Miracle-dz/UniFAR-FTUs huggingface dataset:
Aggregate Fluctuations , Consumer Credit and Bankruptcy ∗ Preliminary and Incomplete

There are large countercyclical fluctuations in U.S. bankruptcy filings and real credit card interest rates, while unsecured credit is pro-cyclical. To asses whether these observations are consistent with standard theory, we introduce aggregate fluctuations into a heterogeneous agent life-cycle incomplete market model calibrated to match key features of the U.S. economy and bankruptcy system. Household borrowing is priced by competitive financial intermediaries who can observe households’ earnings, age and current asset holdings. Aggregate fluctuations change the probability of persistent shocks to household earnings, with negative shocks being more likely in recessions. This leads to asymmetric effects of credit pricing on different household types over the business cycle, since interest rates vary endogenously with borrowers’ default risk. When the only source of aggregate uncertainty is income fluctuations, the calibrated model dramatically understates the volatility of bankruptcies and borrowing interest rates, and generates countercyclical borrowing. The increase in aggregate debt during recessions is largely accounted for by the extensive margin, as more households choose to borrow as a result of negative income shocks. The introduction of intermediation shocks which increase the cost of lending rate during recessions reduces the gap between model and data, and can generate pro-cyclical borrowing and increase the volatility of both filings and interest rates. However, the benchmark model still significantly understates the volatility of bankruptcy filings.
Sensitivity Analysis of Wind Characteristics and Turbine Properties on Wind Turbine Loads

Wind turbine design relies on the ability to accurately predict turbine ultimate and fatigue loads. The loads analysis process requires precise knowledge of the expected wind-inflow conditions as well as turbine structural and aerodynamic properties. However, uncertainty in most parameters is inevitable. It is therefore important to understand the impact such uncertainties have on the resulting loads. The goal of this work is to assess which input parameters have the greatest influence on turbine power, fatigue loads, and ultimate loads during normal turbine operation. An Elementary Effects (EE) sensitivity 10 analysis is performed to identify the most sensitive parameters. Separate case studies are performed on 1) wind-inflow conditions and 2) turbine structural and aerodynamic properties, both using the National Renewable Energy Laboratory (NREL) 5-MW baseline wind turbine. The Veers model was used to generate synthetic IEC Kaimal turbulence spectrum inflow. The focus is on individual parameter sensitivity, though interactions between parameters are considered. 15 The results of this work show that for wind-inflow conditions, turbulence in the primary wind direction and shear are the most sensitivity parameters for turbine loads, which is expected. Secondary parameters of importance are identified as veer, udirection integral length, and components of the IEC coherence model, as well as the exponent. For the turbine properties, the most sensitive parameters are yaw misalignment and outboard lift coefficient distribution. This information can be used to help establish error bars around the predictions of engineering models during validation efforts, and provide insight to 20 probabilistic design methods and site-suitability analyses.
Mining : An Overview of Information Extraction Systems 1

In education, scanning through endless slides in PowerPoint presentation is highly ineffective especially for the Digital Natives due to their multi-modal learning style. In order to cater for the high volume of information emerging from printed alphabets to digital images, this study proposes a text mining approach to extract keywords from a collection of presentation slides in a similar topic. This approach is to support the existing architecture of presentation mapping, whereby the keywords extracted would then be reconstructed visually in the form of visual knowledge display. In achieving this, this study provides a general discussion of text mining technologies available and later focuses on different keyword extraction systems. Finally, this study introduces the frontier method of this field, which is presentation mining.
Enhancement Of Sugar Beet Productivity Under Saline Conditions

Increasing salinity tolerance in sugar beet would markedly increase sugar yields in many irrigated areas. The aim of this study was to determine the effect of exposing direct seed sowing (DSS) or transplanting (T) seven-week old seedlings of sugar beet plants cv. TOP to five NaCl salinity levels (control, 50, 120, 190 and 260 mM) in nutrient solutions on the physiological, vegetative and yield responses in pot experiments. Statistical analysis revealed that increasing NaCl salinity caused a significant increase in leaf chlorophyll content and leaf succulence for juvenile and adult leaves while decreasing leaf area of juvenile and adult leaves and K/Na ratio in leaf blade, petioles and roots after 12 weeks of sowing date as well as root and sugar yields at harvesting time for both method of sowing (DSS and T). Moreover, water use efficiency and water consumption were gradually decreased with increasing NaCl salinity levels. Water use efficiency was decreased more sharply for direct seed sowing than for transplanting method. Increasing salinity levels induced a marked reduction of water consumption (21%) recorded by transplanting compared with direct seed sowing under control treatment. Using NaCl salinity level of 50 mM significantly reduced root and sugar yields by 63, 58% and 13, 10% for direct seed sowing and transplanting methods, respectively, compared with the control treatment. Increasing NaCl salinity level to 120 mM sharply reduced yields for direct seed sowing around 97% and 95% for root and sugar yields, respectively, meanwhile this reduction reached around 52% and 47% for transplanting method, respectively, compared with control treatment. In addition, no further growing was detected for direct seed sowing under NaCl salinity levels of 190 and 260 mM. Meanwhile the transplanted beet plants survived and grow till the salinity level of 260 mM.
Airborne Directional Networking: Topology Control Protocol Design

This research identifies and evaluates the impact of several architectural design choices in relation to airborne networking in contested environments related to autonomous topology control. Using simulation, we evaluate topology reconfiguration effectiveness using classical performance metrics for different point-to-point communication architectures. Our attention is focused on the design choices which have the greatest impact on reliability, scalability, and performance. In this work, we discuss the impact of several practical considerations of airborne networking in contested environments related to autonomous topology control modeling. Using simulation, we derive multiple classical performance metrics to evaluate topology reconfiguration effectiveness for different point-to-point communication architecture attributes for the purpose of qualifying protocol design elements.
A CPW Fed T-shaped Frequency Reconfigurable Antenna for Multi Radio Applications

─ This paper deals with design, simulation and experimental analysis of a compact, Coplanar Waveguide (CPW) fed T-shaped reconfigurable antenna with frequency diversity. The antenna mainly comprises of four strips placed in T-shape fed by coplanar waveguide feed which operates at 5.8GHz. The reconfigurability in frequency is achieved by connecting four strips through three switches in main antenna structure by the use of Positive-Intrinsic-Negative (PIN) diodes. By operating the switches in a controlled manner, the antenna is able to operate at seven frequencies namely 5.82GHz, 5.46GHz, 5.26GHz, 5.15GHz, 4.69GHz, 3.93GHz, and 3.21GHz which are suitable for Wi-Fi, WiMAX, WLAN, other C-band, and S-band applications. The antenna aperture area is 35mm × 30mm and it is designed on a FR4 epoxy substrate whose dielectric constant εr=4.3, thickness h=0.8mm. A parametric study has been carried to analyze the characteristics of the proposed antenna. The measured results are in good agreement with simulation results and show that the antenna exhibits good radiation behavior in the specified application bands. Index Terms ─ Antenna gain, CPW feed, frequency diversity, PIN diodes, radiation pattern, reconfigurable antennas.
Partial differential equations / Game theory Mean-field games with a major player Jeux à champ moyen avec agent dominant

Article history: Received 6 June 2018 Accepted 7 June 2018 Available online 22 June 2018 Presented by Pierre-Louis Lions We introduce and study mathematically a new class of mean-field-game systems of equations. This class of equations allows us to model situations involving one major player (or agent) and a “large” group of “small” players. © 2018 Académie des sciences. Published by Elsevier Masson SAS. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
An ACT-R Model of Elliptical Endpoint Error Distributions in a Mobile Touchscreen 2-D Fitts Law Task

Given the high propensity of users' motoric errors with smaller touchscreen buttons, knowing the endpoint distributions for finger-based pointing and tapping is especially important for higher-fidelity predictive modeling of tasks on such devices. One of the most studied models of aimed human motor movement in HCI is Fitts' Law. While Fitts' Law has a long and successful history of application in predicting mouse-pointing or stylus-tapping times, its traditionally high predictive ability declines when it is applied to finger-pointing tasks involving small touchscreen targets, especially when the finger (input device) is larger than the target itself (commonly known as the " fat finger " problem). There is still some uncertainty regarding the systematic prediction of endpoint distributions for two-dimensional finger-pointing tasks. Recent work (May, 2012) found endpoint error distributions larger for on-axis than off-axis movement in a mouse-pointing task, with the shape of the error distribution along the movement axis more ovoid than circular around the target center. Since the implementation of endpoint error in ACT-R did not previously distinguish between on-axis and off-axis error, Gallagher and Byrne (2013) implemented May's 2012 work in an ACT-R model by modifying the method by which noise is added to the ending position of mouse movements. Here, we build upon such modifications by implementing them in an ACT-Touch model; ACT-Touch is an extension to the ACT-R cognitive modeling framework, useful for modeling and simulation of human interactions with mobile touchscreen devices.
Artificial Intelligence in Forensic Science

Artificial intelligence is now emerging as the most important science in all spears of life. Likewise forensic science is also getting benefitted with it, thanks to the advances in the material science. More and more people understanding the impact of AI in everybody’s life and inter-life and trying to understand through the digital science which is now in everybody’s hand at the distance of finger tips within seconds [1].
Uniform spatial subdivision to improve Boids Algorithm in a gaming environment

Video games often make use of simulation to represent part of a real-world phenomenon; be it simulating a typical crowd behavior (e.g. chaos, rioting), or particle simulation (e.g. fire, smoke) and many other uses. Games have one common characteristic, i.e. they are interactive real-time systems, meaning to say processes that run in these applications must execute within a limited time threshold for the application to be called successful. The Boids algorithm is often used in these applications for realistic simulation of flocking type of behavior of virtual crowds. However, simulation of crowds in real-time using the algorithm is computationally time-consuming, due to how the algorithm evaluates the whole crowd when searching for possible nearest neighbors for each agent in the simulation. There are several approaches to improve the performance of these flocking simulations in real-time, and in this document, we discuss some of those methods that have been applied to the Boids Algorithm. We further implement and test one of these performance optimization methods, and use benchmarking results to compare the performance of the method versus the Boids Algorithms’ brute force neighborhood gathering approach
PROGRAM RENO We recommend that the thesis prepared under our supervision by RACHEL WILLIMOTT entitled Mindfulness-Based Treatments for Trauma Survivors : Effectiveness for Posttraumatic Stress Disorder

Posttraumatic stress disorder (PTSD) affects 5% of men and 10% of women in the general population and is associated with a host of mental health problems (Rosenbaum, 2004). Mindfulness is a practice used in successful interventions that teaches nonjudgmental awareness and acceptance of the current moment. These treatments have successfully treated individuals with depression, anxiety, chronic pain, and addiction (Baer, 2003). Therefore, mindfulness can be an excellent tool for those suffering from PTSD. This paper discusses the characteristics of mindfulness, describes several mindfulness-based therapies, and evaluates the efficacy of these treatments. PTSD is addressed as well, including symptoms, available treatments, and the weaknesses of those treatments. Finally, the justification of using mindfulness-based therapies for PTSD, the current research investigating mindfulness for PTSD, and examples of mindfulness-based treatments in use for PTSD is discussed.
PR ] 9 A pr 2 01 2 Quantitative ergodicity for some switched dynamical systems

We provides quantitative bounds for the long time behavior of a class of Piecewise Deterministic Markov Processes with state space R × E where E is a finite set. The continous component evolves according to a smooth vector field that it switched at the jump times of the discrete coordinate. The jump rates may depend on the whole position of the process. Under regularity assumptions on the jump rates and stability conditions for the vector fields we provide explicit exponential upper bounds for the convergence to equilibrium in terms of Wasserstein distances.
Investigating translational motion of a dual friction-drive surface acoustic wave motor through modeling and finite element simulation

This study presents the investigation of translational motion of a surface acoustic wave (SAW) linear motor employing dual friction drive (DFD) through mathematical modeling and finite element simulation. The presented SAW linear motor consists of two identical piezoelectric stators facing each other and holding a slider tightly between them. The slider is placed in the path of SAWs generated in the two stators supplied with the preload required for the friction drive, which is capable of moving the slider in forward and reverse translational motion. Typically, the stator contains an interdigital transducer (IDT) fabricated on either side of a lithium niobate (LiNbO3) substrate so that the application of sinusoidal voltage excitation to an IDT generates a traveling Rayleigh SAW on the surface of the substrate. The SAW, in the presence of preload, interacts with the slider and the frictional force drives the slider. By simultaneously exciting two IDTs, one each from the top and bottom stators, on one side of the motor, the slider makes a translational motion toward the side of the activated IDTs. The direction of the movement of the slider can be reversed by switching excitation to the IDT pair on the particular side of the motor. Mathematical modeling and finite element simulation of the motor is carried out to study the characteristics such as step motions, displacement, and forces acting on the slider for different amplitudes of input excitation. Finally, a comparative study has been carried out to show the advantages of the proposed DFD SAW motor over the conventional SAW motor.
The international traineeships network at UPF A comparative study between local and international work placements

1. ABSTRACT: This work is a preliminary study aimed at assessing the impact of international traineeships at Universitat Pompeu Fabra (UPF) in the framework of the Erasmus+ Programme. The deployment of post-EHEA traineeships has already been studied in previous works, and a comparison is performed between local and international traineeships. The study is based on a survey among students taking part in these international traineeships, by adapting the previous questionnaire and including contextual aspects.
Analysis of Investors ’ Behavior through Non-Time Series Analysis of Stock Prices

After thewar beganwith the special demand economy in the early 1950’s, Japan was followed by a reactionary recession and repeated business cycles such as the “izanami economy” and the “Global Financial Crisis. ” In this study, we attempt to analyze the investors’ behavior behind these business cycles by analyzing TOPIX price movements from 1954 to 2016 using simple data mining methods. We use the gradient boosting decision tree (GBDT) as the data mining method to analyze TOPIX price movements; this method can analyze mixed distribution. Furthermore, as a method to detect the change in investors’ behavior, we optimize the analyzing period of the datamining process by considering only the fluctuation in the monthly TOPIX price and the standard deviation of the daily price within the month. The academic contributions of this paper are 1) showing the existence of a longterm investors’ behavior over the business cycle; 2) pointing out the existence of anomaly where stock prices can be predicted in multiple markets; and 3) pointing out the importance of the non-time-series analysis of stock prices. 1) The relationship between the identified training period and the business cycles studied by previous researches, and 2) whether the prediction ability found this time will continue, are left as future research issues. *Graduate School of Business Science, University of Tsukuba, yoshida.kenichi. ka@u.tsukuba. ac.jp
Isolation of siderophore-producing strains of Rhizobium meliloti and their biocontrol potential against Macrophomina phaseolina that causes charcoal rot of groundnut

Of the 12 isolates of root-nodulating bacterium, Rhizobium meliloti isolated from the medicinal plant, Mucuna pruriens, only two were able to produce siderophores. The two isolates (RMP3 and RMP5) were able to inhibit a widely occurring plant pathogen, Macrophomina phaseolina that causes charcoal rot in groundnut. Further, there was a marked enhancement in percentage seed germination, seedling biomass, nodule number and nodule fresh weight of M. phaseolina-infected groundnut plants inoculated with the strains RMP3 and RMP5, compared to uninoculated and uninfected controls. Thus plant growth promotory nature of both the rhizobial strains was confirmed.
Modelling and Sentiment Analysis with the Bangla Language : A Deep Learning Approach Combined with the Latent Dirichlet Allocation by Mustakim

In this thesis, the Bangla language topic modelling and sentiment analysis has been researched. It has two contributions lining up together. In this regard, we have proposed different models for both the topic modelling and the sentiment analysis task. Many research exist for both of these works but they do not address the Bangla language. Topic modelling is a powerful technique for unsupervised analysis of large document collections. There are various efficient topic modelling techniques available for the English language as it is one of the most spoken languages in the whole world, but not for the other spoken languages. Bangla being the seventh most spoken native language in the world by population, it needs automation in different aspects. This thesis deals with finding the core topics of the Bangla news corpus and classifying news with a similarity measure which is one of the contributions. This is the first ever tool for Bangla topic modelling. The document models are built using LDA (Latent Dirichlet Allocation) with Bigram. Over the recent years, people in Bangladesh are heavily getting involved in social media with Bangla texts. Among this involvement, people post their opinion about products or businesses across different social sites and Facebook is the most weighted one. We have collected data from the Facebook Bangla comments and applied a state of the art algorithm to extract the sentiments which is another contribution. Our proposed system will demonstrate an efficient sentiment analysis. We have performed a comparison analysis with the existing sentiment analysis system in Bangla. However it is not straightforward to extract sentiments from the Bengali language due to its complex grammatical structure. A deep learning based method was applied to train the model and understand the underlying sentiment. The main idea is confined to the word level and character level encoding and in order to see the differences in terms of the model performance. So, we will explore different algorithms and techniques for topic modelling and sentiment analysis for the Bangla language.
SYNTHESIS AND CHARACTERIZATION OF BIOACTIVE CERAMIC IN CaO-MgO-SiO

Na2SiO3 solution and chloride solutions of calcium and magnesium were used as raw materials. HCl was added to Na2SiO3 solution resulting in gel of silica. In order to obtain a mixture of Si gel, Ca2+ and Mg2+, calcium and magnesium solutions were blended into the gel. After adding NaOH to the mixture, Ca2+ and Mg2+ ions precipitated as hydroxides. Subsequently, it was dried to attain the ceramic precursor powder, which was calcined at 900 oC for 1h, compacted into a pellet form and sintered at 1200 oC for 2h. The ceramic body was characterized by SEM, XRD and FTIR. In vitro test for bioactivity verification was performed in SBF. A surface deposition of hydroxyapatite on the ceramic body was observed after 3 days. The cytotoxicity test revealed that the material has cell viability above 70%, meaning that it is not toxic for the cells, according to ISO 10993-5 standard.
Report of calibration of the tested technologies integrated in the DIGISOIL mapping tool

HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d’enseignement et de recherche français ou étrangers, des laboratoires publics ou privés. Report of calibration of the tested technologies integrated in the DIGISOIL mapping tool Maud Seger, Isabelle Cousin, Arlène Besson, Raluca Maftei, Frédéric Andre, Sébastien Lambot, Julien Thiesson, Francesca Garfagnoli, Sandro Moretti, Antoine Stevens, et al.
The Similarity Calculation of E-commerce User Behaviors with Petri Net

The similarity of user behaviors is conductive to classify users, cluster different groups, and generate the behavior model. It is of great significance to achieve a finegrained analysis of user behaviors. In this paper, a novel method of computing the similarity of e-commerce user behaviors is presented based on Petri nets. This method involves the following aspects. We first use Petri nets to model user behaviors. Then, we calculate the similarities of behavioral sequences and behavioral data, respectively. Finally, we get the results by comparing the similarities of users. Our experiment presents that this method can reflect data features and behavioral sequences by places and transitions of Petri nets. Above all, it shows a higher accuracy of the similarity calculation.