Miracle-dz/UniFAR-FTUs huggingface dataset:
Onset-coda asymmetry in second-language syllable perception by Japanese teachers of English

The paper reports the results of an experiment in second-language speech that provides further evidence for the view that syllable onsets and codas are asymmetric, and for the view that English proficiency affects Japanese listeners’ speech perception performance. When two groups of Japanese listeners (Japanese college students and Japanese teachers of English) were asked to count syllables in spoken English words and nonwords, the performances of both groups declined as the number of consonants in the target item increased, but onsets led to a more drastic decline in performance than did codas. The results of Japanese teachers of English further revealed that upper-level English teachers performed the task significantly better than Japanese college students whereas lower-level English teachers did significantly worse. Among the three groups of participants, lower-level English teachers were the most strongly affected by phonological constraints on syllables in Japanese.
A feasibility study approach for underground railways-a case study : Line 4 of Athens metro

This article introduces a methodology for conducting feasibility studies for underground railways. The study addresses the factors that determine station location, the attributes that enhance rail use through passenger satisfaction. It incorporates the principles of CBA and financial analysis, presents the social impacts and their requirements for the achievement of the social objectives, and discusses the benefits (social, economic, environmental) that are accrued from the existence of underground railways that render them crucial elements for developing sustainable cities. The case study based on Line 4 of the Athens metro has been used to provide an overall description of the implementation of this methodology by using qualitative and quantitative data. The study reveals that the feasibility of a project is improved by assessing its aspects on a global scale, while the perception of its utility by the target-market is integral in its success.
The Emerging Market Crisis and Stock Market Linkages: Further Evidence

This study examines the long-run price relationship and the dynamic price transmission among the U.S., Germany, and four major Eastern European emerging stock markets, with particular attention to the impact of the 1998 Russian financial crisis. The results show that both the long-run price relationship and the dynamic price transmission were strengthened among these markets after the crisis. The influence of Germany became noticeable on all the Eastern European markets only after the crisis but not before the crisis. We also conduct a rolling generalized VAR analysis to confirm the robustness of the main findings.
Heavy Metals Contamination in Roadside Dust along Major Traffic Roads in Jos Metropolitan Area, Nigeria

Heavy metal concentration in roadside dusts are increasingly becoming of health concern. Five major traffic roadside dust were determined for Cu, Pb, Ni, Zn, Fe, Cd, Mn and Cr contamination. Metal concentration in the dusts indicated Cu concentration ranged from 24.5 – 67.0 mg/kg, Pb 25.0 – 66 mg/kg, Ni 1.23 – 3.88 mg/kg, Zn 35.0 – 123 mg/kg, Fe 48.5 – 125 mg/kg, Cd 1.54 – 2.58 mg/kg, Mn 1.15 – 2.58 mg/kg and Cr 1.13 – 2.79 mg/kg. The accumulation of the heavy metals in the soil dust is greatly influenced by traffic volume and the metals exhibited a significant reduction in roadside dust with increasing distance from the road. Four methods of assessing pollution were used to assess the extent of pollution. All the four methods revealed that site ABW, YGW and GJR are pollution impacted as compared MMW and BRR sites. The result suggest mixed origin of pollution sources including human activities, vehicular emissions and lithogenic occurrences of the metals from road construction currently in some of the sites studied. The findings herein will serve to create awareness of vehicular heavy metal pollution and therefore suggest a regular monitoring to ensure suitable management of the urban environment and reduction of traffic related contamination of soil, plants and water in Jos Nigeria. Keywords: Roadside Soil Dust; Heavy Metals Contamination; Enrichment Factor; contamination Factor; Pollution Load Index; Geoaccumulation Index; Statistical Analysis.
Semiparametric Smooth Coef ’ cient Models

In this article, we propose a semiparametric smooth coef cient model as a useful yet  exible speci cation for studying a general regression relationship with varying coef cients. The article proposes a local least squares method with a kernel weight function to estimate the smooth coef cient function. The consistency of the estimator and its asymptotic normality are established. A simple statistic for testing a parametric model versus the semiparametric smooth coef cient model is proposed. An empirical application of the proposed method is presented with an estimation of the production function of the nonmetal mineral industry in China. The empirical  ndings show that the intermediate production and management expense has played a vital role and is an unbalanced determinant of the labor and capital elasticities of output in production.
Stable Specification Search in Structural Equation Models with Latent Variables

In our previous study, we introduced stable specification search for cross-sectional data (S3C). It is an exploratory causal method that combines the concept of stability selection and multi-objective optimization to search for stable and parsimonious causal structures across the entire range of model complexities. S3C, however, is designed to model causal relations among observed variables. In this study, we extended S3C to S3C-Latent, to model linear causal relations between latent variables that are measured through observed proxies. We evaluated S3C-Latent on simulated data and compared the results to those of PC-MIMBuild, an extension of the PC algorithm, the state-of-the-art causal discovery method. The comparison shows that S3C-Latent achieved better performance. We also applied S3C-Latent to real-world data of children with attention deficit/hyperactivity disorder and data about measuring mental abilities among pupils. The results are consistent with those of previous studies.
Changes in Resting-State Connectivity following Melody-Based Therapy in a Patient with Aphasia

Melody-based treatments for patients with aphasia rely on the notion of preserved musical abilities in the RH, following left hemisphere damage. However, despite evidence for their effectiveness, the role of the RH is still an open question. We measured changes in resting-state functional connectivity following melody-based intervention, to identify lateralization of treatment-related changes. A patient with aphasia due to left frontal and temporal hemorrhages following traumatic brain injuries (TBI) more than three years earlier received 48 sessions of melody-based intervention. Behavioral measures improved and were maintained at the 8-week posttreatment follow-up. Resting-state fMRI data collected before and after treatment showed an increase in connectivity between motor speech control areas (bilateral supplementary motor areas and insulae) and RH language areas (inferior frontal gyrus pars triangularis and pars opercularis). This change, which was specific for the RH, was greater than changes in a baseline interval measured before treatment. No changes in RH connectivity were found in a matched control TBI patient scanned at the same intervals. These results are compatible with a compensatory role for RH language areas following melody-based intervention. They further suggest that this therapy intervenes at the level of the interface between language areas and speech motor control areas necessary for language production.
Antioxidant, Antimutagenic and Cytotoxic Properties of Essential Oil from Corchorus olitorius L. Flowers and Leaf

Background: This present research highlight the phytochemical profile, the antioxidant, the antimicrobial, the antimutagenic and the antiproliferative activities of an essential oil extracted from Corchorus olitorius L. flowers and leaf (COFL), an aromatic plant widely distributed in Tunisia and used as a traditional food plant. Results: Gas chromatography/ mass spectrometry was used to determine the composition of the COFL essential oil (COFL-EO). Forty-three components were identified and the main compounds were benzaldehyde (56%), methyl 4-methoxysalicylate (6.55%) and carvacrol (4.75%). The COFL-EO was also found to possess antioxidant activities, as evaluated by the 1,1-diphenyl-2-picrylhydrazyl (DPPH) radical method and β-carotene bleaching assay. The antibacterial activities showed good growth inhibition compared to positive controls. The diameter of the inhibition zones reached a maximum of 16.7 ± 0.1 mm when tested against Salmonella typhimurium using just 6 mg extract. On the other hand, the antimutagenic activity was assessed using the Ames Salmonella/microsome mutagenicity test and the COLF-EO exhibited high antimutagenic effects at 0.125, 0.0125 and 0.00125 mg/plate. Antiproliferative activity of this essential oil evaluated in four mammalian cells lines was significantly stronger in Hela cell line (IC 50 =4 ± 0.98 µg/mL). Conclusion: Overall, results presented here suggest that the COFL-EO is a potential new source of active ingredients for food and pharmaceutical industry.
Quantitative Modeling and Analysis of Service-Oriented Real-Time Systems using Interval Probabilistic Timed Automata

One of the key challenges in service-oriented systems engineering is the prediction and assurance of non-functional properties, such as the reliability and the availability of composite interorganizational services. Such systems are often characterized by a variety of inherent uncertainties, which must be addressed in the modeling and the analysis approach. The different relevant types of uncertainties can be categorized into (1) epistemic uncertainties due to incomplete knowledge and (2) randomization as explicitly used in protocols or as a result of physical processes. In this report, we study a probabilistic timed model which allows us to quantitatively reason about nonfunctional properties for a restricted class of service-oriented real-time systems using formal methods. To properly motivate the choice for the used approach, we devise a requirements catalogue for the modeling and the analysis of probabilistic real-time systems with uncertainties and provide evidence that the uncertainties of type (1) and (2) in the targeted systems have a major impact on the used models and require distinguished analysis approaches. The formal model we use in this report are Interval Probabilistic Timed Automata (IPTA). Based on the outlined requirements, we give evidence that this model provides both enough expressiveness for a realistic and modular specification of the targeted class of systems, and suitable formal methods for analyzing properties, such as safety and reliability properties in a quantitative manner. As technical means for the quantitative analysis, we build on probabilistic model checking, specifically on probabilistic time-bounded reachability analysis and computation of expected reachability rewards and costs. To carry out the quantitative analysis using probabilistic model checking, we developed an extension of the Prism tool for modeling and analyzing IPTA. Our extension of Prism introduces a means for modeling probabilistic uncertainty in the form of probability intervals, as required for IPTA. For analyzing IPTA, our Prism extension moreover adds support for probabilistic reachability checking and computation of expected rewards and costs. We discuss the performance of our extended version of Prism and compare the interval-based IPTA approach to models with fixed probabilities.
Neural Substrates of Specialized Knowledge Representation: An fMRI study

Les techniques d’imagerie cerebrale peuvent etre employees dans la recherche des connaissances specialisees afin de decouvrir la facon dont les concepts specialises sont representes dans le cerveau. L’etude d’IRMf decrite dans cet article porte sur la perception des unites lexicales generales et specialisees, ainsi que de leurs significations semantiques, chez des sujets specialistes en geologie et des sujets non-experts. Les sujets ont effectue des tâches d’appariement semantique par rapport a des mots de la langue generale et a des termes specialises faisant partie de la categorie semantique des instruments, soit menagers soit specialises. Les resultats indiquent que le traitement des termes specialises repose sur l’experience prealable des sujets avec l’objet, ce qui confirme l’hypothese que, lors de l’execution d’une tâche specialisee, les specialistes activent une partie du cerveau differente de celle utilisee par les non-experts. L’experience nous a permis d’obtenir des donnees significatives sur les systemes cerebraux impliques dans ces processus cognitifs.
Tsho Glacial Lake Outburst Flood (GLOF) in Bhutan: cause and impact.

Glacial Lake Outburst Flood (GLOF) is an inherent threat in countries in the Hindu Kush Himalayan (HKH) region and is projected to increase in the face of climate change. One of the recent GLOF events in the region was the outburst of Lemthang Tsho (lake) in Bhutan on 28 July 2015. This paper discusses the cause and impact of the event based on the analysis of multi-temporal satellite images and field observation. The event, which was small to medium in volume, was triggered by the emptying of two supraglacial ponds located upstream of Lemthang Tsho. The area had experienced heavy rainfall till the morning of 28 July. On the same day, at 7:10 am local Bhutan time, a 5.1 magnitude earthquake struck about 177 km southeast of the lake. In the absence of firsthand information from the field, it cannot be confirmed that these two events triggered the lake outburst that took place around 3 pm. However, the possibility cannot be ruled out, either. The rainfall and earthquake are likely to have had a role in triggering the outburst.
Resource Allocation for Network Slices in 5G with Network Resource Pricing

End-to-end network slicing has been viewed as a key enabler for the next generation mobile network (5G), where a Slice Provider (SP) creates various network slices for Slice Customers (SCs) to accommodate diverse services. Due to resource isolation, effective resource allocation for coexisted multiple network slices, \textit{i.e.} network slice dimensioning, is essential to maximize network resource efficiency. From the perspective of operators, both SP and SC pursue a profit-earning business model. However, the relationship between resource efficiency and profit maximization is not clear so far. In this paper, we study network slice dimensioning with resource pricing policy, by exploring this relationship. We first develop an optimization framework for network slice dimensioning, in which the Slice Customer's Problem (SCP) maximizes the SC's profit and the Slice Provider's Problem (SPP) maximizes net social welfare (resource efficiency). We find that maximization of net social welfare and SP's profit are two consistent objectives when resources are scarce; otherwise, there is a tradeoff. Based on this finding, we propose a low-complexity distributed algorithm to achieve near-optimal net social welfare with profit guarantee for SP/SCs. Simulations and numerical results verify the effectiveness of our proposed slice dimensioning strategy, which can help fully exploiting the capability of network slicing.
Granulosa Cell Tumor of the Ovary: A Retrospective Study of 31 Cases and a Review of the Literature

Background Adult granulosa cell tumors (AGCTs) are the most common sex cord-stromal tumors. Unlike epithelial ovarian tumors, they occur in young women and are usually detected at an early stage. The aim of this study was to report the clinical and pathological characteristics of AGCT patients and to identify the prognostic factors. Methods All cases of AGCTs, treated at Salah Azaïz Institute between 1995 and 2010, were retrospectively included. Kaplan-Meier's statistical method was used to assess the relapse-free survival and the overall survival. Results The final cohort included 31 patients with AGCT. The mean age was 53 years (35–73 years). Patients mainly presented with abdominal mass and/or pain (61%, n = 19). Mean tumor size was 20 cm. The majority of patients had a stage I disease (61%, n = 19). Two among 3 patients with stage IV disease had liver metastasis. Mitotic index was low in 45% of cases (n = 14). Surgical treatment was optimal in almost all cases (90%, n = 28). The median follow-up time was 14 years (1–184 months). Ten patients relapsed (32%) with a median RFS of 8.4 years (6.8–9.9 years). Mean overall survival was 13 years (11–15 years). Stage I disease and low-to-intermediate mitotic index were associated with a better prognosis in univariate analysis (resp., p = 0.05 and p = 0.02) but were not independent prognostic factors. Conclusion GCTs have a long natural history with common late relapses. Hence, long active follow-up is recommended. In Tunisian patients, hepatic metastases were more frequent than occidental series. The prognosis remains good and initial staging at diagnosis is an important prognostic factor.
Evaluation of Natural Radioactivity Levels and Radiological Hazards in Soil Samples of Sarıkamış Province, Kars, Turkey

In this study, the activity concentrations of 121 soil samples gathered from diverse places of Sarikamis of Kars were found out employing NaI (Tl) gamma spectrometry. It was monitored that the concentration of the natural radionuclides 40K, 226Ra and 232Th in the soil samples altered from 148.0±31.2 to 909.2±38.4 Bqkg-1, BDL to 38.1±8.9 Bqkg-1 and 7.6±0.7 to 53.0±7.4 Bqkg-1, respectively. Also relatively low deposits of 137Cs were found in the investigated area, where the activity concentrations ranged from BDL to 21.0±1.1 Bqkg-1. The determined average values of activity concentrations of 226Ra, 232Th and 40K were employed to work out the radiation hazard indices in soil samples. The total observed dose rate in the working area varied from 18.4 to 87.7 nGyh-1 with the mean value of 46.9 nGyh-1 and also the annual effective dose ranged between 22.6 and 107.5 µSv with the average value of 57.7 µSv. It was observed that the values established whenever compared to the world values allowed are under the standard limits for the environment.
Larval exposure to the neonicotinoid imidacloprid impacts adult size in the farmland butterfly Pieris brassicae

Populations of farmland butterflies have been suffering from substantial population declines in recent decades. These declines have been correlated with neonicotinoid usage both in Europe and North America but experimental evidence linking these correlations is lacking. The potential for non-target butterflies to be exposed to trace levels of neonicotinoids is high, due to the widespread contamination of agricultural soils and wild plants in field margins. Here we provide experimental evidence that field realistic, sub-lethal exposure to the neonicotinoid imidacloprid negatively impacts the development of the common farmland butterfly Pieris brassicae. Cabbage plants were watered with either 0, 1, 10, 100 or 200 parts per billion imidacloprid, to represent field margin plants growing in contaminated agricultural soils and these were fed to P. brassicae larvae. The approximate digestibility (AD) of the cabbage as well as behavioural responses by the larvae to simulated predator attacks were measured but neither were affected by neonicotinoid treatment. However, the duration of pupation and the size of the adult butterflies were both significantly reduced in the exposed butterflies compared to the controls, suggesting that adult fitness is compromised through exposure to this neonicotinoid.
Patterns of Cervical Disc Degeneration: Analysis of Magnetic Resonance Imaging of Over 1000 Symptomatic Subjects

Study Design: Cross-sectional study. Objectives: The aim of this study was to evaluate cervical disc degeneration on magnetic resonance imaging (MRI) in a large population of symptomatic patients and to provide baseline data on the pattern of degeneration in order to understand how the cervical spine ages. Methods: We performed a cross-sectional study of 1059 patients who underwent upright cervical MRI for neck pain with and without neurological symptoms. A total of 6354 cervical discs from C2/3 to C7/T1 were evaluated. Cervical disc degeneration was evaluated on T2-weighted MRI and graded into 4 categories (Grades 0-III). Positive degeneration was defined as greater than Grade II. The correlation between age and total grade of degeneration of each patient was evaluated, as well as the prevalence and pattern of degeneration. Results: The average number of degenerated disc levels and the total grade of cervical disc degeneration significantly increase with age. In the patient group with 1-level degeneration, C5/6 was the most common degenerated level followed by C4/5 and C6/7. In the group with 2-level degeneration, C5/6 & C6/7 was most common followed by C4/5 & C5/6 and C3/4 & C4/5. Skip level degeneration was significantly rarer than contiguous level degeneration, and C7/T1 and C2/3 were the most unlikely to degenerate in multilevel degeneration. Conclusion: Disc degeneration is most common in the middle cervical spine (C5/6) and progresses to contiguous levels, except for C7/T1 and C2/3. This pattern may play a role in adjacent-level disc degeneration associated with spinal fusion.
A hybrid approach of interpolations and CNN to obtain super-resolution

We propose a novel architecture that learns an end-to-end mapping function to improve the spatial resolution of the input natural images. The model is unique in forming a nonlinear combination of three traditional interpolation techniques using the convolutional neural network. Another proposed architecture uses a skip connection with nearest neighbor interpolation, achieving almost similar results. The architectures have been carefully designed to ensure that the reconstructed images lie precisely in the manifold of high-resolution images, thereby preserving the high-frequency components with fine details. We have compared with the state of the art and recent deep learning based natural image super-resolution techniques and found that our methods are able to preserve the sharp details in the image, while also obtaining comparable or better PSNR than them. Since our methods use only traditional interpolations and a shallow CNN with less number of smaller filters, the computational cost is kept low. We have reported the results of two proposed architectures on five standard datasets, for an upscale factor of 2. Our methods generalize well in most cases, which is evident from the better results obtained with increasingly complex datasets. For 4-times upscaling, we have designed similar architectures for comparing with other methods.