Miracle-dz/UniFAR-FTUs huggingface dataset:
D ec 2 01 9 SPARSE RANDOM TENSORS : CONCENTRATION , REGULARIZATION AND APPLICATIONS

Abstract. We prove a non-asymptotic concentration inequality of sparse inhomogeneous random tensors under the spectral norm. For an order-k inhomogeneous random tensor T with sparsity pmax ≥ c log n n , we show that ‖T − ET‖ = O(√npmax log(n)) with high probability. The optimality of this bound up to polylog factors is provided by an information theoretic lower bound. By tensor matricization, we extend the range of sparsity to pmax ≥ c log n nk−1 and obtain ‖T − ET‖ = O( √
White Matter Evaluation in Multiple Sclerosis Through Magnetic Resonance Kurtosis Imaging

Objectives: To investigate diffusional changes in multiple sclerosis (MS) plaques and non-Gaussian behavior of water diffusion by using diffusional kurtosis imaging (DKI). Methods: 31 MS patients and 21 controls underwent MRI on a 3T scanner. Mean kurtosis (MK) parametric maps were computed. Region of interest (ROI) was delineated as white matter (WM) in controls and MS plaques and WM in patients. Results: There was no significance of WM kurtosis and skewness parameters among MS group and control group patients p=0.213 and p=0.390, respectively. In MS patients, kurtosis, skewness, maximum intensity, minimum intensity, and median intensity values of WM, Plaque 1, Plaque 2, and Plague 3 were significantly higher at p<0.0001 for all. Conclusions: DKI may provide more extensive characterization of lesions and WM and may be a sensitive indicator of tissue damage and microstructural change in patients with MS in addition to conventional diffusional evaluations.
Patterns of teacher-students interaction in eighth grade of junior high school

The objectives of this research are to: (1) reveal the teacher-students’ interaction patterns applied between teacher and students during teaching and learning process in SMP Muhammadiyah Imogiri. , and (2) describe the interactional features used by the teacher related to the pedagogic goals during teaching learning process SMP Muhammadiyah Imogiri. This research belongs to discourse analysis which aims at describing conversation and interaction of teacher-students during English teaching learning process in the eighth grade of SMP Muhammadiyah Imogiri. The data were collected through observation and were analyzed using the theory of IRF exchange structure and the SETT Framework. The result showed there were 30 patterns of interaction of 30 exchange structures used in seven types of transaction. The transactions greeting session, introduction, re-checking session, explaining session, instruction session, practicing session, note taking session. There were 12 types of interactional features used by the teacher with the total number of 135. It appears the display question interactional feature plays an important role in this case. Through display question, the teacher raises up the students’ desire to learn and participate in the teaching learning process. The teacher ‘24’ form-focused on feedback interactional features backs up the students when they did a mistake. That is a good unity to build the students competencies.
The Role of In Situ Stress in Organizing Flow Pathways in Natural Fracture Networks at the Percolation Threshold

We investigated the effect of in situ stresses on fluid flow in a natural fracture network. The fracture network model is based on an actual critically connected (i.e., close to the percolation threshold) fracture pattern mapped from a field outcrop. We derive stress-dependent fracture aperture fields using a hybrid finite-discrete element method. We analyze the changes of aperture distribution and fluid flow field with variations of in situ stress orientation and magnitude. Our simulations show that an isotropic stress loading tends to reduce fracture apertures and suppress fluid flow, resulting in a decrease of equivalent permeability of the fractured rock. Anisotropic stresses may cause a significant amount of sliding of fracture walls accompanied with shear-induced dilation along some preferentially oriented fractures, resulting in enhanced flow heterogeneity and channelization. When the differential stress is further elevated, fracture propagation becomes prevailing and creates some new flow paths via linking preexisting natural fractures, which attempts to increase the bulk permeability but attenuates the flow channelization. Comparing to the shear-induced dilation effect, it appears that the propagation of new cracks leads to a more prominent permeability enhancement for the natural fracture system. The results have particularly important implications for predicting the hydraulic responses of fractured rocks to in situ stress fields and may provide useful guidance for the strategy design of geofluid production from naturally fractured reservoirs.
Agro-ecological assessment of physico-chemical properties of soils in Kulfo Watershed, South Western Ethiopia

Variation in physical landscape of the highlands gives rise to variations in agro-climatic and soil parent materials in Ethiopia. The aim of this research is to characterize the physio-chemical properties of soils in Kulfo watershed. For the study, primary data from transect walks, composite soil samples and GPS points and secondary data from satellite imaginaries, National Metrological Agency and Central Statistical Agency were used. 36 composite soil samples (0-30 cm depth) were collected from three agro-ecologies (upland, mid and lowland) and analyzed in soil laboratory. Accordingly, the watershed is characterized into four agro ecologies: Lowland (20.9%), midland (35.9%), highland (37.4%) and cold high mountain areas (5.8%). Soil analysis revealed that dominantly the watershed is characterized as textually clay loam to sandy loam and there are no significant textural differences among soils in all agro-ecologies. The soil reaction varies from moderately acidic (with pH 5.4) to neutral (pH 7.3). The watershed is dominated by medium organic matter, low total nitrogen, very low available phosphorus (3.83-6.65 ppm), high potassium and very low to low cation exchange capacity. Soil and water conservation measures in the upland and use of organic manure in the lowland areas could be the viable options for rehabilitation of soil productivity. Key words: GIS, remote sensing techniques, transect walk, composite soil sample.
The Distribution of the Sum of Log-normal Variables and Exact Pricing of the Arithmetic Asian Options: A Simple, Explicit Formula

We overcome an obstacle in statistics and finance. In doing so, we show that the distribution of the arithmetic, continuous average of lognormal variables is log-normal. Furthermore, we offer a breakthrough result in finance. In doing so, we introduce a simple, exact and explicit formula for pricing the arithmetic Asian options. The pricing formula is as simple as the classical Black-Scholes formula.
DI: deionized; GLYMO: 3-glycidoxypropyltrimethoxysilane; PFOTES: 1H, 1H, 2H, 2H– perfluorooctyltriethoxysilane; PTFE: polytetrafluoroethylene; RH: relative humidity; TEOS:

Among different types of anti-icing coatings, superhydrophobic coatings have attracted considerable attention due to their water repellency and low heat-transfer rate. However, condensation on superhydrophobic surfaces at low temperatures usually causes an increase in ice adhesion because of the induced wetting of microand nanostructures. By tuning the weight ratio of surface-modified nanoparticles to unmodified ones, five superhydrophobic coatings with different structural features at the microscale were developed. Ice-adhesion strength and icenucleation temperature were studied, together with the effect of moisture condensation on ice adhesion. It was found that the ice-adhesion strength and icing temperature of these coatings do not necessarily follow the same order among these surfaces because of different mechanisms involved. Surface roughness is inadequate to describe the necessary surface features that critically affect the anti-icing behavior of the coatings. Detailed topology / geometry has to be considered when designing icephobic coatings. Superhydrophobic coatings can be adopted for icephobic applications once the surface topology is carefully designed.
ON THE EFFECT OF USING CUBIC BOXES ON VOCABULARY ACQUISITION OF EFL YOUNG LEARNERS

Vocabulary acquisition has long been a major concern among EFL instructors teaching young learners. Among all the techniques proposed for vocabulary retention and enhancement among young learners, using cubic boxes can play a pivotal role in developing and activating young learners to acquire elementary vocabularies more effectively. It was proven in this study that cooperative vocabulary activities among those young leaners applying cubic boxes outweighs the ones who try to acquire new words via traditional pen-and-paper techniques. Thus, using cubic boxes possesses a major function in vocabulary enhancement and retention of young learners of English. Moreover, vocabulary learning based on the adaptation of the cubic boxes is highly cooperative and leads to more dynamic learning rather than individual vocabulary learning in language classrooms. Article visualizations:
Transmission of oil price shocks in the East African stock market

The main objectives of this paper were to find out if shocks from oil prices affect the East Africa's securities market and these shocks are transmitted across the three countries; Kenya, Uganda and Tanzania. Stock prices from the three countries were used in coming up with the results. Based on the empirical results, there is a negative and significant transmission of crude oil price shocks to the East African securities market. There is also some transmission of shocks across the three East African countries. The Vector Autoregressive model was used in coming up with theses empirical results. The main advantage of this model is that it is flexibility whereby it is not necessary to specify which variables are exogenous or endogenous since they are all endogenous and the "exogenous" variables are the lags. Key limitation is the detennination of the appropriate lag length since each lag can be very sensitive to the results. Further research needs to be done to ascertain whether these shocks are transmitted to other financial markets other than the stock market.
Testing Epistemic Injustice

This work builds on the trivial observation that everyone is not trusted equally. One’s gender, ethnic group, occupation etc. will affect how one’s information is believed and interpreted by others. We begin by reviewing past approaches to reliability and epistemic injustice, and the factors which affect how one’s reliability is evaluated by others in discourse. We then discuss recent experimental results which show that the linguistic manipulation of gender seems to affect the strategies with which the source’s reliability is evaluated. We argue that masculine sources benefit from more charitable assumptions than feminine ones. To support this claim, we present the results of a fine-grained categorization task. The results of this task seem to support our claim about charity, i.e. that a masculine source can more easily claim competence about a topic categorized as feminine, whereas the converse appears less true.
Cross-cultural analysis of the ecological behavior of Chilean and Spanish ecotourists: a structural model

Citizen concern for the environment in light of problems such as freshwater shortages, deforestation, and climate change has been steadily increasing in postmodern societies since the mid-20th century. Ecotourists and their proenvironmental or proecological behavior are still areas of opportunity for research in order to understand the factors, whether economic, cultural, social, demographic, or psychographic, that determine this behavior. This research uses the value-belief-norm (VBN) theory and the theory of planned behavior (TPB) to analyze the intention to practice ecotourism among ecotourists from two countries with different cultures and customs. Based on these premises, the objective of this work is to create a new model that facilitates the understanding of the intention to practice ecotourism, as well as the intention to pay more for it, by comparing ecotourists from two different cultures, Chilean and Spanish, in which the importance of ecotourism is similar. The data were obtained from a panel of 809 ecotourists (406 Chileans and 403 Spaniards) through partial least squares-structural equation modeling. The results indicate that the model is a good fit to the data; therefore, the hypotheses were confirmed. Specifically, the construct of conscience in consequences and the construct of personal norms have a strong influence on the intention to practice ecotourism. The results suggest that the proposed model is a useful framework for understanding the behavioral intention of ecotourists from different countries and their intention to pay more for ecotourism. The cultural differences between the two countries did not affect the causal relations established in the model in any way.
Interacting Surface Plasmon with Electron Beam and Acoustic Vibration

Interacting Surface Plasmon with Electron Beam and Acoustic Vibration by Yue Zhang Surface plasmon, collaborative oscillation of conduction band electrons in metal, has attracted research attention very much, due to its potential applications to many fields, such as sensing, photodetector, photocatalysis and imaging. It benefits from easily tunable resonance from ultra-violet (UV) to infrared by many factors like environment, structure size, shape, material and coupling between individual structures. This thesis will cover two parts of surface plasmon: (1) imaging surface plasmon with electron spectroscopies and (2) acoustic vibration probed by surface plasmon. Electron excited plasmon method can achieve high spatial resolution and energy resolution than optical spectroscopy. This makes it a great to image and map surface plasmon. Building corresponding simulation model help us to have deep understanding about how electrons interact with material and excite surface plasmon. Acoustic vibration probed by surface plasmon is also important. After plasmon excited by a femtosecond laser, it will generate hot electron which will further transfer energy to phonon and launch acoustic vibration. This thesis shows how to find a good excitation and probing condition to generate acoustic vibration.
1 Insights on Atmospheric Oxidation Processes by Performing Factor Analyses on 1 Subranges of Mass Spectra 2

14 With the recent developments in mass spectrometry, combined with the strengths of factor analysis 15 techniques, our understanding of atmospheric oxidation chemistry has improved significantly. The 16 typical approach for using techniques like positive matrix factorization (PMF) is to input all measured 17 data for the factorization in order to separate contributions from different sources and/or processes to 18 the total measured signal. However, while this is a valid approach for assigning the total signal to 19 factors, we have identified several cases where useful information can be lost if solely using this 20 approach. For example, gaseous molecules emitted from the same source can show different temporal 21 behaviors due differing loss terms, like condensation at different rates due to different molecular 22 masses. This conflicts with one of PMF’s basic assumptions of constant factor profiles. In addition, 23 some ranges of a mass spectrum may contain useful information, despite contributing only minimal 24 fraction to the total signal, in which case they are unlikely to have a significant impact on the 25 factorization result. Finally, certain mass ranges may contain molecules formed via pathways not 26 available to molecules in other mass ranges, e.g. dimeric species versus monomeric species. In this 27 study, we attempted to address these challenges by dividing mass spectra into sub-ranges and 28 applying the newly developed binPMF method to these ranges separately. We utilized a dataset from 29 a chemical ionization atmospheric pressure interface time-of-flight (CI-APi-TOF) mass spectrometer 30 as an example. We compare the results from these three different ranges, each corresponding to 31 molecules of different volatilities, with binPMF results from the combined range. Separate analysis 32 showed clear benefits in dividing factors for molecules of different volatilities more accurately, in 33 https://doi.org/10.5194/acp-2019-838 Preprint. Discussion started: 28 November 2019 c © Author(s) 2019. CC BY 4.0 License.
Stein-type Estimators for Mean Vector in Two-Sample Problem of Multivariate Student-t Populations with Common Covariance Matrix

The paper obtains two Stein-type estimators of the mean vector of a multivariate Student-t population with unknown shape parameter based on two random samples from populations having common but unknown covariance matrix by using the preliminary test approach to shrinkage estimation. The properties of the shrinkage and the positive rule shrinkage estimators are investigated in terms of bias and the quadratic risk criteria. The relative performances of the estimators, and dominance over the usual maximum likelihood estimator are discussed. Comparisons of the estimators for the multivariate normal model are also included under different conditions. The uniform dominance of the positive rule shrinkage estimator over the shrinkage and maximum likelihood estimator is established.
What determines Venture Capital investment decisions? Evidence from the emerging VC market in Egypt

The decision of a venture capitalist to commit capital in a new risky business is a complex decision. Investors need to consider a number of important criteria simultaneously. Based on the postulates of signaling theory and the investment criteria outlined in the extant literature, we propose a theoretical framework to describe the relationship between a new venture’s characteristics and the funding decision. The proposed framework is tested using actual data of a unique sample of 200 new Egyptian technological startups. The startups were tracked from establishment until applying to a venture capitalist and a decision was made either to accept or to reject them. Logistic regression analysis reveals that venture capitalists prefer to invest in startups with mature products and actual financial performance. The entrepreneurs’ industry experience and the size of their social networks are important factors that affect the startup’s access to finance. Using decision tree analysis to map venture capitalists’ decisions, we show that the time of applying for funds is critical and serves as a gateway for further evaluation. Startups are more likely rejected for applying later into the venture capital fund than for lack of experience or unproved products. This suggests that the development of the Egyptian tech ecosystem may be hugely constrained by the limited availability of capital as well as the high aversion to risk on behalf of venture capitalists.
A Bifurcation Deep Neural Network for Electricity Meter Error Prediction under Actual Conditions

Received: 10 May 2019 Accepted: 19 August 2019 The environmental conditions have a great impact on the measuring accuracy of electricity meters, once they are installed. This paper aims to find a way to accurately evaluate the measuring errors of electricity meters under actual conditions. Specifically, a novel bifurcation deep neural network (BDNN) model was designed and tested. The BDNN consists of a subnetwork and a fully-connected network. The subnetwork is a deep autoencoderconvolutional neural network (DAE-CNN) dedicated to processing harmonic features. The fully-connected network takes the subnetwork output and the environmental conditions as its inputs, and generates the output of the entire model by softmax. Then, the BDNN was trained on a dataset generated by real experiments with electricity meters. Three hyperparameters, namely, the activation function, the number of hidden layers and the autoencoder structure, were optimized through several experiments. Through the optimization, the rectified linear unit (ReLu) was adopted as the activation function, the number of hidden layers was set to 4, and the autoencoder structure was determined as 256-128-64-32. Each numerical figure refers to the number of nodes in the corresponding hidden layer. Finally, the BDNN was compared with the least squares support vector machine (LS-SVM), the fully-connected MLP (FCP) and the original CNN, and found to outshine the contrastive methods in prediction error and computing cost. The research results shed important new light on the field calibration and error prediction of electricity meters.
Emotion Estimation Adapted to Gender of User Based on Deep Neural Networks

In this study, we focus on Twitter as a representative SNS and target emotion estimation from tweets posted on Twitter by male and female users. Specifically, we construct gender-based emotion estimation models assuming that there are different word usage tendencies between genders. By analyzing gender-specific differences in the use of emotion-related slang and emoji, we propose a method to improve emotion estimation based on neural networks using a different distributed representation model for each gender. Our evaluation experiments show that training with Deep Convolutional Neural Networks using word's distributed representation as the feature produced higher estimation accuracy than training with Feed Forward Neural Networks.
Satellite observations of new phytoplankton blooms in the Maud Rise Polynya, Southern Ocean

Abstract. Appearance of new phytoplankton blooms with in the sea-ice cover has large importance considering the upper ocean primary production that controls the biological pump with the implications for atmospheric CO2 and global climate. Satellite derived chlorophyll-a concentration showed the unprecedented phytoplankton blooms in the Maud Rise polynya, Southern Ocean with chlorophyll-a reached up to 4.67 mg m-3. Multi-satellite data indicated that the bloom appeared for the first time in the entire mission records started since 1978. Argo float located in the polynya edge provided evidence of bloom condition in austral spring 2017 (chlorophyll-a up to 5.47 mg m-3) compared to the preceding years of prevailed low chlorophyll-a. The occurrence of bloom was associated with the supply of nutrients into the upper ocean through the Ekman upwelling (driven by wind stress curl and cyclonic ocean eddies), and improved light condition up to 61.9 Einstein m-2 day-1. The net primary production from Aqua-MODIS chlorophyll-based algorithm showed that the Maud Rise polynya was as productive as the Antarctic coastal polynyas with the carbon fixation rates reached up to 415.08 mg C m-2 day-1. The study demonstrates how the phytoplankton in the Southern Ocean (specifically over the shallow bathymetric region) would likely respond in the future under a warming climate condition and continued melting of Antarctic sea-ice since 2016.