Miracle-dz/UniFAR-FTUs huggingface dataset:
Phonological markedness effects in sentence formation*1

Earlier research has found that phonological markedness constraints (for example, against stress clash or sibilant sequences) statistically influence speakers’ choices between particular syntactic constructions and between synonymous words. In this study, we test phonological constraints not just in particular cases, but across the board. We employ a novel method that statistically models the distribution of WORD BIGRAMS (consecutive two-word sequences) and how this distribution is influenced by phonological constraints. Our study of multiple corpora indicates that several phonological constraints do indeed play a statistically significant role in English sentence formation. We also show that by examining particular subsets of the corpora we can diagnose the mechanisms whereby phonologically marked sequences come to be underrepresented. We conclude by discussing modes of grammatical organization compatible with our findings.
Sizing/Optimization of a Small Satellite Energy Storage and Attitude Control System

Abstract : The recent advent of miniature single gimbal control moment gyroscopes has spawned interest in variable speed versions for combined energy storage and attitude control systems on small satellites. Although much has been studied on the theory behind such a system, little has been done In optimally sizing these actuators for small satellite applications. Therefore this paper investigates the fundamental design concepts, optimal sizing, and mission benefits for these actuators. Given a set of small satellite agility and energy storage requirements, an optimal, nonlinear programming method is applied to this problem.
Fe b 20 19 Approximate unitary n 2 / 3-designs give rise to quantum channels with super additive classical capacity

In a breakthrough, Hastings [Has09] showed that there exist quantum channels whose classical capacity is superadditive i.e. more classical information can be transmitted by quantum encoding strategies entangled across multiple channel uses as compared to unentangled quantum encoding strategies. Hastings’ proof used Haar random unitaries to exhibit superadditivity. In this paper we show that a unitary chosen uniformly at random from an approximate ndesign gives rise to a quantum channel with superadditive classical capacity, where n is the dimension of the unitary exhibiting the Stinespring dilation of the channel superoperator. We do so by showing that the minimum output von Neumann entropy of a quantum channel arising from an approximate unitary n-design is subadditive, which by Shor’s work [Sho04] implies superadditivity of classical capacity of quantum channels. We follow the geometric functional analytic approach of Aubrun, Szarek andWerner [ASW10a] in order to prove our result. More precisely we prove a sharp Dvoretzky-like theorem stating that, with high probability under the choice of a unitary from an approximate t-design, random subspaces of large dimension make a Lipschitz function take almost constant value. Such theorems were known earlier only for Haar random unitaries. We obtain our result by appealing to Low’s technique [Low09] for proving concentration of measure for an approximate t-design, combined with a stratified analysis of the variational behaviour of Lipschitz functions on the unit sphere in high dimension. The stratified analysis is the main echnical advance of this work. Haar random unitaries require at least Ω(n) random bits in order to describe them with good precision. In contrast, there exist exact n-designs using only O(n logn) random bits for a precise description [Kup06]. Thus, our work can be viewed as a partial derandomisation of Hastings’ result, and a step towards the quest of finding an explicit quantum channel with superadditive classical capacity.
Tropical seaweeds improve cardiovascular and metabolic health of diet-induced obese and hypertensive rats

Seaweeds have been an important part of the diet of coastal populations in Asia possibly for millennia but only a few scattered coastal communities in Europe and the Americas have maintained these traditions. Our studies have investigated the potential of two tropical seaweeds grown commercially in Asia, Sarconema and Caulerpa spp. , as functional foods for the reversal of metabolic syndrome and possible mechanisms. Sarconema spp. are a source of carrageenans used as thickening and gelling agents in foods, while Caulerpa spp. are consumed in Southeast Asia as lowenergy foods with high contents of vitamins and minerals. For our studies, male Wistar rats were divided into groups in a 16-week protocol: corn starch diet-fed rats (C); C rats supplemented with 5% dried seaweed for the last 8 weeks; high-carbohydrate, high-fat diet-fed rats (H); and H rats supplemented with 5% dried seaweed for the last 8 weeks. H rats developed obesity, hypertension, dyslipidaemia, glucose intolerance, fatty liver and increased left ventricular collagen deposition, infiltration of inflammatory cells and plasma liver enzyme activities. Seaweed supplementation decreased body weight, abdominal and liver fat, systolic blood pressure, plasma lipid concentrations, plasma activities of liver enzymes and collagen deposition. Furthermore, seaweed supplementation modulated gut microbiota. Possible mechanisms for improved cardiovascular and metabolic health include a reduced infiltration of inflammatory cells into organs as well as an increased intake of fibre modulating gut microbiota composition.
Evaluation of Human Capital in the Macroregion (on the Example of the Yenisey Siberia)

The article is devoted to the problem of measuring and estimating the human capital of the natural resource macroregion, whose territory is characterized by a high level of social and economic asymmetry. It presents results of testing of modified index of human capital in context of interdisciplinary approach. The study was based on survey findings, along with statistical data. The satisfaction of the population with the quality of life is a key indicator of the dynamics of human capital in the long term. The authors give recommendations on the development of information support of territorial policy.
Onocerane testifies to dry climatic events during the Quaternary in the Tropics.

An unusual molecular fossil (onocerane I) has been detected for the first time in Quaternary lacustrine sediments (Lagoa do Caçó, NE Brazil). This molecule was initially thought to attest to the former presence of ferns or club mosses. According to possible plant precursors of onocerane-related molecules recorded in the literature and by comparison with palynological results and palaeoclimatic data, we here provide evidence that club mosses and ferns cannot account as sources of onocerane I in this setting. Onocerane I is abundant in the lipid extracts of sediments deposited during the two driest periods recorded in Northern Brazil (Last Glacial Maximum and Younger Dryas). This molecule is therefore suspected to be diagnostic of the development of plants adapted to dry or semi-arid conditions in this
Empirical Analysis of Stock Returns and Volatility : Evidence from Seven Asian Stock Markets Based on TAR-GARCH Model

This paper investigates the time-series behavior of stock returns for seven Asian stock markets. In most cases, higher average returns appear to be associated with a higher level of volatility. Testing the relationship between stock returns and unexpected volatility, the evidence shows that four out of seven Asian stock markets have significant results. Further analyzing the relationship between stock returns and time-varying volatility by using Threshold Autoregressive GARCH(1,1)-in-mean specification indicates that the null hypothesis of no asymmetric effect on the conditional volatility is rejected for the daily data. However, the null cannot be rejected for the monthly data.
Critical angle for interfacial phonon scattering: Results from ab initio lattice dynamics calculations

Thermal boundary resistance is a critical quantity that controls heat transfer at the nanoscale, which is primarily related to interfacial phonon scattering. Here, we combine lattice dynamics calculations and inputs from first principles ab initio simulations to predict phonon transmission at the Si/Ge interface as a function of both the phonon frequency and the phonon wavevector. This technique allows us to determine the overall thermal transmission coefficient as a function of the phonon scattering direction and frequency. Our results show that the thermal energy transmission is highly anisotropic, while thermal energy reflection is almost isotropic. In addition, we found the existence of a global critical angle of transmission beyond which almost no thermal energy is transmitted. This critical angle around 50° is found to be almost independent of the interaction range between Si and Ge, the interfacial bonding strength, and the temperature above 30 K. We interpret these results by carrying out a spectr.
FLUID MECHANICS ANALYSIS IN VOLLEYBALL SERVICES

The service is considered the first attack action in volleyball games. Erratic behavior also appears along the trajectory, hindering reception. We suspect that these effects can be related to the ‘drag crisis’ phenomenon described in fluid mechanics. Thus, we decided to quantify the trajectories of four types of services (underhand, floater, floater with jump, overhand with jump). Altogether, twenty-six real trajectories of service balls were recorded and 3D reconstructed with the DVIDEOW system. Polynomials of the 4th degree of time were adjusted to the coordinates of each trajectory, obtaining the speed and acceleration of the balls. We compared, in the horizontal and vertical planes, the real trajectories with simulated ones in which the ball was submitted to the same initial conditions but without any aerodynamic drag forces. We calculated the Reynolds Number (Re), the drag coefficient (CD) and the drag force (FD), applying the model presented at the XVI ISB Congress (Depra et al., 1997). We observed that all services are placed in the region of the so-called drag crisis (1.105 < Re < 3.105) and present great variations of drag coefficient (Fig. 1). We also observed that the four types of services analyzed can be ordered in an increasing sequence of Reynolds numbers. The first three types presented a decreasing sequence of median values of CD, accompanying the CD(Re) literature curve (line in Fig. 1). Even so, we observed the growth of the drag force (FD) as a function of Re (Fig. 2). Comparing the magnitude of the two forces that act on the ball, we estimated that in the case of the overhand service with jump the drag force becomes up to 1.4 times larger than the weight force (mg = 2.55 N). All these kind of quantification may also be used to compare characteristics of different players.
Optimization of extraction of phenolic compounds from Tokaji Aszú marc using response surface methodology

Similarly to other industries wineries also increasingly attempt to minimize and utilize waste to protect our environment. The aim of this study was to determine the optimal parameters (temperature, solvent concentration, and time) of extracting total polyphenol content (TPC) from Tokaji Aszú marc using two different extraction solvents: ethanol–water and isopropanol–water (1:4 solid/liquid ratio). The extractions were achieved based on Central Composite Design with Response Surface Method (CCRD–RSM). The optimal extraction parameters in the case of ethanol–water solvent: 60 °C temperature, 59.5% ethanol concentration in solvent, 5 h. At these parameters the probable TPC concentration is 23966.2 uM GAE/L. The optimal extraction parameters in the case of isopropanol–water solvent: 60 °C temperature, 52% ethanol concentration in solvent, 5 h. At these parameters the probable TPC concentration is 7188.44 uM GAE/L. In both cases the binary solvent was better than the mono-solvent. Ethanol–water solvent was more efficient than the isopropanol–water solvent.
Understanding of the Importance of Mother Tongue Learning

Mother tongue is valuable due to several reasons. Mother tongue is vital in framing the thinking and emotions of people. Learning to speak in the mother tongue is very necessary for a child’s comprehensive development. Being fluent in the mother tongue, which is also known as the native language, benefits the child in numerous ways. It associates him to his culture, ensures enhanced cognitive development, and supports in the learning of other languages. A child first comprehends what is around them through the language they hear their mother communicating in from before they are born and thought their lives. Many children across the developing world are learning very little in school, a reality that can be linked to teaching that is in a language they do not fully understand. It is a practice that leads to limited or non-existent learning and acquisition of knowledge and skills, alienating experiences, and high drop-out and repetition rates. To improve the quality of education, language policies need to take account of mother-tongue learning. Models of education which ignore the mother tongue in the early years can be unproductive, ineffective and have a negative effect on children’s learning. Mother-tongue education at least in early years can enable teachers to teach, and learners to learn more effectively.
Aalborg Universitet Secondary Control for Reactive Power Sharing in Droop-Controlled Islanded

This paper focuses on the islanded operation of microgrids. In this mode of operation, the microsources are required to cooperate autonomously to regulate the local grid voltage and frequency. Droop control is typically used to achieve this autonomous voltage and frequency regulation. However, droop control has real and reactive power sharing limitations when there are mismatches between the microsources. This paper analyses the effect due to mismatches in the power line impedances connecting the source inverters to the microgrid. From the simulations results obtained, it was shown that the reactive power demand is unequally shared between the microsource inverters when there are mismatches between the power line impedances. To achieve equal reactive power sharing between the inverters, an external loop requiring low bandwidth communications was implemented in a central controller. Simulation results are presented showing the feasibility of the proposed solution in achieving reactive power sharing between the inverters connected to the microgrid.
Improving Ant Collaborative Filtering on Sparsity via Dimension Reduction

Recommender systems should be able to handle highly sparse training data that continues to change over time. Among the many solutions, Ant Colony Optimization, as a kind of optimization algorithm modeled on the actions of an ant colony, enjoys the favorable characteristic of being optimal, which has not been easily achieved by other kinds of algorithms. A recent work adopting genetic optimization proposes a collaborative filtering scheme: Ant Collaborative Filtering (ACF), which models the pheromone of ants for a recommender system in two ways: (1) use the pheromone exchange to model the ratings given by users with respect to items; (2) use the evaporation of existing pheromone to model the evolution of users’ preference change over time. This mechanism helps to identify the users and the items most related, even in the case of sparsity, and can capture the drift of user preferences over time. However, it reveals that many users share the same preference over items, which means it is not necessary to initialize each user with a unique type of pheromone, as was done with the ACF. Regarding the sparsity problem, this work takes one step further to improve the Ant Collaborative Filtering’s performance by adding a clustering step in the initialization phase to reduce the dimension of the rate matrix, which leads to the results that K<<#users, where K is the number of clusters, which stands for the maximum number of types of pheromone carried by all users. We call this revised version the Improved Ant Collaborative Filtering (IACF). Experiments are conducted on larger datasets, compared with the previous work, based on three typical recommender systems: (1) movie recommendations, (2) music recommendations, and (3) book recommendations. For movie recommendation, a larger dataset, MoviesLens 10M, was used, instead of MoviesLens 1M. For book recommendation and music recommendation, we used a new dataset that has a much larger size of samples from Douban and NetEase. The results illustrate that our IACF algorithm can better deal with practical recommendation scenarios that handle sparse dataset.
Formulation of Metformin-Loaded Alginate Microspheres by Ionotropic Gelation-Aerosolization Technique

Metformin hydrochloric acid (HCl)-loaded alginate microspheres prepared using aerosolization method were subsequently evaluated for their physico-chemical characteristics in terms of particle size, morphology, drug loading, entrapment efficiency, yield and in vitro release. A two factorial Design of Experiment (DoE) was used to study the influence of polymer alginate and cross-linker calcium chloride (CaCl2) concentrations on microparticle characteristics. The results indicated that all microspheres were spherical in shape, while their particle size was less than 5 μm, although this increased with the intensification of alginate and CaCl2 concentrations. Encapsulation efficiency, loading, and yield were all enhanced by increasing alginate concentration and, conversely, decreasing CaCl2 concentration. The highest encapsulation efficiency, loading, and yield were 40, 31, and 73%, respectively, produced by a formula containing 1.75% alginate and 3% CaCl2. The drug release of Metformin-loaded microparticles in HCl pH 1.2 ranged from 22 to 28% during a two-hour period, while further drug release of PBS pH 7.4 increased from 67 to 95% over ten hours. The total amount of drug released during a 12-h period increased by reducing alginate concentration. Furthermore, a kinetic study of the dissolution data confirmed the prevalence of a diffusion-controlled mechanism or Higuchi pattern of drug release.
Large Scale Co-Regularized Ranking

As unlabeled data is usually easy to collect, semisupervised learning algorithms that can be trained on large amounts of unlabeled and labeled data are becoming increasingly popular for ranking and preference learning problems [6, 23, 8, 21]. However, the computational complexity of the vast majority of these (pairwise) ranking and preference learning methods is super-linear, as optimizing an objective function over all possible pairs of data points is computationally expensive. This paper builds upon [16] and proposes a novel large scale co-regularized algorithm that can take unlabeled data into account. This algorithm is suitable for learning to rank when large amounts of labeled and unlabeled data are available for training. Most importantly, the complexity of our algorithm does not depend on the size of the dataset. We evaluate the proposed algorithm using several publicly available datasets from the information retrieval (IR) domain, and show that it improves performance over supervised methods. Finally, we discuss possible implications of our algorithm for learning with implicit feedback in an online setting.
A spatio-temporal analysis of baboon damage using Sentinel-2 imagery and Extreme Gradient Boosting

Abstract The use of remote sensing for forest health monitoring has increased in popularity over the years, improving quality, spatial and spectral resolutions. However, revisit times of satellites is too slow for real-time detection. The need exists for high resolution monitoring, to quantify biotic damage, which is more difficult to detect due to the diversity of severity. Sentinel-2 MSI data, with 10 - 60 m spatial resolution and 443 - 2190 nm spectral range was used. Through strategical bands and derived vegetation indices, an accuracy of 89,34% with a Kappa of 0.85 using XGboost, was achieved. The study found: (1) Sentinel-2 identified baboon damage with high accuracy, with field measured data (2) different damage severities could be distinguished. SAVI and SIPI were most influential variables, due to good discrimination of structural variations in the canopy. The method provides an accurate and repeatable framework for rapid damage mapping at a sub-compartment scale.
Number 1 The West East Institute 1 OUTSOURCING FROM A SUPPLIER PERSPECTIVE

This paper investigates outsourcing from a supplier perspective. More specifically, it focuses on strategic and also operational factors that are addressed when a supplier considers taking over outsourcing that they have not handled previously. The supplier side has not been given the same attention as the customer side in the outsourcing literature to date, and this paper represents a step towards complementing this predominant customer focus. The paper applies a case study approach. Data collection is based on 23 in-depth interviews in the Scandinavian wood products industry. The paper finds that cost advantages in comparison with customers’ large-scale capacity production are difficult to achieve in the context studied. Under the circumstances, there are limited possibilities for economies of scale; in addition, new investments are needed to build manufacturing capacity. The recommendation for practitioners is to consider what new competencies are required when entering into an outsourcing agreement. In addition, it is critical that the outsourced manufacturing is profitable by itself, and that the revenues derived from the delivered components are sufficient to cover the resulting costs.
Assessing the Predictor Roles of Mindfulness and Spiritual Intelligence for Depressive and Anxiety Symptoms

©Copyright 2020 by Author(s) Abstract The goal of this study was to examine the effects of mindfulness (MF) and spiritual intelligence (SI) as predictors of depression and anxiety, the most frequent manifestations of mental disorders – among 184 Turkish participants of diverse ages, predominantly students, living in Istanbul and Sarajevo. Four instruments were administered either directly or via web-based services: Scale for Spiritual Intelligence (SSI), Hospital anxiety and depression scale (HADS), Five Facet Mindfulness Questionnaire Short Form (FFMQ-S) and Sociodemographic Information Form. Through the use of linear regression analysis, Actaware (b = -.19, p ≤ .001), Nonjudge (b = -.22, p ≤ .001), Nonreact (b = -.19, p ≤ .001) subscales of FFMQ-S were found to be negative predictors for depression and anxiety, whereas, Self-understanding subscale of SSI was not significant. Although our findings suggest that spiritual intelligence is not significant in prediction of depression and anxiety, our research provides empirical evidence for the link between MF, SI, depression and anxiety, as well as revealing MF as predictor for anxiety and depression which may be useful for further improvements in the scope of current interventions.
Risk Quantification in Deep MRI Reconstruction

Reliable medical image recovery is crucial for accurate patient diagnoses, but little prior work has centered on quantifying uncertainty when using non-transparent deep learning approaches to reconstruct high-quality images from limited measured data. In this study, we develop methods to address these concerns, utilizing a VAE as a probabilistic recovery algorithm for pediatric knee MR imaging. Through our use of SURE, which examines the end-to-end network Jacobian, we demonstrate a new and rigorous metric for assessing risk in medical image recovery that applies universally across model architectures