Miracle-dz/UniFAR-FTUs huggingface dataset:
Vacancy Ordering in Vanadium Carbides Based on V_6C_5

Abstract The ordered arrangement of carbon vacancies in vanadium carbides near V6C5 has been analysed by means of selected-area electron diffraction and high-voltage electron microscopy. A new type of ordered distribution of carbon vacancies is found at non-stoichiometric compositions between V6C5 and V8C7. This structure can be expressed as a longperiod structure consisting of the enantiomorphic domains based on the structure V6C5 which was determined by Billingham. Bell and Lewis (1972). The periodic domain boundaries with spacing eleven times the nearest-neighbour interatomic distance are directly observed by electron microscopy.
A Preliminary Contextual Analysis of the Web Query Process

In contrast with the significant quantitative analyses of large Web search transaction logs, in this paper, we use a contextual interview approach to understand when queries are used, and how they are formulated and reformulated in Web searching. This work is part of a larger study that aims to identify ways to build more supportive Web search interfaces. Analysis is based on the coding.
Understanding heritage languages

With a growing interest in heritage languages from researchers of bilingualism and linguistic theory, the field of heritage-language studies has begun to build on its empirical foundations, moving toward a deeper understanding of the nature of language competence under unbalanced bilingualism. In furtherance of this trend, the current work synthesizes pertinent empirical observations and theoretical claims about vulnerable and robust areas of heritage language competence into early steps toward a model of heritage-language grammar. We highlight two key triggers for deviation from the relevant baseline: the quantity and quality of the input from which the heritage grammar is acquired, and the economy of online resources when operating in a less dominant language. In response to these triggers, we identify three outcomes of deviation in the heritage grammar: an avoidance of ambiguity, a resistance to irregularity, and a shrinking of structure. While we are still a ways away from a level of understanding that allows us to predict those aspects of heritage grammar that will be robust and those that will deviate from the relevant baselines, our hope is that the current work will spur the continued development of a predictive model of heritage language competence.
Application of magnetic resonance spectroscopy in the preoperative grading of gliomas

This study aims to assess Proton Magnetic Resonance Spectroscopy (1H-MRS) for diagnosis and preoperative grading of cerebral gliomas. A multi point biopsy under 1H-MRS metabolism imaging guidance in 21 cerebral glioma patients was performed preoperatively to obtain the corresponding voxel tissue samples. The gliomas were graded according to MRS and results compared with routine MRI and pathology data, respectively. One hundred and sixteen tissue samples were obtained by biopsy, and the puncture target exactly matched the selected voxel. Choline/N-acetyl aspartate (Cho/NAA) ratios positively correlated with pathological grades (r=0.368, P=0.031). The Cho/NAA ratio was 2.52 with a maximum Youden index of 0.7; based on these results, MRS had 92.9% sensitivity, 71.4% specificity, and 85.7% accuracy, and was more favorable than routine plain and enhanced MRI with 64.3% sensitivity, 85.7% specificity, and 71.4% diagnosis accordance (P=0.040). MRS may contribute to accuracy improvement for grading cerebral gliomas prior to operation.
impact of perseverance and passion for long term goals ( GRIT ) n educational achievements of migrant children : Evidence rom Tatarstan , Russia dgar

This article empirically studies the impact of perseverance and passion for long term goals (GRIT) on educational achievements. Specifically, the study compares GRIT levels between migrants and native school students, and tests the role of GRIT in explaining school achievements of migrants. Based on regression analysis and using a sample of 2,003 ninth graders, including 178 migrants from the Republic of Tatarstan, Russia, the results did not suggest an educational gap between native students and first generation migrants, ethnic Tatar migrants, and those from Central Asia. In addition, GRIT has significant effects in explaining the educational achievements of these migrant groups. On the contrary, the findings suggest that native students outperform their ethnic Russian migrant peers. © 2017 Colegio Oficial de Psicólogos de Madrid. Published by Elsevier España, S.L. U. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). El impacto de la perseverancia y pasión por las metas de largo plazo (GRIT) en los éxitos educativos de niños migrantes: evidencia desde Tartaristán, Rusia
J UDI S HARE : Judicious Resource Allocation for QoS-based Services in Shared Wireless Sensor Networks

In shared wireless sensor networks (WSNs), multiple users request access to sensing resources, often with varying sampling rates and QoS requirements. To accommodate a request, appropriate sensing, computing and communication resources need to be allocated across the network. Traditionally, each request is mapped to a dedicated set of resources, even when the requests are similar. The need to reduce resource usage has led to data virtualization techniques that focus primarily on merging the requests ignoring the QoS requirements. In this paper, we present a QoS-aware resource allocation approach, JUDISHARE, that merges requests, where possible, if they are compatible in their requirements, providing judicious reuse of both sensing and communication resources through a mixture of data virtualization and Virtual Network Embedding (VNE). We show that JUDISHARE respects QoS requirements and reduces resource usage to up to 60%. This, in turn, allows up to 50% more requests to be accommodated onto the network, even when the network resources are fully utilized.
Computer Students Attitudes on the Integration of m-Learning Applications

Technology has an important role in the lives particularly in the field of education nowadays because of its accessibility and affordability. Mobile learning (m-Learning) which is form of e-learning is a novel approach in the arena of educational technology that offers personal, informal, blended learning and flexible learning opportunities to learners and instructors. The present study is an attempt to determine the computer students’ attitudes on the integration of m-Learning app (WhatsApp). A total numbers of 143 student participants participated in the experiment. The study used quasi-experimental research design. The learners were performed intact groups of a public university. They were asked to complete the assignments through WhatsApp application. Two questionnaires were used to gather the data. The data was analyzed descriptively. Findings of the data showed that learners had positive attitudes towards the integration of m-Learning apps. The study also reports the suggestions for the future research and implications for the teachers.
On investigation of rheological, mechanical and morphological characteristics of waste polymer-based feedstock filament for 3D printing applications

In this study, a novel route for the preparation of feedstock filaments for fused deposition modelling from recycled high-density polyethylene (HDPE) and low-density polyethylene (LDPE) waste polymers has been explored. For improving the properties of HDPE/LDPE-recycled polymers, Fe powder has been reinforced through single-screw extrusion. It has been observed that Fe powder (from 0 wt% to 25 wt%) in the LDPE and HDPE matrices has shown increasing trend in melt flow index. Furthermore, Fe powder reinforcement resulted in 36.66% improvement in hardness of reinforced HDPE polymer and 64% in LDPE. Mechanical properties (peak elongation, peak strength, break strength and shore D hardness (SDH)) have been improved significantly with the addition of 6 wt% and 10 wt% reinforcement of Fe powder in the matrix of LDPE and HDPE, respectively. The results of study suggest that morphological properties, such as SDH and percentage porosity, have direct relation with mechanical properties as it has been found that the sample with better mechanical properties was also having high hardness and low porosity. Scanning electron microscopy and energy-dispersive X-ray spectroscopy have been performed on 3D printed functional parts and it has been observed that highly dense texture of HDPE and low surface roughness resulted in better mechanical properties.
Potential of pulp production from whole-tree wood of Betula platyphylla Roth. based on wood characteristics

To ascertain the possibility of using branchwood, trunkwood, and rootwood of Betula platyphylla Roth. in papermaking, this study investigated tissue proportion, fiber features, and major chemical components in whole-tree wood of the tree species. Analysis of variance (ANOVA) indicated that the rootwood had a significantly lower density and vessel proportion, higher ray proportion, wider lumen, and thicker wall of fiber than the trunkwood and branchwood (p <0.05). The branchwood had a significantly shorter fiber and smaller length/width than the trunkwood and rootwood (p <0.05). The trunkwood had significantly longer and narrower fibers with thinner wall and higher cellulose, but lower hemicelluloses than the branchwood and rootwood (p <0.05). The study concluded that the trunkwood of B. platyphylla was suitable for producing good paper, while the branchwood and rootwood met the basic requirements of papermaking and could be used to produce low-grade paper.
Analysis of Reinforced Concrete Deep Beams Using Nonlinear Strain Model

A nonlinear strain compatibility model is considered to investigate the behavior of reinforced concrete deep beams. It is based on satisfying equilibrium of stresses and compatibility of strains at all layers of the beam cross-section. A VISUAL BASIC code is developed for this model. Strain distribution over the cross section depth in deep beams is different from shallow beams, and varies according to the case of loading, the span-to-depth ratio (L/h), and the structural system. The experimental values of strain over the cross-section depth for different cases for simply supported deep beams, are extracted from the available literature. Based on these values, simplified equations for strain profiles for each case is proposed to use them in the present model. A key feature of the model is the ability to illustrate the effect of shear deformation of the cross section. The model is validated by comparing predicted results with experimental ones from literature in terms of load-displacement.
Effectiveness of Common Defense Mechanisms Against Adversarial Inputs for DNN based Android Malware Detectors

Tremendous popularity of Android devices makes Android malware detection an important issue that needs to be resolved. Machine learning algorithms are often used to detect malicious applications (malwares). Many of these machine learning models have shown to be vulnerable to adversarial inputs: inputs intentionally crafted to cause a machine learning model to misclassify. This vulnerability is a general problem in various state-of-theart machine learning algorithms. This work focuses on a malware detector based on a deep neural network (DNN). We evaluate different defensive measures, including feature reduction and ensemble learning, whether they can effectively reduce the sensitivity of deep neural network based malware detectors against adversarial inputs. This study shows that especially ensemble learning is able to reduce the success of adversarial samples. An ensemble of a deep neural network and K-Nearest Neighbor (KNN) model was used to improve the detection rate of adversarial inputs from 54% to almost 90% for the studied models. However, the evaluation also shows that these methods can limit the harm only to a certain extent.
The Interplay of Information from Friends and from the Crowd to Search and to Purchase Experience Goods *

Consumers use information from both friends and the crowd to estimate the quality of products prior to search and purchase. However, these signals may carry information of different nature and value and thus consumers are likely to combine them in different ways throughout the consumption funnel. We study how they do so using an optimal stopping framework to model search behavior and a multinomial choice model to describe purchase decisions. We show results from an observational study using clickstream data from a large provider of video-on-demand and from a randomized control trial using an online video-on-demand system created and operated by us for the purpose of this study. In the latter case, we randomize the friends that buy movies, the movies’ number of likes and their prices, thus obtaining identification by design for the effects of interest. We find consistent evidence that the relative value of a like increases from search to purchase although less so for more expensive movies. In particular, for the most browsed movies, additional likes do not change the likelihood of searching for a movie but increase the likelihood of purchasing the movie whereas additional friends’ rentals increase the likelihood of searching for a movie but do not further increase the likelihood of purchasing the movie. In our setting, consumers seem to primarily start by browsing movies that their friends bought to form a consideration set and use likes for decision making purposes only when they are closer to commit. Our results show how highlighting different signals throughout the consumers’ shopping journey may help improve recommender systems.
A probabilistic real-time algorithm for detecting blinks, saccades, and fixations from EOG data

We present a computationally light real-time algorithm which automatically detects blinks, saccades, and fixations from electro-oculography (EOG) data and calculates their temporal parameters. The method is probabilistic which allows to consider the uncertainties in the detected events. The method is real-time in the sense that it processes the data sample-by-sample, without a need to process the whole data as a batch. Prior to the actual measurements, a short, unsupervised training period is required. The parameters of the Gaussian likelihoods are learnt using an expectation maximization algorithm. The results show the promise of the method in detecting blinks, saccades, and fixations, with detection rates close to 100 %. The presented method is published as an open source tool.
Shrimp Assemblages in Relation to Environmental Characteristics of Four Shallow Rivers in South East Côte d’Ivoire

Shrimps are essential components of freshwater ecosystems where they contribute to detritivorous roles and can comprise the majority of macroinvertebrate biomass. However, changes in some environmental characteristics strongly influence their diversity and abundance. Patterns of their community structure in relation to environmental characteristics were investigated in four shallow rivers in South East Côte d’Ivoire. Shrimp samples were taken monthly using a longhandled net. Three species (Desmocaris trispinosa, Macrobrachium thysi and M. raridens) were caught in this study. Overall, species diversity and abundance were lower in rivers receiving palm oil mill effluents (POME) in their catchment area. Highest abundances for the latter rivers were recorded downstream, farther to POME release point. Analysis of the correlation between community structure and environmental variables showed that conductivity, water temperature, dissolved oxygen, percentage of mud, and pH were the environmental factors that strongly influenced spatial variation in shrimp abundance. D. trispinosa seemed to tolerate a wide range of environmental conditions, while M. thysi appeared more sensitive to disturbance of its environment.
Room Temperature Ferromagnetism in Fe-Doped BaSnO3.

Abstract Polycrystalline bulk samples of BaSn 1− x Fe x O 3 , with x = 0.03, 0.04 and 0.05 were prepared by solid-state reaction method. These Fe-doped BaSnO 3 systems exhibit ferromagnetism at room temperature with an average magnetic moment of 0.047, 0.038 and 0.025 μ B / F e and Curie temperature of 510, 462 and 446 K, respectively. The observed magnetic properties are not attributed to any of the known impurity phases or clusters. The presence of ferromagnetic interaction at room temperature is supported by the ferromagnetic resonance (FMR) signals observed in the electron spin resonance spectra. The ferromagnetic order between Fe-ions is expected to be mediated by an electron trapped at the oxygen anion vacancy, called the F -centre exchange (FCE) interaction.
Understanding Attitudes Towards Mathematics ( ATM ) using a Multi-modal Model : An Exploratory Case Study with Secondary School Children in England

This paper reports on a multi-modal exploratory case study within the realm of pragmatism to study the attitudes of 11 and 15-year-old students towards Mathematics (ATM). More than 200 secondary school children from the East Midlands, England, participated in this research. The aim of this research was to understand students’ emotions, perceptions, beliefs and vision about Mathematics and to investigate the factors which influence their attitudes. This study employed a multi-modal research design to elicit data from the young learners by engaging and involving them through different media of communication. Four different kinds of data were collected namely aural or spoken data (audio recorded in focus group interviews), scale data (from Likert scale style items in the questionnaire), textual/written data (collected through open ended questions in the questionnaire), and visual data (in the form of pictures drawn by the participants). Since the favoured mode of expression varies from person to person, multiple modes of data collection can include a larger number of respondents by providing them the opportunity to orchestrate their perspective in their preferred mode of communication. This research suggests that gender and attainment level have a significant impact on attitudes towards Mathematics. Boys and high ability learners have a more positive attitude towards the subject as compared to girls and low ability students. Age, socio economic status and linguistic background also seem to influence ATM but the effect is statistically insignificant.
Base-Rate Neglect : Foundations and Implications ∗

We explore the implications of a model in which people underweight the use of their prior beliefs when updating based on new information. Our model is an extension, clarification, and “completion” of previous formalizations of base-rate neglect. Although base-rate neglect can cause beliefs to overreact to new information, beliefs are too moderate on average, and a person may even weaken her beliefs in a hypothesis following supportive evidence. Under a natural interpretation of how base-rate neglect plays out in dynamic settings, a person’s beliefs will reflect the most recent signals and not converge to certainty even given abundant information. We also demonstrate that BRN can generate effects similar to other wellknown biases such as the hot-hand fallacy, prediction momentum, and adaptive expectations. We examine implications of the model in settings of individual forecasting and information gathering, as well studying how rational firms would engage in persuasion and reputationbuilding for BRN investors and consumers. We also explore many of the features, such as intrinsic framing effects, that make BRN difficult to formulaically incorporate into economic analysis, but which also have important implications. ∗For helpful comments, we thank seminar participants at Berkeley, Harvard, LSE, Queen’s University, Stanford, and WZB Berlin, and conference participants at BEAM, SITE, and the 29th International Conference on Game Theory at Stony Brook. We are grateful to Kevin He for valuable research assistance. †Corresponding Author. E-mail: acreed@berkeley.edu WWW: http://faculty.haas. berkeley.edu/acreed
Experimental investigation of the filling process in evacuated spacecraft propulsion system feedlines

During the start-up of the propulsion system of a satellite or spacecraft, the opening of the tank isolation valve will cause the propellant to flow into an evacuated feedline and slam against a closed thruster valve. This filling process, called priming, can cause severe pressure peaks that could lead to structural failure. In the case of monopropellants such as hydrazine also the risk of adiabatic compression detonation must be taken into account in the design of the feedline subsystem. The phenomenon of priming involves complex two-phase flow aspects: the liquid entering the evacuated pipe undergoes flash evaporation creating a vapor cushion in front of the liquid that mixes with the residual inert gas in the pipeline. In addition, the desorption of the dissolved pressurizing gas strongly affects the pressure wave characteristics, such as peak, frequency and attenuation. In this research work an extensive experimental campaign is carried out in a dedicated test facility which allows to test in the same conditions as the operating space system. The influence of several parameters such as pressurizing condition, material and geometry is intensively investigated, as well as the effect of different operating conditions such as tank pressure, line pressure and test fluid (water and ethanol). The most important fluid properties are identified and their influence on the different physical processes involved in priming are evaluated. The differences in the pressure wave between water and ethanol is also analyzed with respect to their fluid properties. Among the key-parameters used to describe the flow, the speed of sound is found to play a crucial role since its value affects both the pressure peak and the wave frequency. However its assessment is not an easy task due to rapidly changing flow conditions. Phenomena such as cavitation and gas desorption create strong gradients in the fluid which make the speed of sound, as well as other quantities, both time and space dependent. Flow visualizations is a valuable support for the correct interpretation of the flow behavior. Image analysis allows to characterize the flow pattern and to examine the evolution of the two-phase/two component flow. Understanding the flow evolution in the feedline system during the start-up is important not only for a safe design of the system but also to improve the numerical modeling. The obtained experimental data are used to validate numerical simulations performed with EcosimPro/ESPSS. The validation focuses in particular on the gas desorption model and on the unsteady friction model. Including these sub-models in the equations leads to a significant improvement in the wave prediction. Further possible development of sensitive parameters is proposed and others important effects to be considered, such as the bubble dynamics, are suggested.