Miracle-dz/UniFAR-FTUs huggingface dataset:
UvA-DARE ( Digital Academic Repository ) Magnetoelectric resonant metamaterial scatterers

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Analyzing Network Effects on a Fanfiction Community

Since the early days of the Web 2.0, online communities have been growing quickly and have become important part of life for large number of people. In one of these communities, this http URL, users can read and write stories which are adapted, recreated and modified from original famous books, tv series, movies, among others. By following stories and their authors, the fanfiction community creates a social network. Previous research on online communities has shown how features of the social network can help explain the behavior of the community, so we are interested in studying fanfiction's social network as well as its influence in aspects of the community. In particular, in this article we describe several properties of the members of the community, and we also try to discover which factors explain the popularity of the authors. We discover that time since joining fanfiction and the size of the authors' biography, has a negative effect on the authors popularity. Moreover, we show that the users' network metrics help to explain better authors' popularity.
Nutraceuticals Impact on Probiotics Growth: A Challenge in Synbiotic-Yoghurt Production

The prebiotic effect of three concentrations of thirteen crude plant extracts: eight aqueous extracts (rosemary, dill, garlic, ginger, flaxseeds, thyme, oat, and moringa leaves); and five Dimethyl sulfoxide (DMSO) extracts (rosemary, dill, garlic, ginger and flaxseeds) on ten different probiotic LAB was studied. Some strains (Lactobacillus brevis KP653, Lactobacillus delbrueckii subsp. lactis KP645, and Lactobacillus acidophilus CHA2) were sensitive to the plant extracts, and relative decline in the growth was noticed. While, Lactobacillus delbrueckii subsp. delbrueckii KT615, Bifidobacterium longum 141B, Lactobacillus plantarum KP623, Lactobacillus delbrueckii subsp. bulgaricus YASH2, Lactobacillus johnsonii A1, Lactobacillus casei YA1, and Streptocccus thermophilus T11 were positively influenced with the presence of some extracts. Sixteen synbiotic yoghurt trials were prepared, which produced well-formed set-yoghurt style, similar or close to the control in appearance. Total acceptability scores ranged between 76 and 98%. The highest value was recorded for the control, followed by yoghurt containing rosemary, dill, flaxseeds, thyme, oat, and moringa. While the lowest overall score was recorded for yoghurt containing garlic.
Influence of Preoperative Transcatheter Arterial Chemoembolization on Gene Expression in the HIF-1 α Pathway in Patients with Hepatocellular Carcinoma

·········································································································· i TABLE OF CONTENTS ························································································ iii LIST OF FIGURES ·································································································· iv LIST OF TABLES ···································································································· v ABBREVIATION ····································································································· vi .
ICEMST 2014 : International Conference on Education in Mathematics , Science & Technology USEFULNESS OF SPSS SUPPORT FOR STUDENTS OF ECONOMICS

Faculty of Economics and Business (University of Maribor) offers complex and useful knowledge in the field of statistics, so among other things the SPSS (Statistical Package for the Social Sciences) is part of students’ courses. SPSS is the most widely used statistical package that is applied by professionals as well as by higher education institutions, and it represents the important IT support. For that reason in this paper we present conceptual model of the usability of IT SPSS support, which was tested on a sample of 300 undergraduate and postgraduate students of economics and business. The basis for conceptual model developed in this paper represents the expanded TAM model (Technology Acceptance Model). The conceptual model was verified using structural equation modeling (SEM). Based on the set of basic models, we examined connections between formed constructs of the TAM model and in this way we presented the results of the conceptual models. The study reveals that there is a positive relationship between perceived usefulness of statistics and perceived usefulness of SPSS, perceived ease of use of SPSS, and attitude towards using the SPSS. Research model was analyzed by using the SmartPLS and WarpPLS approaches. The examination of the usefulness of statistical information support for educational institutions represents a starting point for further pedagogical and software development, and it also provides an opportunity to increase the value of SPSS in planning of IT support.
The smallest , cheapest , and best : Superlatives in Opinion Mining

This paper introduces superlatives as special indicators for product features in customer reviews. The investigation shows that one type of superlative (called ‘ISA’) is of particular relevance, as instances in this class tend to contain both a feature string and its associated opinion word. An identification of the components of such superlative comparisons can therefore help to solve two Opinion Mining tasks at once: Feature and Opinion Word Identification. The study further introduces and evaluates a novel tool that can reliably identify such superlatives, and extract from them potential product feature strings and opinion words.
Bulletin of the Geological Society of Greece

In this paper, the implementation of the framework DPSIR is presented in the coastal part of the Almyros Basin, Magnesia Prefecture. The procedure included the use of previous relevant geological, hydrological, hydrogeological and management studies, regarding the study area, the results of which are classified and assigned to the driving forces, pressures, states, impacts and responses of the DPSIR method for the area under investigation. The approach concluded to an interesting visualization of the current situation of the urban and natural environment of the study area, promoting the recognition of problems arising from the intervention of the human factor and directing environmental actions towards a rational water resources management in the wider region.
Efficient Indoor Localization using Graphs Brasil 2019

The main goal of an Indoor Positioning System (IPS) is to estimate the position of mobile devices in indoor environments. For this, the primary source of information is the signal strength of packets received by a set of routers. The fingerprint technique is one of the most used techniques for IPSs. By using supervised machine learning techniques, it trains a model with the received signal intensity information so it can be used to estimate the positions of the devices later in an online phase. Although the k-Nearest Neighbors (kNN) is one of the most widely used classification methods due to its accuracy, it has no scalability since a sample we need to classify must be compared to all other samples in the training database. In this work, we use a novel hierarchical navigable small world graph technique to build a search structure so the location of a sample can be efficiently found, allowing the IPSs to be used in large scale scenarios or run on devices with limited resources. To carry out our performance evaluation, we proposed a synthetic IPS dataset generator as well as implemented a complete real-world, high scale IPS testbed. We compared the performance of our graph-based solution with other known kNN variants, such as Kd-Tree and Ball-Tree. Our results clearly show the performance gains of the proposed solution at 96% when compared to the classic kNN and at least 77% when compared to the tree-based approaches. Key-words: indoor positioning systems, nearest neighbors, small world graphs.
Numerical Simulation of a Bat Wing at a Wing Beat

The inspiration from nature, firstly used by leonardo davinci the famous artist, which later led to the foundation of the science of bionics. He inspired bat’s wing that could be seen in his drawing for design of flying machine, he had chosen the structure of a bat’s wing for his aerial vehicle structure, and he intended to simulate the movement of the flywheel with a cloth reinforced by wooden beams. After it, a lot of research has been done to understand how the animals fly to inspire the design of new aircrafts.
Robust and accurate 2 D-tracking-based 3 D positioning method : Application to head pose estimation

Head pose estimation (HPE) is currently a growing research field, mainly because of the proliferation of human– computer interfaces (HCI) in the last decade. It offers a wide variety of applications, including human behavior analysis, driver assistance systems or gaze estimation systems. This article aims to contribute to the development of robust and accurate HPE methods based on 2D tracking of the face, enhancing performance of both 2D point tracking and 3D pose estimation. We start with a baseline method for pose estimation based on POSIT algorithm. A novel weighted variant of POSIT is then proposed, together with a methodology to estimate weights for the 2D–3D point correspondences. Further, outlier detection and correction methods are also proposed in order to enhance both point tracking and pose estimation. With the aim of achieving a wider impact, the problem is addressed using a global approach: all the methods proposed are generalizable to any kind of object for which an approximate 3D model is available. These methods have been evaluated for the specific task of HPE using two different head pose video databases; a recently published one that reflects the expected performance of the system in current technological conditions, and an older one that allows an extensive comparison with stateof-the-art HPE methods. Results show that the proposed enhancements improve the accuracy of both 2D facial point tracking and 3D HPE, with respect to the implemented baseline method, by over 15% in normal tracking conditions and over 30% in noisy tracking conditions. Moreover, the proposed HPE system outperforms the state of the art on the two databases.
Chapter 0 Boundary-Value Problems for Second Order PDEs Arising in Risk Management and Cellular Neural Networks Approach

This work deals with the Dirichlet problem for some PDEs of second order with non-negative characteristic form. One main motivation is to study some boundary-value problems for PDEs of Black-Scholes type arising in the pricing problem for financial options of barrier type. Barrier options on stocks have been traded since the end of the Sixties and the market for these options has been dramatically expanding, making barrier options the most popular ones among the exotic. The class of standard barrier options includes ’in’ barriers and ’out’ barriers, which are activated (knocked in) and, respectively, extinguished (knocked out) if the underlying asset price crosses the barrier before expiration. Moreover, each class includes ’down’ or ’up’ options, depending on whether the barrier is below or above the current asset price and thus can be breached from above or below. Therefore there are eight types of standard barrier options, depending on their ’in’ or ’out’, ’down’ or ’up’, and ’call’ or ’put’ attributes. It is possible to include a cash rebate, which is paid out at option expiration if an ’in’ (’out’) option has not been knocked in (has been knocked out, respectively) during its lifetime. One can consider barrier options with rebates of several types, terminal payoffs of different forms (e.g. power options), more than one underlying assets and/or barriers, and allow for time-dependent barriers, thus enriching this class still further. On the other hand, a large variety of new exotic barriers have been designed to accommodate investors’ preferences. Another motivation for the study of such options is related to credit risk theory. Several credit-risk models build on the barrier option formalism, since the default event can be modeled throughout a signalling variable hitting a pre-specified boundary value (See [3],[8] among others). As a consequence, a substantial body of academic literature provides pricing methods for valuating barrier options, starting from the seminal work of [18], where an exact formula is offered for a down-and-out European call with zero rebate. Further extensions
Variety seeking: conceptual model in information technologies domain

Information technologies have changed social media consumption. For example, competition between online streaming companies (e.g., Netflix) and cable TV firms have risen although these two services do not offer the same content. Our research argues that in this case consumers may be motivated to alternate between services to increase utility, rather than completely replace one service by the other. Previous research has focused on technology adoption, technology usage continuity, and switching to a new technology. However, alternating between technologies remains unexplored. Grounded on motivation theory, our proposed research model synthesizes the contributions from fields like psychology and marketing to find potential antecedents to user alternating behavior of technologies: OSL, ASL, variety seeking, intrinsic and extrinsic motivations, and product characteristics. We will conduct a survey among USA users to gather data about these variables and validate their significant impact on alternating behavior of technologies. A pilot test will be conduct to refine our measurement items, whereas the full sample will be assessed in terms of reliability, validity, and explanation power. The results are expected to validate our model for explaining this relatively new behavior in the use of technologies, whereas they could suggest managers which strategies they can focus on to remain competitive in the market and co-exist with other technologies offering similar services.
CHARACTERIZING THE GROUNDWATER CONTRIBUTION TO ECOLOGICALLY VALUEBLE LOWLAND STREAMS USING TRAVEL TIME DISTRIBUTIONS

Groundwater is the main source of stream flow for many lowland streams and therefore affecting the abiotic habitat conditions of aquatic ecosystems. The groundwater contribution to streams influences (1) river discharge, (2) water quality, (3) temperature and (4) the riparian zone. The input of groundwater provides streams with a stable base flow, good quality water and a steady temperature. However, the groundwater contribution to streams is often not characterized in detail. The current research addresses the groundwater input and its importance for aquatic ecology in lowland streams and aims to characterize it in a more sophisticated way using dynamic Travel Time Distributions. A 3D groundwater flow model (MODFLOW) was used to characterize daily Travel Time Distributions in the Dinkel lowland catchment in The Netherlands. This revealed varying contributions of groundwater flow paths with different travel times. Longer and shorter flow paths differ in amount and timing of flow, hydrochemistry and temperature. Results can be used to study the effect of stresses on the groundwater component of stream flow, and the aquatic ecosystems and habitats present in the stream.
VARUS-VALGUS STIFFNESS MODEL OF THE KNEE IDENTIFIED BY A ROBOT-BASED APPROACH

In most medical programs education is very theoretical. Due to limited access to volunteer patients, training in medical education is difficult and time consuming. The use of modern simulation techniques can enhance medical education. Therefore the multi modal Munich Knee Joint Simulator (MKS) (Figure 1) with visual, acoustic and haptic feedback is being developed at the Technical University of Munich [Riener]. The visual display gives the possibility to get an insight into the knee joint and the anatomical structures. The acoustic display generates sounds uttered by the virtual patient when pain occurs and noise from inner structures of the knee joint when moving the leg. The haptic display enables the user to feel forces and torques appearing in an intact or pathological knee joint.
The meaning of caring for nursing students in a baccalaureate nursing program: An arts-based inquiry

Objective: To determine the meaning of caring for nursing students in order to inform development of a caring curriculum for a four-year Bachelor of Nursing Program.Methods: A hermeneutic phenomenological method was employed to explore the meaning students ascribed to caring in nursing. Students drew from their own experiences within the context of nursing education. Arts-based inquiry was used as the medium to elicit students’ reflections of the meaning of caring. Seven nursing students participated in the study. Each student was asked to paint a picture capturing the meaning of caring in nursing, followed by one semi-structured audio-recorded interview. Data analysis followed the seven-step method of contextual analysis described by Diekelmann, Allan and Tanner (1989), and incorportated the methods of van Manen (1990). Results: Four themes emerged from the interview data: a) caring comes from within, b) caring is being the best you can be, c) caring is providing holistic care, and d) caring cannot be taught.Conclusions: Arts-based inquiry and the phenomenological method enabled in-depth exploration of the meaning of caring in nursing for seven nursing students. Arts-based inquiry can serve as an effective educational strategy for facilitating and fostering nurse caring among nursing students. The findings from this study have important implications for designing and implementing a caring curriculum in a baccalaureate nursing program including ensuring a caring learning environment is established for nursing students. A caring curriculum will advance student caring, and, ultimately, promote higher quality nursing care delivery.
Diversely Stale Parameters for Efficient Training of CNNs

The backpropagation algorithm is the most popular algorithm training neural networks nowadays. However, it suffers from the forward locking, backward locking and update locking problems, especially when a neural network is so large that its layers are distributed across multiple devices. Existing solutions either can only handle one locking problem or lead to severe accuracy loss or memory inefficiency. Moreover, none of them consider the straggler problem among devices. In this paper, we propose Layer-wise Staleness and a novel efficient training algorithm, Diversely Stale Parameters (DSP), which can address all these challenges without loss of accuracy nor memory issue. We also analyze the convergence of DSP with two popular gradient-based methods and prove that both of them are guaranteed to converge to critical points for non-convex problems. Finally, extensive experimental results on training deep convolutional neural networks demonstrate that our proposed DSP algorithm can achieve significant training speedup with stronger robustness and better generalization than compared methods.
A Comparison of New and Previous Methods of ICI Canceller for Mobile OFDM Receivers

While OFDM achieves a high spectral efficiency by using multiple orthogonal sub-carriers, it is sensitive to frequency offset. Especially, for OFDM mobile receivers, Doppler effect causes frequency offset. Consequently, inter-carrier interference (ICI) occurs and results in a serious degradation of received signal. In this paper, we implement a combination of Linear MMSE (LMMSE) channel estimation and ICI canceller in a simple manner. By using output from ICI canceller, we implement LMMSE without knowledge of statistical characteristic of channel. This method can achieve a slightly better performance than an iterative ICI canceller that we proposed in [1]. In addition, we implement a combination of 2D channel estimation and ICI canceller to deal with serious channel conditions in which high delay and high Doppler happen simultaneously. Keywords—OFDM, ICI, LMMSE
FAST INSIGHT ABOUT THE SEVERITY OF HURRICANE IMPACT WITH SPATIAL ANALYSIS OF TWITTER POSTS

Abstract. Social media could be very useful source of data for a people interested in disasters, since it can provide them with on-site information. Posted georeferenced messages and images can help to understand the situation of the area affected by the event. Considering this type of resource as a real-time crowdsource of crisis information, the spatial distribution of geolocated posts related to an event can represent an early indicator of the severity of impact. The aim of this paper is to explore the spatial distribution of Twitter posts related to hurricane Michael, occurred in the USA in 2018 and to analyse their potential in providing a fast insight about the event impact. Kernel density estimation has been applied to explore the spatial distribution of Twitter posts, after which Hot Spot analysis has been performed in order to analyse the spatiotemporal distribution of the data. Hot Spot analysis has shown to be the most comprehensive analysis, detecting the area of high impact. The Kernel density map has shown to be useful as well.
Trans-identity in Benin: Fact or Fiction? Social Response and Consequences

Transgender individuals are recognized globally as a key population that is at heightened risk than the general population for transmitting and contracting sexually transmitted infections (STIs) and human immunodeficiency virus (HIV). One of the social outcomes of the gender transition process is the adoption of risky behaviours as coping strategies. Examining the unique health-related needs of transgender individuals in Benin, this study describes the experience of being transgender, along with the social and community ramifications associated with this identity. The research team conducted a cross-sectional study in 2017. Study participants were recruited via respondent-driven sampling among networks across Benin. Inclusion criteria included self-identifying as transgender and being over 15 years of age. Data were collected via questionnaires regarding individuals' management of the gender transition, reactions within their community and social spheres, and engagement in risky behaviours. A total of 326 transgender individuals were identified with a majority of participants being born biologically male (89.57%). The average age was 24.13±4.88, with a strong representation of students (36.50%). In 64.72% of cases, participants' families were informed of their transgender identity. The overall attitude of families was of acceptance/support in 7 cases out of 10. Stigmatization and discrimination were reported by 50% of the subjects and 59.02% were subjected to at least one assault. Among these, half were unable to pursue legal action in response, with the main reason being a lack of knowledge of their options for legal recourse. Having multiple sexual partners was the most common risky behaviour among participants, occurring in 81.54% of the cases. Transgender individuals constitute a population with specific needs in Benin. The services and interventions dedicated to this population must integrate the prevention of STIs and HIV, along with providing legal, social and psychological support.