Miracle-dz/UniFAR-FTUs huggingface dataset:
The Impact of online word-of-mouth on Consumers' Purchase Intention in Social Commerce

Compared with traditional online shopping, consumer decision-making in social commerce is more susceptible to online word-of-mouth which can be published by people with weak relationship (stranger), moderate relationship (opinion leader), and strong relationship (friend). It's meaningful to study how word-of-mouth impacts consumer's purchase intention. In this paper, we designed an S1-S2 paradigm (reviewer review) using Event-Related Potentials(ERPs) technique to investigate this problem. On the basis of the given information (reviewer and review), participants had to decide whether to buy the product. The Late Positive Potential (LPP) component was successfully evoked and the order of LPP amplitudes from large to small was opinion leader-friendstranger. It indicates that participants consume more and more emotional processing resources in this order. The order of conformity rates from high to low was friend-opinion leaderstranger, inconsistent with the order of LPP amplitudes. It shows that emotional resources only play a part in decision-making process. The final decision made by the participants is more relevant to the degree of intimacy. Our findings suggest merchants that they can promote their products through opinion leaders to attract customers' attention and increase the proportion of friends' comments, thereby motivating consumers to make purchase decisions.
Registration of High Resolution Sar and Optical Satellite Imagery Using Fully Convolutional Networks

Multi-modal image registration is a crucial step when fusing images which show different physical/chemical properties of an object. Depending on the compared modalities and the used registration metric, this process exhibits varying reliability. We propose a deep metric based on a fully convo-lutional neural network (FCN). It is trained from scratch on SAR-optical image pairs to predict whether certain image areas are aligned or not. Tests on the affine registration of SAR and optical images showing suburban areas verify an enormous improvement of the registration accuracy in comparison to registration metrics that are based on mutual information (MI).
Magnetic Assembly of Hydrogel Fiber for Constructing Three-dimensional Hepatic Lobule-like Channel Network

This paper proposes a magnetic assembly method for constructing hepatic lobule like channel network using magnetic hydrogel fibers. For constructing hepatic lobule like vascular network in cellular structure, we consider two things. First, we should make a magnetic system that can construct hepatic lobule structure. To realize three veins in the structure, we use steel rods and magnetic fibers. For this, a magnetic tweezer with seven poles is designed based on simulation results in 3D. The tweezer magnetize the steel rods and the rods attracts the fibers with high magnetic fields. Second, biocompatible condition should be established to make a 3D tissue. For this, we culture rat liver cells in fibrin gel with channel network for seven days. Then, we perform viability test of cells inside fibrin gel. Finally, we construct multi-layered vascular network embedding rat liver cells.
Ischemia modified albumin as an early biomarker in diagnosing the late stages abortus in cows

Nowadays, Ischemia Modified Albumin (IMA) has been regarded as an indicator for various maladies and complicated pregnancy in humans. Therefore, it is hypothesized that evaluation of the maternal serum IMA degrees can serve as an early detection of abortion in dairy cows. 252 Holstein cows’ serum samples were taken both in the 2nd and 6th months of their pregnancy. Twenty-two cattle were selected as a positive control group among the non aborted ones. Furthermore, blood samples from 20 non-pregnant cows were taken to identify the effects of physiological changes of pregnancy. IMA and Ischemia Modified Albumin Rate (IMAR) were markedly higher (p<0.01); and albumin was markedly lower (p<0.01) in aborted cows and healthy-pregnant cows compared with non-pregnant cows in both months. In aborted cows, IMA, IMAR and Oxidative stress index (OSI) degrees were found to be more increased than healthy pregnancies both in 2nd and 6th months of pregnancy; however, there were statistically significant only at 6th month (p<0.01). Total Oxidative Stress (TOS) levels were higher than healthy pregnancies. So, as a result of IMA which was caused by oxidative stress rising from hypoxia/ischemia could serve as an early bioindicator for miscarriage in cattle.
Multi-Scale Hybrid Micro-Appearance Modeling and Realtime Rendering of Thin Fabrics

Micro-appearance models offer state-of-the-art quality for cloth renderings. Unfortunately, they usually rely on 3D volumes or fiber meshes that are not only data-intensive but also expensive to render. Traditional surface-based models, on the other hand, are light-weight and fast to render but normally lack the fidelity and details important for design and prototyping applications. We introduce a multi-scale, hybrid model to bridge this gap for thin fabrics. Our model enjoys both the compactness and speedy rendering offered by traditional surface-based models and the rich details provided by the micro-appearance models. Further, we propose a new algorithm to convert state-of-the-art micro-appearance models into our representation while qualitatively preserving the detailed appearance. We demonstrate the effectiveness of our technique by integrating it into a real-time rendering system.
NDT_A_201620 1413..1419

Maryam Vahdat Shariatpanahi Aynaz Velayati Seyed Ali Jamalian Mehdi Babevaynejad Zahra Vahdat Shariatpanahi 1Department of Psychiatry, Faculty of Medicine, Tehran Medical Sciences, Islamic Azad University, Tehran, Iran; 2National Nutrition and Food Technology Research Institute, Faculty of Nutrition and Food Technology, Shahid Beheshti University of Medical Sciences, Tehran, Iran; 3Department of Cardiology, Shahid Lavasani Hospital, Islamic Azad University, Tehran, Iran; 4Department of Cardiac Surgery, Shahid Lavasani Hospital, Islamic Azad University, Tehran, Iran Purpose: It has been reported that cobalamin and folate deficiency is related to delirium in persons with dementia. We evaluated the association of admission serum levels of cobalamin, folic acid, and homocysteine with the occurrence of acute delirium after coronary artery bypass surgery. Methods: In this prospective cohort study, serum levels of cobalamin, folic acid, and homocysteine were measured for 296 patients upon admission. Delirium was defined by the confusion assessment method for the intensive care unit. Results: Postoperative delirium was detected in 23% (n=68) of patients. Cobalamin deficiency, folate deficiency, and hyperhomocysteinemia were observed in 29% (n=86), 6% (n=18), and 68% (n=200) of patients, respectively. Themean ± SD serum levels of folic acidwere 10.77±5.39 ng/mL and 12.86±6.51 ng/mL in delirium and non-delirium patients, respectively (P=0.008). The median (interquartile range [IQR]) serum levels of cobalamin were 280 (216–351) and 247 (195.5–336) in delirium and non-delirium patients, respectively (P=0.09). The median (IQR) serum levels of homocysteine were 18.5 (14.5–22.1) μmol/L and 17.33 (14.2–23.2) μmol/L in delirium and nondelirium patients, respectively (P=0.94). Multivariate regression analysis adjusted by other risk factors indicated that serum homocysteine, folate, and cobalamin levels had no association with the occurrence of delirium. Conclusion: There was no relationship between the preoperative levels of cobalamin, folate, and homocysteine, and acute occurrence of delirium observed after cardiac surgery.
Review Highlights: Opinion Mining On Reviews

This paper proposes amethodology to extract key insights from user generated reviews. This work is based on Aspect Based Sentiment Analysis (ABSA) which predicts the sentiment of aspects mentioned in the text documents. The extracted aspects are fine-grained for the presentation form known as Review Highlights. The syntactic approach for extraction process suffers from the overlapping chunking rules which result in noise extraction. We introduce a hybrid technique which combines machine learning and rule based model. A multi-label classifier identifies the effective rules which efficiently parse aspects and opinions from texts. This selection of rules reduce the amount of noise in extraction tasks. This is a novel attempt to learn syntactic rule fitness from a corpus using machine learning for accurate aspect extraction. As the model learns the syntactic rule prediction from the corpus, it makes the extraction method domain independent. It also allows studying the quality of syntactic rules in a different corpus.
Modularity and Derivation at the Syntax-Phonology Interface

This chapter investigates some of the nuanced distinctions between the predictions of a cyclic, modular, Rule-Based Phonological account of the Morphosyntax-Phonology Interface, and those of a cyclic, modular, Constraint-Based account (Stratal Optimality Theory). The focus here is on the theoretical distinctions between these two proposed systems that pertain to the construction of a general theory of linguistic computation. The discussion is centred around questions of modularity and derivation/cyclicity. Specific topics include (i) investigating the necessity of postulating both derivational and representational accounts of phonological domains, (ii) detailing how the two theories differ regarding how cycles are triggered, and in which module (the syntax or the phonology) they are controlled, and (iii) questioning whether the effects of constraint re-ranking across strata can be captured by a theory of structural underspecification. Data from English, Portuguese, Malayalam, and Ojibwe are analysed, and it is argued that the patterns we see are best accounted for within a Rule-Based system.
Development of a Morphological Index of the Nutritional Status of Juvenile Largemouth Bass

Abstract We describe the morphological changes associated with starvation in larval largemouth bass Micropterus salmoides and develop bivariate and multivariate morphological indices of nutritional status. We obtained hatchery-reared largemouth bass, raised them until completion of fin development, and divided them into two randomized experimental groups of fed and unfed fishes. Fed fishes were provided with newly hatched brine shrimp twice daily. We quantified morphological changes in body shape using 23 morphometric characters. After only 3 d of food deprivation, we were able to detect statistically significant differences in morphology between the fed and unfed fish using multivariate analysis. The magnitude of the mean difference increased over time. An unexpected result suggested that a simple, bivariate ratio of standard length to body depth at the anus was almost as efficient and robust at classifying fed and unfed largemouth bass from an independent data set as a multivariate index based on all 23.
Extensible Android Malware Detection and Family Classification Using Network-Flows and API-Calls

Android OS-based mobile devices have attracted numerous end-users since they are convenient to work with and offer a variety of features. As a result, Android has become one of the most important targets for attackers to launch their malicious intentions. Every year, researchers propose a novel Android malware analyzer framework to defend against real-world Android malware Apps. The researchers require an inclusive Android dataset to assess their Android analyzers. However, generating a comprehensive Android malware dataset is a challenging concept in malware scrutiny fields. In 2018, we made the first part of our Android malware dataset, CICAndMal2017 [16], publicly available while performing dynamic analyses on real smartphones. In this paper, we provide the second part of the CICAndMal2017 dataset [16] publicly available which includes permissions and intents as static features, and API calls as dynamic features. Besides, we examine these features with our two-layer Android malware analyzer. According to our analyses, we succeeded in achieving 95.3% precision in Static-Based Malware Binary Classification at the first layer, 83.3% precision in Dynamic-Based Malware Category Classification and 59.7% precision in Dynamic-Based Malware Family Classification at the second layer.
Elevation Imaging Based on Vortex Electromagnetic Wave

A method of elevation imaging based on vortex electromagnetic wave generated by concentric uniform circular array (UCA) is proposed. The dual relationship between the elevation angle of target and the locations of the UCA elements is used. Subsequently, the compressed sensing strategy is utilized to determine the elevation angle of target. Simulation results show high accuracy of this method. The work can benefit the research on orbital angular momentum (OAM) based information-rich radar.
Black-Box vs. White-Box: Understanding Their Advantages and Weaknesses From a Practical Point of View

Nowadays, in the international scientific community of machine learning, there exists an enormous discussion about the use of black-box models or explainable models; especially in practical problems. On the one hand, a part of the community defends that black-box models are more accurate than explainable models in some contexts, like image preprocessing. On the other hand, there exist another part of the community alleging that explainable models are better than black-box models because they can obtain comparable results and also they can explain these results in a language close to a human expert by using patterns. In this paper, advantages and weaknesses for each approach are shown; taking into account a state-of-the-art review for both approaches, their practical applications, trends, and future challenges. This paper shows that both approaches are suitable for solving practical problems, but experts in machine learning need to understand the input data, the problem to solve, and the best way for showing the output data before applying a machine learning model. Also, we propose some ideas for fusing both, explainable and black-box, approaches to provide better solutions to experts in real-world domains. Additionally, we show one way to measure the effectiveness of the applied machine learning model by using expert opinions jointly with statistical methods. Throughout this paper, we show the impact of using explainable and black-box models on the security and medical applications.
Phase-Controlled Beam-Scanning of Arbitrary Antenna Arrays with Far-Field Fixed Nulls

This paper presents a synthesis algorithm for the beam-scanning of antenna arrays having fixed null directions in the far-field pattern. The proposed algorithm performs the beam-scanning by phase-only control. Hence, the amplitudes of the array elements are kept constant, while only their excitations are modified. This allows one to maintain a simpler and less expensive feeding network. The algorithm is suitable for arrays of arbitrary geometry. Numerical examples are provided to show the effectiveness of the method.
Valerie Adams, Complex words in English. Harlow: Pearson Education/Longman, 2001. Pp. vii + 173. Hardback 25, ISBN 0 582 23964 8

Apart from the textbook treatments by Adams (1973) and Bauer (1983) this is the first general descriptive overview of English word formation since Marchand’s Categories and types of present-day word-formation, whose revised second edition appeared in 1969. This fact alone makes Complex words in English a most welcome contribution to a field that has seen considerable advancement during the past decades. Contrary to what the title may suggest, this book is restricted to derivation and compounding, excluding all questions concerning inflection, unless they arise in close connection to word formation. And, contrary to what the first pages may suggest, this is not an introduction to English word formation, but primarily a reference book providing thorough and insightful descriptions of a wide range of derivational and compounding patterns. One of the major strengths of the book is that the analyses are accompanied by numerous authentic examples, taken mostly from the OED and the Guardian. The use of such electronic sources is an illustration of the important methodological developments that are characteristic of recent research in the field and that are responsible for the current popularity of word formation studies. Adams’s analyses are generally lucid and incorporate insights from the recent literature. Overall, the book is a great resource for anyone looking for up-to-date information on particular patterns in English word formation. I have, however, some reservations concerning the overall organization and a number of theoretical points. The book is divided into twelve chapters: ‘Preliminaries’, ‘Transposition’, ‘Prefixes’, ‘Suffixes’, ‘Particles’, ‘Noun compounds’, ‘Adjective compounds’, ‘Verb compounds’, ‘Stem formations’, ‘Phonaesthemes’, ‘Reanalysis’, and ‘Overview’. This overall organization appears effective, but loses much of its appeal when the individual chapters are scrutinized. Given the character of the book as a reference volume, potential users need to find the information they are looking for as efficiently as possible, which, however, is sometimes hard to achieve due to some unfortunate organizational decisions. Thus, derivation is subdivided into processes that change the syntactic category of the base word, dealt with in chapter 2 (‘Transposition’), and processes that do not change the category of the base, dealt with in chapters 3, 4, and (parts of) 5 (‘Prefixes’, ‘Suffixes’, ‘Particles’). This not only has the conceptual drawback that we have an incompatible cross-classification (one based on form, one based on function), but also has practical disadvantages for the user. While the distinction in categorychanging and category-maintaining affixes may make sense for a considerable number
Numerical solution of staggered circular tubes in two-dimensional laminar forced convection

This paper aims to demonstrate the importance of adequately estimating the discretization error intrinsic in the result of any numerical simulation. The problem under consideration is forced convection in a staggered circular tube heat exchanger. The problem is solved to analyze the effect of the distance between the tubes, aiming to optimize the heat exchangers geometrical configuration by two Reynolds numbers (50 and 100). The present work did not confirm the existence of an optimal geometrical point for the operation of staggered circular tube heat exchangers, as claimed in a numerical study published in the literature.
Quadrivalent VesiculoVax vaccine protects nonhuman primates from viral-induced hemorrhagic fever and death

Recent occurrences of filoviruses and the arenavirus Lassa virus (LASV) in overlapping endemic areas of Africa highlight the need for a prophylactic vaccine that would confer protection against all of these viruses that cause lethal hemorrhagic fever (HF). We developed a quadrivalent formulation of VesiculoVax that contains recombinant vesicular stomatitis virus (rVSV) vectors expressing filovirus glycoproteins and that also contains a rVSV vector expressing the glycoprotein of a lineage IV strain of LASV. Cynomolgus macaques were vaccinated twice with the quadrivalent formulation, followed by challenge 28 days after the boost vaccination with each of the 3 corresponding filoviruses (Ebola, Sudan, Marburg) or a heterologous contemporary lineage II strain of LASV. Serum IgG and neutralizing antibody responses specific for all 4 glycoproteins were detected in all vaccinated animals. A modest and balanced cell-mediated immune response specific for the glycoproteins was also detected in most of the vaccinated macaques. Regardless of the level of total glycoprotein-specific immune response detected after vaccination, all immunized animals were protected from disease and death following lethal challenges. These findings indicate that vaccination with attenuated rVSV vectors each expressing a single HF virus glycoprotein may provide protection against those filoviruses and LASV most commonly responsible for outbreaks of severe HF in Africa.
Unsupervised Learning by Spike-Timing-Dependent Plasticity in a Mainstream NOR Flash Memory Array—Part I: Cell Operation

This article and its part II demonstrate the possibility to operate a mainstream NOR Flash memory array as an artificial synaptic array learning without external supervision according to the spike-timing-dependent plasticity (STDP) rule. As a first mandatory step to this aim, suitable array working conditions allowing not only selective cell programming but also selective cell erase are here identified, overcoming the block erase operation typical of any Flash memory technology. The proposed array working conditions exploit channel hot-electron injection and hot-hole injection at the drain side to achieve selective, bidirectional, and virtually analog tuning of cell threshold voltage, with no need for changes in the design of a common-ground double-polysilicon NOR array. In part II, the new working scheme will be shown to allow for a straightforward implementation of STDP and unsupervised learning in the array.
Fault-detection for nonlinear time-delays networked control systems with packet dropouts and access constraints

Abstract:The problem of fault detection for the Lipschitz nonlinear time-delay networked control systems with packet dropouts and access constraints is concerned. By using the linear matrix inequality technique, a fault detection filter is designed. Then, a new threshold calculation method is proposed, so that the residual evaluation function can quickly exceed the designed threshold and the residual error can achieve minimum when actuators fault occur with disturbance. Finally, simulation results show that the proposed method can detect fault faster than some others.
Distribution and Cycling of Suspended Particles Inferred from Transmissivity in the Strait of Georgia, Haro Strait and Juan de Fuca Strait

Abstract Transmissometer profiles collected during quarterly cruises in 2000–03 indicate that most suspended particles in the Strait of Georgia and Juan de Fuca Strait are confined to the top and bottom of the water column. In Haro Strait, however, the particles are mixed throughout the water column by strong tidal currents, producing an estuarine turbidity maximum. The distribution and cycling of particles provide important aquatic controls for contaminant transport, photochemical reactions and photosynthesis. Particle‐associated contaminants that enter Haro Strait may remain in suspension and enter the food web at all water depths. In the autumn and sometimes in the summer, the rate of photochemical transformation of dissolved organic matter is probably higher in Juan de Fuca Strait than in the Strait of Georgia or Haro Strait, because the surface water in Juan de Fuca Strait is less turbid.
A Process Model of Knowledge Self-Creation in Professional Work

In the movement of microfoundations, in order to understand a performance at an organizational level, researchers must focus on individuals and think that it is necessary to understand them in terms of basic behaviors, characteristics such as interactions, etc. This paper proposes a lens to view knowledge creation processes, which are individual centric, not organization centric, and tries to provide a concept model that can explain realities that cannot be grasped directly by the conventional organizational knowledge-creation theory.