extensive experimentation on hierarchical and orthogonal drawings of graphs. The resulting label assignments are very practical and indicate the effectiveness of our approach.
Chemotherapy dose reductions in obese patients with colorectal cancer.

BACKGROUND In cancer patients with a large Body Surface Area, chemotherapy drug doses are often reduced, as studies have suggested that their pharmacokinetics may be altered. However, this strategy may result in underdosing obese patients. PATIENTS AND METHODS In three Medical Research Council trials of chemotherapy for advanced colorectal cancer, dose reductions were not mandated. This provided the opportunity to compare the toxicity levels in those obese patients fully dosed and to investigate if those under dosed experienced a worse survival. Body Mass Index (BMI) was used to classify patients as normal weight (BMI < 25), overweight (BMI 25-29), or obese (BMI 30+). RESULTS Of the 4781 patients, 2158 (45%) were classified as normal weight, 1753 (37%) as overweight, and 870 (18%) as obese. There was no evidence that, in those patients fully dosed, obese patients experienced more toxicity or that dose-reducing obese patients resulted in less toxicity. However, there was a suggestion that those obese patients who were given reduced doses had a worse progression-free survival [hazard ratio (HR) 1.21, 95% confidence interval (CI) 1.06-1.39, P = 0.006] and a slightly worse overall survival (HR 1.12, 95% CI 0.96-1.30, P = 0.152). CONCLUSION These results, although not a randomised comparison, do not support the policy of reducing chemotherapy doses for obese patients with colorectal cancer.
Use of nanoscale delivery systems to maintain synergistic drug ratios in vivo

Importance of the field: Drug combinations have been the standard of care in the treatment of cancer for > 50 years. Typically, combination chemotherapy uses agents with non-overlapping toxicities which are escalated to their maximum tolerated dose. However, emerging evidence indicates that this approach may not be providing optimal efficacy depending on the drug ratios to which the tumor is exposed. Combined drugs can be synergistic whereas other ratios of the same agents may be antagonistic or additive. Areas covered in this review: In this review, we examine the importance of drug ratios in cancer therapy. We describe how manipulation of the lipid membrane and internal buffer composition maintains synergistic ratios of irinotecan and floxuridine (CPX-1), daunorubicin and cytarabine (CPX-351) or cisplatin and irinotecan (CPX-571). For polymer-based nanoparticles, prodrug hydrophobicity was exploited to coordinate the release of gemcitabine and the more hydrophobic paclitaxel. We present preclinical data for liposomal drug combinations which demonstrate that the most efficacious formulation is not always the highest dose of both agents. What the reader will gain: An insight into the use of liposomes and polymer-based nanoparticles to deliver synergistic drug combinations to the tumor site and avoid antagonistic drug–drug interactions. Take home message: The ability to control and maintain drug ratios in vivo through the use of nanoscale delivery vehicles results in a significant improvement in therapeutic activity.
Nanocrystal targeting in vivo

Inorganic nanostructures that interface with biological systems have recently attracted widespread interest in biology and medicine. Nanoparticles are thought to have potential as novel intravascular probes for both diagnostic (e.g., imaging) and therapeutic purposes (e.g., drug delivery). Critical issues for successful nanoparticle delivery include the ability to target specific tissues and cell types and escape from the biological particulate filter known as the reticuloendothelial system. We set out to explore the feasibility of in vivo targeting by using semiconductor quantum dots (qdots). Qdots are small (<10 nm) inorganic nanocrystals that possess unique luminescent properties; their fluorescence emission is stable and tuned by varying the particle size or composition. We show that ZnS-capped CdSe qdots coated with a lung-targeting peptide accumulate in the lungs of mice after i.v. injection, whereas two other peptides specifically direct qdots to blood vessels or lymphatic vessels in tumors. We also show that adding polyethylene glycol to the qdot coating prevents nonselective accumulation of qdots in reticuloendothelial tissues. These results encourage the construction of more complex nanostructures with capabilities such as disease sensing and drug delivery.
A new look at aging and performance in the antisaccade task: The impact of response selection

Aged adults respond more slowly and less accurately in the antisaccade task, in which a saccade away from a visual stimulus is required. This decreased performance has been attributed to a decline in the ability to inhibit prepotent responses with age. Considering that antisaccades also involve response selection, the present experiment investigated the contribution of inhibition and response selection. Young and aged adults were compared between conditions that required varying percentages of prosaccades, antisaccades, and no-go trials. The comparison between no-go (inhibition of a prosaccade) and antisaccade trials (inhibition of a prosaccade and selection of an antisaccade) showed significantly worse performance in the antisaccade task, especially for the older group, suggesting that they failed to select the antisaccade in a situation in which a competing, prepotent response is available. The impact of this response selection failure was underlined by an equivalent ability of both groups to impose inhibition.
An introduction to the special issue on autobiographical memory

This article serves as an introduction to this volume's Nordic Psychology Special Issue on autobiographical memory. We were given the opportunity to present examples from the ‘growth layer’ from the Center on Autobiographical Memory Research (CON AMORE), located at Aarhus University. This is displayed by the fact that all six articles in the present volume have PhD students as first authors. Although quite different issues are covered, the articles as a whole do not provide an exhaustive review on autobiographical memory research. Rather, the contributions are constrained by the topics that each PhD students is working on. Especially two themes, that recently both have received a lot of interest in the field, are prominent across the contributions: Cultural Life Scripts, and Mental Time Travel. Before introducing each article, a brief general outline on autobiographical memory and how the field has developed so far is offered.
Changing Concepts in the Management of Severe Ocular Surface Disease Over Twenty-five Years

The management of severe ocular surface disease (OSD) has changed dramatically over the last 25 years. In the 1970s, all patients with severe OSD had a poor prognosis. The available techniques for visual rehabilitation at that time consisted of lamellar and penetrating keratoplasty, tarsorrhaphy, and preserved artificial tears. Modern day treatment of severe OSD is quite different. Advances in microsurgical techniques and understanding of the role of the limbal stem cells have led to great improvements in both visual acuity and quality of life for these patients. Progress in this area has occurred in a step-wise fashion. What follows is a chronological review of what we believe are the most important steps that have brought us to where we are today in the treatment of severe OSD.
Power-aware data analysis in sensor networks

Sensor networks have evolved to a powerful infrastructure component for event monitoring in many application scenarios. In addition to simple filter and aggregation operations, an important task in processing sensor data is data mining - the identification of relevant information and patterns. Limited capabilities of sensor nodes in terms of storage and processing capacity, battery lifetime, and communication demand a power-efficient, preferably sensor-local processing. In this paper, we present AnduIN, a system for developing, deploying, and running in-network data mining tasks. The system consists of a data stream processing engine, a library of operators for sensor-local processing, a box-and-arrow editor for specifying data mining tasks and deployment, a GUI providing the user with current information about the network and running queries, and an alerter notifying the user if a better query execution plan is available. At the demonstration site, we plan to show our system in action using burst detection as example application.
Qualitative analysis by interviews and video recordings to establish the components of a skilled low‐cavity non‐rotational vacuum delivery

Objectives The objectives of this study were to define the components of a skilled low‐cavity non‐rotational vacuum delivery (occiput anterior, vertex at station +2 or below and less than 45‐degree rotation from midline) and to facilitate the transfer of skills from expert to trainee obstetricians.
Predicting defect densities in source code files with decision tree learners

With the advent of open source software repositories the data available for defect prediction in source files increased tremendously. Although traditional statistics turned out to derive reasonable results the sheer amount of data and the problem context of defect prediction demand sophisticated analysis such as provided by current data mining and machine learning techniques.In this work we focus on defect density prediction and present an approach that applies a decision tree learner on evolution data extracted from the Mozilla open source web browser project. The evolution data includes different source code, modification, and defect measures computed from seven recent Mozilla releases. Among the modification measures we also take into account the change coupling, a measure for the number of change-dependencies between source files. The main reason for choosing decision tree learners, instead of for example neural nets, was the goal of finding underlying rules which can be easily interpreted by humans. To find these rules, we set up a number of experiments to test common hypotheses regarding defects in software entities. Our experiments showed, that a simple tree learner can produce good results with various sets of input data.
The Prompt Inventory from Very Massive Stars and Elemental Abundances in Lyα Systems

It has been proposed that very massive stars (VMSs) dominated heavy-element production until a "metallicity" threshold corresponding to [Fe/H] ≈ -3 was reached. This results in a prompt (P) inventory of elements, the abundances of which were determined from observations of Galactic halo stars with [Fe/H] ≈ -3. We calculate ΩP(E) from the P inventory for a large number of elements in the intergalactic medium (IGM). Using the available data on Ω(Eion) for C IV, O VI, and Si IV in Lyα systems, we find that the ionization fractions calculated from Ω(Eion)/ΩP(E) are, within reasonable uncertainties, compatible with the values estimated from ionization models for Lyα systems. This agreement appears to hold from z ~ 0.09 to ~4.6, indicating that the bulk of the baryonic matter remains dispersed with a fixed chemical composition. We conclude that the P inventory was established in the epoch prior to z ~ 4.6. The dispersal of processed baryonic matter to the general IGM is considered to be the result of energetic VMS explosions that disrupted baryonic aggregates until the "metallicity" threshold was reached to permit normal astration. The formation of most galaxies is considered to have occurred subsequent to the achievement of this metallicity threshold in the IGM.
Cultural Tolerance: Measurement and Latent Structure of Attitudes toward the Cultural Practices of Others

The goals of the present study were to construct a scale of cultural tolerance, examine the latent structure of this scale, and determine the relationship of the scale to measures of other relevant constructs. The scale was administered to three samples of students from the University of Minnesota. Results based on multidimensional scaling suggested that a two-dimensional structure was the most parsimonious solution. One dimension represented items assessing affect and belief at one pole and items assessing intention to behave at the other pole. The second dimension represented a continuum, with the items related to specific cultures. The components of the scale were shown to correlate differentially with measures of personality constructs.