Miracle-dz/UniFAR-FTUs huggingface dataset:
Examination of CEFR-J spoken interaction tasks using many-facet Rasch measurement and generalizability theory

Attempts are underway to develop prototype tasks, based on a Japanese version of the Common European Framework of Reference for Languages (CEFR; Council of Europe, 2001; CEFR-J; Negishi, Takada, & Tono, 2013). As part of this larger project, the current paper reports on the creation of spoken interaction tasks for five levels (Pre-A1, A1.1, A1.2, A1.3, and A2.1). Tasks were undertaken by 66 Japanese university students. Two raters evaluated their interactions using a three-level holistic rating scale, and 20% of the performances were double rated. The spoken ratings were analysed using many-facet Rasch measurement (MFRM) and generalizability theory (G-theory). MFRM showed that all the tasks fit the Rasch model well, the scale functioned satisfactorily, and the difficulty of the tasks generally concurred with CEFR-J levels. Results from G-theory that employed the p x t design, including tasks as a facet, showed the different proportion of variance accounted for by tasks, as well as the number of tasks that could be required to ensure sufficiently high reliability. The MFRM and G-theory results effectively revealed areas for improving spoken interaction tasks; the results also showed the usefulness of combining the two methods for task development and revision.
Quantum-resistant Designated-ciphertext Searchable Encryption

Public key encryption with keyword search (PEKS) was proposed by Boneh et al. in 2004; it allows users to search encrypted keywords without losing data privacy. Although extensive studies have been conducted on this topic, only a few focus on the insider keyword guessing attack that will cause users to leak sensitive information. More specifically, after receiving the trapdoor from the user, the malicious insider (e.g. server) can randomly encrypt possible keywords using the user’s public key. Then, the insider can test whether the trapdoor corresponds to the selected keyword. To solve the above issue, we introduce the notion of designated-ciphertext searchable encryption (DCSE) in this work. Then, we propose a generic construction that employs an anonymous identity-based encryption and key encapsulation mechanism. Additionally, we demonstrated that our work satisfies the indistinguishability under chosen-keyword attack (IND-CKA) and indistinguishability under insider keyword guessing attack (IND-IKGA) in the standard model. Moreover, we provide an instantiation from the NTRU lattices. Compared with other state-of-the-art schemes, our scheme is not only more efficient and practical, it also provides more robust security.
A Nonparametric Offpolicy Policy Gradient

Reinforcement learning (RL) algorithms still suffer from high sample complexity despite outstanding recent successes. The need for intensive interactions with the environment is especially observed in many widely popular policy gradient algorithms that perform updates using on-policy samples. The price of such inefficiency becomes evident in real-world scenarios such as interaction-driven robot learning, where the success of RL has been rather limited. We address this issue by building on the general sample efficiency of off-policy algorithms. With nonparametric regression and density estimation methods we construct a nonparametric Bellman equation in a principled manner, which allows us to obtain closed-form estimates of the value function, and to analytically express the full policy gradient. We provide a theoretical analysis of our estimate to show that it is consistent under mild smoothness assumptions and empirically show that our approach has better sample efficiency than state-of-the-art policy gradient methods.
Titanium and Vanadium Catalysts with 2-Hydroxyphenyloxazoline and Oxazine Ligands for Ethylene-Norbornene (co)Polymerization

A series of titanium and vanadium complexes with oxazoline 2-(4,5-dihydro-1,3-oxazol-2-yl)phenol (L1), 2-(4-methyl-4,5-dihydro-1,3-oxazol-2-yl)phenol (L2), and oxazine 2-(5,6-dihydro-4H-1,3-oxazin-2-yl)phenol (L3) ligands were synthesized, and their structures were determined by NMR and MS methods as (L)2MtCl2. The vanadium complexes were found to be highly active in ethylene (7300 kgPE/(molV·h)) and ethylene/norbornene (5300 kgPE/(molV·h)) (co)polymerization. The polyethylene characteristics were melting temperature (123–142 °C), crystallinity degree (49–75%), molecular weight (8.5–7.2 × 105 g/mol), molecular weight distribution (1.5–2.4). The ethylene-norbornene (E-NB) copolymer characteristics were molecular weight (2.6–0.9 × 105 g/mol), molecular weight distribution (1.6–2.2), glass transition temperature (4–62 °C), norbornene incorporation (12.3–30.1 mol%) at initial concentration (0.5–1.5 mol/L). The microstructure of E-NB copolymers depends on the catalyst applied with the highest diads content for the (L3)2VCl2 and triads for the (L2)2VCl2 complexes.
General Guidance on Endocrine Assessment: Assays and Endpoints

33. The purpose of this section is to provide background information on the relevance of various types of data for supporting decisions about the endocrine disrupting properties of chemicals and other test materials (e.g. effluents, natural waters, contaminated foods, etc.) in humans and non-mammalian vertebrates. Interpretation of results from some invertebrate test guidelines is also included, but due to the rather poor current understanding of endocrinology in most invertebrates, and the lack of diagnostic screening endpoints with these taxonomic groups (e.g. OECD [2010c]), guidance cannot yet be given for many of these assays. Nevertheless, non-OECD test assays, including those utilising invertebrate species, may provide information that can be used in a weight of evidence (WOE) approach. Furthermore, the document only deals with estrogen-, androgenand thyroidmediated endocrine disruption, and with interference with steroidogenesis (although some guidance is also provided for evaluation of juvenile hormone, ecdysteroid and retinoid activity). It does not cover other possible types of endocrine disruption, such as effects on the hypothalamus-pituitary-adrenal axis or other receptor pathways. Some advice on the endocrine control of neural development is provided, but this is only rudimentary. The section is organised according to the OECD Conceptual Framework (CF) (see Section A.2), as updated in 2017 with tests which were unavailable or not included when it was first proposed.
Dust Heterogeneous Reactions during Long-Range Transport of a Severe Dust Storm in May 2017 over East Asia

Dust aerosol has important climate and environmental effects, which could be changed by internally mixing with anthropogenic aerosol as a result of heterogeneous reactions; however, the importance of these reactions is not fully understood yet. In this study, synergetic observations and an air quality model were used to analyze the transport of a severe dust storm and its impacts on nitrate and sulfate levels over East Asia between 3 and 11 May 2017. The model successfully reproduced the occurrence and transport of the dust storm compared to dust RGB imageries of the Himawari-8 satellite and dust extinction coefficients observed by LIDAR. The model also reasonably simulated the variations of observed nitrate and sulfate concentrations, and the results indicated that the dust heterogeneous reactions were dominant pathways for nitrate formation, but they had limited contribution for sulfate in both fine and coarse mode in Fukuoka, Japan. Dust nitrate formed rapidly after leaving China, and the highest period-averaged concentration of dust nitrate (>5 μg m−3) was shown over the Yellow Sea. Based on model results; we found that the mass ratio of dust nitrate to dust aerosol could reach 10% over the Pacific Ocean. Our results confirmed the importance of heterogeneous reactions on compositions of dust particles.
Factors Controlling Long-Term Survival and Growth of Naturalized Escherichia coli Populations in Temperate Field Soils

While Escherichia coli is widely used as an indicator of fecal contamination of waterways, recent studies suggest that this bacterium may become “naturalized” to soils. In this study, we investigated the survival and growth of naturalized E. coli in temperate soil in northern Minnesota. A spontaneously-occurring, antibiotic resistant E. coli strain, KS7-NR, was added to a field site at 10 cells (g soil). The survival and growth of E. coli KS7-NR were followed from June to October, by using colony counts on agar plates supplemented with antibiotics, and by using quantitative PCR (qPCR) with strain-specific primers developed based on suppressive subtractive hybridization. Both plate count and qPCR analyses indicated that E. coli KS7-NR survived for more than 2 months in the field soil. Laboratory experiments showed that soil temperature, moisture, nutrients, and the presence of other soil organisms influenced growth and survival of E. coli KS7-NR in soil. Moreover, our results indicated that summer drought conditions that occurred during the field study likely limited in situ growth of E. coli at the field site. Taken together, these results suggest that E. coli strains can survive long-term and grow in soils, provided that abiotic factors are within their tolerance limits.
An Ultra-Wideband Bandpass Filter with a Notch Band and Wide Upper Bandstop Performances

This paper presents an ultra-wideband bandpass filter (UWB-BPF) with a notch band and a wide upper stopband. Two pairs of half-wavelength high-impedance line resonators tightly and strongly coupled to the input/output lines are used to provide the wideband responses. The first UWB responses of 3.4–5.0 GHz and the second UWB of 6.0–10.0 GHz are designed independently first and then combined together for the application of a direct-sequence ultra-wideband bandpass (DS-UWB) system. Without using any extra bandstop structure, a notch band at 5.2 GHz can be obtained. The fabricated UWB-BPF with a compact circuit size exhibits good passband performances including insertion losses of 1 ± 0.3 and 2 ± 0.4 dB for first and second passbands, respectively, a high isolation at 5.2 GHz with an attenuation level of 22.7 dB, and wide upper stopband responses from 11 GHz to 19 GHz, simultaneously. The measured results also exhibit good agreement with the simulated results.
The Effects of High-Intensity Interval Training on VO2 max in Different Groups: A Review

Vieira EFS, Aidar FJ, de Matos DG, Santos LR, Esteva CS, de Araújo SS, Marçal AC. The Effects of High-Intensity Interval Training on VO2 max in Different Groups: A Review. JEPonline 2019;4(2):142-153. The purpose of this study was to investigate whether HIIT can influence the VO2 max. This review evaluated 123 articles: (a) 78 were from PubMed database; (b) 6 were in the SciELO database; (c) 29 from Periodicals Capes; and (d) 10 articles from Lilacs. Of these, 22 papers were selected and analyzed. At the end of the analysis, 11 articles met the inclusion and exclusion criteria. There is still no consensus on the duration of exercise and rest intervals in the HIIT practitioners, but most of the protocols used demonstrated efficacy for the improvement of VO2 max. Further studies are needed to determine exercise and rest time that can promote the benefits of HITT on physical condition, cardiac systolic function, and post-exercise oxygen consumption (VO2) more efficiently.
DEMONSTRATION SESSION Following the spirit of the Demos Session of PROPOR’2010, 2012, 2014, and 2016, the PROPOR 2018 demonstration track aims at bringing together Academia and Industry and creating a forum

This work presents an ongoing effort towards a Portuguese grammar under the Grammatical Framework (GF) formalism. GF and the new grammar are briefly introduced, and then we employ the grammar to parse HPSG’s Matrix MRS test suite. We will demonstrate the use of the grammar in the parsing of text and in natural language appli-
Machine Learning Approach to Measure Sleep Quality using EEG Signals

Sleep quality has a vital effect on good health and well-being throughout a life. Getting enough sleep at the right times can help protect mental health, physical health, quality of life, and safety. In this study, an electroencephalography (EEG)-based machine-learning approach is proposed to measure sleep quality. The advantages of our approach over standard Polysomnography (PSG) method are: 1) it measures sleep quality by recognizing three sleep categories rather than five sleep stages, thus higher accuracy can be expected; 2) three sleep categories are recognized by analyzing EEG signals only using two EEG electrodes, so the user experience is improved because he/she is attached with fewer sensors during sleep. Using quantitative features obtained from EEG signals, we developed a new automatic sleep-staging framework that consists of a multi-class support vector machine (SVM) classification based on a decision tree approach. We used polysomnographic data from PhysioBank database to train and evaluate the performance of the framework, where the sleep stages have been visually annotated. The results demonstrated that the proposed approach achieves high classification performance, which helps to measure sleep quality accurately.
RECOMMENDING AUTOMATED EXTRACT METHOD REFACTORING

Extract Method is a key refactoring for improving software maintainability. In fact, small methods with meaningful names improve source code readability and also favor reuse. For such reasons, Extract Method is one of the most popular and versatile refactorings. However, recent empirical research shows that refactoring tools designed to automate this refactoring are often underused and, more important, they do not support developers in the identification of potential code fragments for extraction. To address this issue, we propose an approach to identify Extract Method refactoring opportunities that are directly automated by IDE-based refactoring tools. The proposed approach relies on a heuristic to rank the identified refactoring opportunities based on the design principle of separation of concerns. Specifically, we assume that the structural dependencies established by a Extract Method candidate should be very different from the ones established by the remaining statements in the original method. In a first study using synthesized Extract Method opportunities introduced by inlining method invocations, shows that our approach is more effective (w.r.t. recall and precision) than a state-of-the-art tool. In a second study, with 13 open-source systems our approach achieved an overall recall of 59.1%. Moreover, when we tolerate suggestions that are slight variations of known Extract Method instances (e.g., including/excluding a single statement), recall rises to 66.6%.
Neutron Monitor Comparison by Spectral Analysis in relation to Cosmic Ray Intensity in the period 2013-2018

Morlet Wavelet Analysis is applied to the period 2013–2018 corresponding to the decreasing phase of the solar cycle 24. The aim is to identify characteristic periodicities between days to one years in the neutron monitor counting rates of a set of 22 neutron monitors distributed around the world and at different elevation above sea level (a.s.l). Six periodicities are observed once the one day period is removed: The synodic solar rotation (27–28.3 days) and its second harmonic, the near annual period and 47, 93 and 133 days periods. The last one is especially strong since 2014. An artificial neutron monitor power spectrum has been built by averaging the obtained power spectrum of the 22 neutron monitors. This average power spectrum is used as reference for the rest of neutron monitors. After the comparison, we have defined two indices, Q j and Qx, the first one determines how much the power spectrum of a single station differs with respect to the reference spectrum and the second one is the weighted cross-correlation between a single neutron monitor and the other 21. Finally, we define a station factor quality as the mean value of Q j and Qx.
Physical Therapy as Adjuvant Therapy for Patients Undergoing Allogeneic Haematopoietic Stem Cell Transplantation

Copyright: © 2013 Morishita S, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Allogeneic hematopoietic stem cell transplantation (alloHSCT) has been increasingly used in treating hematopoieticdiseases worldwide[1,2]. This treatment has disease-specific5-year survival rates ranging from 5%–80 %[3]. Allo-HSCT is associated with numerous treatment-relatedsomatic, psychological, and psychosocial side effects[4]. Patients experience considerable physical and functional deterioration and diminished psychological well-being before, during, and after allo-HSCT [5,6]. Our previous study showed reduced skeletal muscle strength and exercise tolerance in patients prior to allo-HSCT compared with population norms (respectively almost 20%) [7]. Furthermore, we also showed that patients receiving alloHSCT experienced significant (almost 20%) decrease in grip strength, knee-extensor strength, and 6-min walking distance following transplantation[8]. Therefore, in patients receiving allo-HSCT, physical exercise has been proposed as a means of recovering from the loss of functional capacity and muscle weakness that can occur with prolonged lack of physical activity after transplantation [9].
Age-related changes in haematologic parameters of cage-raised Japanese quails (Cortunix japonica)

Blood samples were collected from clinically normal, cage-raised Japanese quails at regular intervals, over a six-week period. Full routine haematological analyses were carried out to establish reference values for growing individuals of this species and to assess age-related changes. The results of this study showed an initial significant reduction (p˂0.001) in the values of the mean corpuscular volume (MCV) and mean corpuscular haemoglobin (MCH) at the second week of age relative to the values at the first week of age. However, MCV values significantly increased (p˂0.001) weekly, up to the sixth week of age. Similarly, significant decrease (p˂0.05) was observed in the total white blood cell count at the second week of age, but subsequently remains unaltered throughout the period of the experiment. However, the heterophil:lymphocyte ratio increased significantly (p<0.05) with increase in the age of birds. The observations in this study compares favourably with published literature. Key words: Quails, haematology, age.
FOOD LIMITATION OF BIVALVE LARVAE IN COASTAL WATERS OF NORTH WESTERN EUROPE

There is much debate on whether bivalve larvae are food limited in their natural environment. In this study field data on numbers of bivalve larvae and their most important food, small phytoplankton, were combined with model predictions of energetic requirements of larvae. Bivalve larvae were monitored during the year 2000 at 10 different study sites in 4 different areas (Limfjorden, Sylt-Rømø bight, Western Wadden Sea and Schelde estuary) along the coast of North Western Europe. The energetic requirements of a larva were calculated with the help of a dynamic energy budget model (DEB-model), based on literature data. At 15°C, the maintenance costs of a 200 μm bivalve larva were 1.9 x 10-5 J larva-1 d-1, while the maximal assimilation rate, resulting in maximal growth, was 6.2 × 10-3 J larva-1 d-1. Next, potential assimilation rates of larvae in the field were estimated based on the energy content of the palatable phytoplankton species. In general these rates ranged between 10-5 and 10-3 J larva-1 d-1. Single or multiple larval peaks occurred from May till September with maximum densities ranging from 17 up to 392 larvae l-1. At most study sites, larvae were able to provide in their maintenance costs, but were never able to attain maximal growth rates. This study therefore suggests that bivalve larvae are generally food limited throughout the year, irrespective of the study site. Submitted to the Journal of Sea Research. Chapter 4 Food limitation of bivalve larvae
Distributional semantics and the conceptual foundations of verb meaning: how neural word embeddings memorize the unaccusative hypothesis

In the present paper, I investigate whether and how neural word embeddings can be understood to encode not only idiosyncratic aspects of word meaning but also the kind of general and abstract concepts that are central to theoretical approaches of lexical semantics. To this end, I compute the difference between general-purpose embeddings of intransitive verbs, and taskspecific embeddings of the same verbs that capture their similarity according to the unaccusative hypothesis. I approximate the resulting set of difference vectors with their nearest neighbors in the embedding space and show that the nearest neighbors correspond to prototypical linguistic realizations of unergativity and unaccusativity. My study thus suggests that word embeddings may provide a novel and empirically grounded perspective on the conceptual underpinnings of verb meaning.
A Day in the Life in the Universal Village Applications of a General Platform for Continuous Mobile Monitoring

The universal village can be characterized by the ubiquity of sensors and connected infrastructure which enable intelligent services that improve the quality of our lives. In this paper, we describe various novel services built atop a general purpose mobile platform for continuous mobile monitoring. Our platform was developed with next-generation healthcare services in mind, but has applicability more broadly as a platform for deploying real-time services that utilize data coming from arbitrary sensors. We provide an overview of our platform, and highlight a few services that act as new touchpoints between a user and the universal village infrastructure. We thread these services through a prototypical day and describe how they serve to define a new normal for quality of life in the universal village. Keywords—mobile platform; continuous sensing; services; healthcare; remote monitoring; stress
Kernel Learning and Meta Kernels for Transfer Learning

In transfer learning, the task is to find a suitable learning bias for a new target dataset, given a set of related source datasets. In this study, we extend our previous work on kernel-based inductive transfer, where we aim at inducing a kernel from the source datasets, which leads to good predictive accuracy on the new target data. To find such a kernel, we proceed in three steps. First, we find a predictive kernel for each of the source datasets. Second, we induce a meta-classifier, which combines these source kernels into a new kernel for the target dataset. Third, we use the new target kernel to learn a successful classifier for the target data. The first step is a perfect application for kernel learning algorithms, because here we are more interested in finding a predictive kernel rather than a classifier. We present a new fast method based on semidefinite programming and a restricted classifier space to learn such source kernels. To combine these source kernels into a suitable kernel for the target learning task, we present three new meta kernels that quantify the similarity of two datasets. Preliminary experiments indicate that the approach performs well on datasets with structured data.