Miracle-dz/UniFAR-FTUs huggingface dataset:
Loss absorption capacity of central counterparties. Evidence from EU-authorised CCPs – part II

The aim of this study was to investigate loss absorption capacity of central counterparties. The qualitative and quantitative analysis was based on PQD data provided by 15 EU-authorised CCPs for Q4 2015–Q4 2017. Certain indicators were proposed in order to delineate the empirical structure of CCPs’ default waterfalls and to assess the viability and stability of CCPs. The main conclusion of the analysis is that in order to incentivise clearing participants as much as possible towards prudent risk management, the structure of default waterfall should be modified.
Evaluation of oil productivity of Chlorella minutissima cultivated in two homemade photobioreactors (bubble column and tank)

Several environmental damages caused by the use of fossil fuels, such as the green house effect, have being a motivation for researchers all around the world to develop new green techniques for power generation. Among all the possibilities of clean energy sources, there is the use of microalgae to obtain biodiesel. Many microalgae species, in certain growing conditions, accumulate considerable lipid content within their cells. Therefore, this study aimed to evaluate parameters that could influence the microalgae oil extraction and compare the productivity of the microalgae Chlorella minutissima in different photobioreactors’ designs (bubble column and tank). For each extraction, the biomass (5 or 10 mg) was mixed in Erlenmeyer flasks (125 or 500 mL) to solvents (methanol and chloroform) and kept for 40 min in ultrasound bath. For each studied condition, extractions were performed in one or two steps. After the extraction, the remaining solvent was removed using a rotaevaporator and oil yield was determined. After the improvement in the extraction process, it was evaluated the efficiency of the microalgae Chlorella minutissima cultivation in two different homemade photobiorreactors: 3 bubble column (50 L of capacity, each) and 4 tank photobioreactors (5 L of capacity, each). Regarding to extraction tests, a second extraction step is desirable to increase significantly the amount of oil extracted. The container size used in the extraction process was also a significant factor (extractions showed better results when the 125mL erlenmeyer flask was employed). The biomass amount extracted in each batch was not a contributing factor, especially because the solvents were added in proportional quantities to the biomass amount. It was also observed that cultivation of Chlorella minutissima in the bubble column photobioreactor showed lower oil productivity (7.82 mgL -1 day -1 ) compared with the tank reactor (14.6 mgL -1 day -1 ). The discrepancies of their working volume do not allow a direct comparison between those photobioreactors. However, their good oil productivities show that both can be used for Chlorella minutissima cultivation. Keywords— Chlorella minutissima, bubble column photobioreactor, tank photobioreactor,
Impact of synthetic space-borne NO2 observations from the Sentinel-4 and Sentinel-5P missions on tropospheric NO2 analyses

Abstract. We present an Observing System Simulation Experiment (OSSE) dedicated to the evaluation of the added value of the Sentinel-4 and Sentinel-5P missions for tropospheric nitrogen dioxide (NO2). Sentinel-4 is a geostationary (GEO) mission covering the European continent, providing observations with high temporal resolution (hourly). Sentinel-5P is a low Earth orbit (LEO) mission providing daily observations with a global coverage. The OSSE experiment has been carefully designed, with separate models for the simulation of observations and for the assimilation experiments and with conservative estimates of the total observation uncertainties. In the experiment we simulate Sentinel-4 and Sentinel-5P tropospheric NO2 columns and surface ozone concentrations at 7 by 7 km resolution over Europe for two 3-month summer and winter periods. The synthetic observations are based on a nature run (NR) from a chemistry transport model (MOCAGE) and error estimates using instrument characteristics. We assimilate the simulated observations into a chemistry transport model (LOTOS-EUROS) independent of the NR to evaluate their impact on modelled NO2 tropospheric columns and surface concentrations. The results are compared to an operational system where only ground-based ozone observations are ingested. Both instruments have an added value to analysed NO2 columns and surface values, reflected in decreased biases and improved correlations. The Sentinel-4 NO2 observations with hourly temporal resolution benefit modelled NO2 analyses throughout the entire day where the daily Sentinel-5P NO2 observations have a slightly lower impact that lasts up to 3–6 h after overpass. The evaluated benefits may be even higher in reality as the applied error estimates were shown to be higher than actual errors in the now operational Sentinel-5P NO2 products. We show that an accurate representation of the NO2 profile is crucial for the benefit of the column observations on surface values. The results support the need for having a combination of GEO and LEO missions for NO2 analyses in view of the complementary benefits of hourly temporal resolution (GEO, Sentinel-4) and global coverage (LEO, Sentinel-5P).
Compact Wideband Circularly Polarized Antenna with Symmetric Parasitic Rectangular Patches for Ka-Band Applications

In this paper, a novel wideband circularly polarized (CP) millimeter wave (mmWave) microstrip antenna is presented. The proposed antenna consists of a central patch and a microstrip line radiator. The CP radiation is achieved by loading a rectangular slot on the ground plane. To improve the 3-dB axial ratio bandwidth (ARBW), two symmetric parasitic rectangular patches paralleled to a central patch and a slit positioned to the right of the central patch are loaded. To verify this design, the proposed antenna is fabricated with a small antenna of 2.88 × 3.32 × 0.508 mm3. The measured impedance bandwidth (IMBW) for S11<−10 dB of the proposed antenna is 35.97% (22.8 to 33.8 GHz). Meanwhile, the simulation result shows that the 3-dB ARBW is 15.19% (28.77 to 33.5 GHz) within impedance bandwidth, and the peak gain is from 5.08 to 5.22 dBic within 3-dB ARBW. The proposed antenna is suitable for CP applications in the Ka-band.
Physico-Chemical, Microbiological and Sensory Changes in Sun-dried Trichogaster fasciata During Storage

Sun dried (T. fasciata) was stored with airtight polyethylene bags at room temperature to investigate the changes in physical, chemical, microbiological and sensory characteristics for 90 days. Sensory and physical (water reconstitution, pH) characteristics of dried T. fasciata showed that the product was acceptable up to 60 days of storage. Moisture content of T. fasciata was significantly increased from 15.06% to 17.80% during the storage period. No significant difference was observed in protein, lipid and ash content on dry matter basis during storage. However, amount of lipids of the dried fish was slightly decreased with the increasing of storage time. The pH value of dried T. fasciata was decreased significantly from 6.51 to 5.94 during the storage period. The peroxide value was increased from 13.84 to 27.87 meq/Kg of lipid. Similarly, acid value and conjugated diene of the lipids were increased significantly, and this result suggested that lipid oxidation occurred over this period of time. Microbial load was also increased from 1.13 to 8.37 log CFU/g with the increasing of storage time. Results of this study showed that the product was oxidized marginally during the storage period and suitable for human consumption up to 60 days.
Prerequisite or Not Prerequisite? That's the Problem! An NLP-based Approach for Concept Prerequisite Learning

English. This paper presents a method for prerequisite learning classification between educational concepts. The proposed system was developed by adapting a classification algorithm designed for sequencing Learning Objects to the task of ordering concepts from a computer science textbook. In order to apply the system to the new task, for each concept we automatically created a learning unit from the textbook using two criteria based on concept occurrences and burst intervals. Results are promising and suggest that further improvements could highly benefit the results.1 Italiano. Il presente articolo descrive una stategia per l’identificazione di prerequisiti fra concetti didattici. Il sistema proposto è stato realizzato adattando un algoritmo per ordinamento di Learning Objects al compito di ordinamento di concetti estratti da un libro di testo di informatica. Per adeguare il sistema al nuovo scenario, per ogni concetto stata automaticamente creata una unità di apprendimento a partire dal libro di testo selezionando i contenuti sulla base di due differenti criteri: basandosi sull’occorrenza del concetto e sugli intervalli di burst. I risultati sono promettenti e lasciano intuire la possibilità di ulteriori miglioramenti.
Hyperspectral Nonlinear Unmixing: Endmember extracting Using Iterative Simplex CNN Method

— Hyperspectral remote sensing images are showing rapid improvements in many domain such as weather, land cover classification, underwater species identification, exploring the space etc. Over the past decades pixel-wise classification have been focussed by the research community by improving accuracy, but still the problems persists due to low spatial resolution and multiple scattering effects of light generates the mixed substances in a pixel. In recent decade, the sub-pixel-wise and object based methods are focussed in a hyperspectral image classification. This paper concentrates on the experimentation of hyperspectral sub-pixel wise classification. There are two different types of spectral unmixing techniques are based on linear and nonlinear unmixing approaches. In linear unmixing techniques assumes that in macroscopic pixel level, pure substances may present per pixel, but in reality the intimate mixtures present in microscopic level due to the scattering effects of light. Basically there are two step involved in the nonlinear unmixing: endmembers extraction and abundances fractions present per pixel. This paper proposed the novel iterative simplex volume analysis Convolutional Neural Network (IS_CNN) method to extract the end members. And further, this research work employed fully constrained least square (FCLS) method to extract the endmembers of the hyperspectral data. The overall performance of the proposed method is measured with Root mean squared error (RMSE), the IS_CNN RMSE Average value for all extracted end members is 0.08 which shows the significant performance when compared with the FCLS method.
A Mobile Application for motor coordination deficiency users

It is not uncommon to find people with manual difficulties due to problems of motor coordination or some physical or neurological deficiency. This can hamper, among other things, the learning of writing digits and letters of the alphabet. In this article, we present a tool, developed in Python, to be used in tablets or phones with Android system. The tool can help users with some kind of hand handicap in the learning of letters or numbers writing, through their interaction with the electronic device. This system uses a CNN for recognizing the letters or digits and to give a feedback positive or negative for the user. Further, it can help users to learn about the corresponding image and sound, for each respective letter or digit. The mobile application is easy to use and has been tested in the learning of autistic children for 4 months. During training, the children demonstrated a good familiarity with the software and improved writing performance.
An IBM-FSI solver of exible objects in uid ow for pumps clogging applications

A range of pumps have been developed to handle mixtures of liquid and suspended solids and rags. The increase in certain solid wastes found in municipal sewage water, however, can pose signi cant challenges. The rate of accumulation of rags and brous clumps is known to depend on the ow conditions and certain hydrodynamic properties of the pumps. While it is di cult to characterize and quantify experimentally the mechanism that leads to clogging, a fully coupled uid and solid computational simulation would allow a visualization of the deformation of immersed suspended material, a characterization of the ow and solid dynamic behaviors and, crucially, an assessment of correlations between uid and solid responses. Although theoretically feasible, the task is far from straightforward and no such solution has yet been published for a full pump case. This article presents initial work on a model developed speci cally to study exible cloths like structures (rags). A computational Fluid Structure Interaction (FSI) model has been developed and validated. The model includes (i) a Navier-Stokes Finite Volume solver for the ow equations, (ii) a coupling algorithm preserving the no slip boundary condition at the interface, (iii) a Finite Di erence solution of the variational derivative of the deformation energy for the solid, and (iv) a soliduid interface tracking model. The no slip boundary condition at the soliduid interface is maintained by adding a momentum source term in both the solid and the uid solvers. This solution is based on the Immersed Boundary Method (IBM) proposed in [1] which treats the rag or ber as a Lagrangian elastic body. Both structural and uid solvers are implemented in the open source platform OpenFOAM R ©. The method is mainly used in the literature to analyze the oscillational behavior of laments or rags constrained at one end. It is extended here to account for rag/ lament transport in a owing uid and interactions with xed obstacles. Results are compared to published simulations for validation and then applied to a range of test cases chosen to represent conditions found in pump applications. The code has been extended for the study of cases relevant to processes leading up to rag blockage. This includes the analysis of the lament/rag motion behind an obstacle, and the interaction of the deformed object with rigid solid surfaces. The IBM solver for rag motion in uid ow is combined with two di erent collision models for modeling the interaction of the deformable object with the side walls: (1) A method similar to the hard sphere collision model is considered to correct the velocity of the Lagrangian points during collision, and (2) a force based model where a short range repulsive force [2] is applied once the distance between the slender object and the solid wall becomes smaller than a speci c threshold. The results are assessed qualitatively and show that the ag's response does depend on the collision model, and con rm the importance of using a force based model that can be adopted to account for the solid solid friction or the lubrication e ect.
Computational Linguistics Against Hate: Hate Speech Detection and Visualization on Social Media in the "Contro L'Odio" Project

The paper describes the Web platform built within the project “Contro l’odio”, for monitoring and contrasting discrimination and hate speech against immigrants in Italy. It applies a combination of computational linguistics techniques for hate speech detection and data visualization tools on data drawn from Twitter. It allows users to access a huge amount of information through interactive maps, also tuning their view, e.g., visualizing the most viral tweets and interactively reducing the inherent complexity of data. Educational courses for high school students and citizenship has been developed which are centered on the platform and focused on the deconstruction of negative stereotypes against immigrants, Roma, and religious minorities, and on the creation of positive narratives.
Integrating risk and knowledge management in human spaceflight programs

The National Aeronautics and Space Administration (NASA) established the Exploration Systems Mission Directorate (ESMD) in the 2004 timeframe to manage a new portfolio of programs and projects aimed at lunar return. To ensure an effective transfer of knowledge from NASA legacy programs, such as Apollo, International Space Station, and Space Shuttle, ESMD took an integrated approach towards managing risk and knowledge. This case study examines the implementation of ESMD’s integrated risk and knowledge management (IRKM) framework in the 2005-2012 timeframe. An important and novel aspect of this approach was using risk records to identify knowledge gaps and support the creation and transfer of both tacit and explicit knowledge. This explanatory case study describes how the integration of knowledge management and risk management, at both the enterprise and project-level, creates value to both processes and can assist any organization in more effectively pursuing its goals. The case also investigates how coupling these two business processes can garner broader-based organizational support for knowledge management activities. This paper is about enhancing risk management but at the same time it is a front-line investigation of what it takes to successfully implement and sustain a knowledge management enabled learning organization.
A Needs Assessment, Development, and Formative Evaluation of a Health Promotion Smartphone Application for College Students

Background: Approximately half of college students who completed the National College Health Assessment 2013 indicated a greater need for health-related information. University-based smartphone applications may help students better access this information. Purpose: This study describes the needs assessment, development, and formative evaluation of a smartphone application designed to link students to health promotion information and on-campus resources at a public university. Methods: An online survey was administered to 219 students. A smartphone application was subsequently developed also considering feedback from selected campus leaders. A focus group was conducted with 9 students to assess opinions about the application prototype. Results: The 3 most common health topics participants selected as most important to them were stress management, nutrition/diet, and physical activity/fitness. Students thought the application prototype was beneficial to the campus community and the topics included were helpful. They also provided specific suggestions on how to improve the application. Translation to Health Education Practice: A smartphone application that is responsive to students’ needs and specific to their campus community may be well accepted and utilized by students. Increased utilization of such apps may translate to increased utilization of health-related services and positive health behaviors.
Synaptic Scaling Improves the Stability of Neural Mass Models Capable of Simulating Brain Plasticity

Neural mass models offer a way of studying the development and behavior of large-scale brain networks through computer simulations. Such simulations are currently mainly research tools, but as they improve, they could soon play a role in understanding, predicting, and optimizing patient treatments, particularly in relation to effects and outcomes of brain injury. To bring us closer to this goal, we took an existing state-of-the-art neural mass model capable of simulating connection growth through simulated plasticity processes. We identified and addressed some of the model's limitations by implementing biologically plausible mechanisms. The main limitation of the original model was its instability, which we addressed by incorporating a representation of the mechanism of synaptic scaling and examining the effects of optimizing parameters in the model. We show that the updated model retains all the merits of the original model, while being more stable and capable of generating networks that are in several aspects similar to those found in real brains.
Effects of Edentulism on the Structure of the Human Mandible

The bones in the human body are constantly remodeled as osteoclasts and osteoblasts remove and add bone in order to adjust to changing mechanical conditions. Much research has been done with respect to how our diet, the way in which we exercise, and our genetics influence skeletal morphology and its responsiveness to external environmental conditions. This study seeks to determine the effects of tooth loss on the shape of the mandible. Specifically, I seek to understand how the structure of the human mandible is altered as a result of the progressive loss of teeth during life in order to better understand the role of changing mechanical forces on mandibular shape. I predicted that tooth loss would be reflected in the shape of the mandible. I expected that tooth loss would explain structural variation particular to the alveolar crest and the mandibular corpus. I tested the null hypothesis that edentulation, or tooth loss, along with age and sex do not have any effect on the structure of the human mandible. A sample of 30 human mandibles were digitized and landmarked with the intent to use geometric morphometrics to identify structural variation among each mandible in the observed population. The morphometric data were used to assess shape variation in relation to the degree of edentulism, age, and sex. The data collected through this study suggest that edentulation does contribute to changes in mandibular shape. Specifically, the loss of teeth leads to a widening of the mandibular corpus to form more of a “U-shape” as opposed to a more “V-like-shape” present in individuals with teeth. Additionally, tooth loss results in considerable alveolar ridge resorption and an increase in the gonial angle. Age and sex also correlate significantly with changes in mandibular structure, as older female individuals tended to be prone to the same mandibular restructuring observed in
The effect of language on labour market success for immigrants and citizens in South Africa

A sharp increase in the number of immigrants in South Africa has raised questions about the impact of immigration on the labour market. Whether or not immigrants can speak English— the primary language of business in South Africa—may affect their labour market success. This study uses the 2011 South African Census data and finds that immigrants are more successful than locals in South Africa. Immigrants’ success is partially attributed to the advantage gained from speaking English as a second language, whereas speaking English as a second language is less valued by the labour market for locals. Individuals who speak English are more active and more likely to obtain employment and earn higher wages than non-English speakers. The study finally shows that, although female immigrants benefit more from the ability to speak English, male immigrants are more successful overall in South Africa’s labour market.
Design and Application of an Improved Least Mean Square Algorithm for Adaptive Filtering

Received: 10 April 2019 Accepted: 28 May 2019 This paper enumerates the strengths and defects of the traditional least mean square (LMS) algorithm for adaptive filtering, and then designs a novel LMS algorithm with variable step size and verifies its performance through simulation. In our algorithm, the step size is no longer adjusted by the square of the error (e2(n)), but by the correlation between the current error and the error of a previous moment e(n-D). In this way, the algorithm becomes less sensitive to the noise with weak autocorrelation, and manages to achieve fast convergence, high time-varying tracking accuracy, and small steady-state error. The simulation results show that our algorithm outperformed the traditional LMS algorithm with fixed step size in convergence speed, tracking accuracy and noise suppression. The research findings provide a new tool for many other fields of adaptive filtering, such as adaptive system identification and adaptive signal separation.