Miracle-dz/UniFAR-FTUs huggingface dataset:
Applying Deep Reinforcement Learning in the Navigation of Mobile Robots in Static and Dynamic Environments

Nowadays mobile robots operate reliably in clean static environments like industry setups, but rather fail in complex dynamic environments, like e.g. airports or shopping centers. Those environments are more crowded and narrow than industry-like environments and contain moving objects — mainly humans. Traditional navigation approaches treat all objects as static objects, resulting in a non-reasonable behavior. Mobile robots should be able to cope with dynamic objects as well as dynamic crowds. In this thesis, local planning is realized with the state-of-the-art Deep Reinforcement Learning (DRL) approach Proximal Policy Optimization (PPO). The RL-agent is trained in a 2D-simulation environment, where it collects experiences to update the Deep Neural Network, that serves as a function approximator. First, several RL-agents are trained in a static industry-like task setup and compared to traditional navigation approaches. Second, profiting from the knowledge of the static training, agents were trained in a dynamic environment with simulated humans, behaving according to Helbing’s Social Force Model. Two different behaviors worth mentioning have been evolved. One agent learned a policy, that avoids individual humans, but stops and waits if the robot faces unsolvable situations like crowds or blocked passages. The other agent learned a more aggressive policy. It can push pedestrians by driving very slowly towards them until they give way.
P 5 B . 11 DOPPLER WIND ANALYSIS OF THE AIRFLOW IN A STRATIFORM FRONTAL RAINBAND IN THE PACIFIC NORTHWEST USING A BISTATIC RADAR NETWORK

During January and February 2001, a bistatic radar network was deployed along the coast of Washington state during the IMPROVE field project for the purpose of mapping out the three-dimensional air motions within frontally driven precipitation systems in the near-offshore waters. IMPROVE, which stands for Improvement of Microphysical Parameterization through Observational Verification Experiment (Mass 2003; Stoelinga et al. 2003), is a research effort involving field observations, analysis, and numerical modeling, and is aimed at verifying and improving bulk microphysical parameterization schemes used in mesoscale models. During the field studies, remotely sensed and in situ microphysical data were gathered from radar and research aircraft, respectively. In addition, other measurements of standard meteorological variables (wind, pressure, temperature, and humidity) were gathered from a variety of sources, to verify the kinematic and thermodynamic aspects of the model simulations, thus isolating any problems with the microphysical schemes. A key component of the observational strategy in IMPROVE-1 was the deployment of the National Center for Atmospheric Research (NCAR) Bistatic Network (BINET). The bistatic approach to Doppler velocity measurements (Wurman et al. 1993; Wurman 1994) is a practical and cost-effective alternative to the traditional approach of using multiple, monostatic radars. In the bistatic method, a single transmitting/receiving (monostatic) radar is used, but echoes from the transmitted pulse are also received by several passive receiving (bistatic) antennas at other locations. Bistatic antennas are simpler and cheaper to deploy than multiple monostatic radars. In addition, the bistatic approach offers the advantage of taking simultaneous multi-Doppler measurements of each sampled volume, since all receivers detect echoes from the same transmitted pulse. Several studies have demonstrated success in obtaining wind fields from bistatic networks (Wurman 1994; Protat and Zawadzki 1999; Friedrich et al. 2000). This paper discusses the set-up of the IMPROVE-1 bistatic network and the data obtained. N
Fabrication of nanoparticles for generation of force and torque at nanoscale

Chiral patterns are created by focused ion-beam milling nano-grooves with sub-15 nm resolution on thin metal films and arrays of nanoparticles, scattering and absorbing light selectively for left and right circularly polarized light, with high fidelity over fields up to 100 x 100 μm2 without positioning errors. This allows to carry out numerical simulations to estimate light enhancement and circular dichroism both on ideal and realistic particles taken from SEM images, showing doubling of scattering cross-section and enhancement changes up to 5 times controlled by dichroism, with localized field enhancements up to 20000. 3D plasmonic structures extending out of a gold film plane are created by dry etching of the film in the openings of a resist mask defined by electron beam lithography. Conical vertical protrusions (nano-wells) are left, and their optical properties are numerically simulated, showing easily reachable out-of-plane trapping of both dielectric and metal plasmonic nano-spheres, with trapping forces up to 20 pN/W/μm2. Wideband refractive index spectra in 3D-FDTD are correctly represented by overcoming the polynomial approximations to give accurate field and force/torque results for generalized artificial materials.
Individualization of head-related transfer functions

The simulation of HRTFs may yield good results. An accurate model of the head is required to achieve an acceptable accuracy in high frequencies. Again, special devices are necessary for creating such a model. Hearing tests for finding the best-suited HRTF are able to reduce the errors introduced by non-individualized HRTFs. Fast and effective approaches are available, but the success of these methods is always limited by the "best" available HRTF. Estimation methods can be further divided into subcategories, e.g. geometrically, structurally or empirically motivated models (see overview in [6]).
Gating Networks in Learning Machines for Multimodal Data Decision Fusion on Single Modality Classifiers

Different architectures of gating networks that aggregate information from multiple modalities and their suitability for decision fusion is investigated. The research question, how does a gating network for decision fusion in multimodal classification problem compare to other alternatives, is answered by a quantitative and inductive reasoning approach. This is done by training different machine learning methods on individual modalities and fusing their predictions for the final classification using M-MNIST, a new data set with three modalities (image, audio, and text). The gating networks achieve greater classification accuracy when fusing information from all modalities, in contrast to considering only one modality, or without fusion. The gating network potential is demonstrated by training it on modalities with different levels of classification accuracy where it achieves the highest average normalized gain when scoring the highest validation accuracy of the three fusion methods, where the results indicate that the gating network can suppress noise in the data. Moreover, by adding an additional weak modality to the gating network, the classification accuracy is improved, hinting at that there might be an incentive to use many weak modalities instead of a few strong ones.
Using more native-like language acquisition processes in the foreign language classroom

Abstract This work presents the case for using native-like language and learning networks in the classroom-based teaching of foreign languages and suggests how this might be done for EFL lessons. Networks in both syntax and syntax learning are discussed. Language and learning networks are then identified using principles from Evolutionary Linguistics and Cognitive Linguistics. The work culminates in an examination of how the identified networks in language and language learning can be better employed by teachers in the classroom to improve retention and use. Three general lesson plan types are suggested, which correspond with the three language network types that have been identified, which go further to attach meaning to the structures learnt in class.
Fail-safe encircling of multiple UAVs with bearing only measurements

This paper presents a cooperative strategy to achieve evenly spaced circular formation of a group of UAVs. The strategy is claimed to be fail-safe because the circular formation remains unaltered even if one or more UAVs fail. We can also add more UAVs without altering the formation. The control law uses only bearing angle information. We can pre-specify the centre of the circular formation of the UAVs. The UAVs will maintain the desired distance from the centre with bearing angle measurement only. We assume that the UAVs are identical and can measure the bearing angle of all the other UAVs. The strategy is analysed using unicycle kinematic and verified using 6 DOF model of the UAVs. Extensive simulations are carried out for noisy measurement, presence of wind and moving target. Index Terms Balance circular formation, encirclement, fail-safe strategy, bearing only measurement, target tracking, 6 DOF UAV model
A Hybrid WindFarm Parametrization for Mesoscale and Climate Models

To better understand the potential impact of wind farms on weather and climate at the regional to global scales, a new hybrid wind-farm parametrization is proposed for mesoscale and climate models. The proposed parametrization is a hybrid model because it is not based on physical processes or conservation laws, but on the multiple linear regression of the results of large-eddy simulations (LES) with the geometric properties of the wind-farm layout (e.g., the blockage ratio and blockage distance). The innovative aspect is that each wind turbine is treated individually based on its position in the farm and on the wind direction by predicting the velocity upstream of each turbine. The turbine-induced forces and added turbulence kinetic energy (TKE) are first derived analytically and then implemented in the Weather Research and Forecasting model. Idealized simulations of the offshore Lillgrund wind farm are conducted. The wind-speed deficit and TKE predicted with the hybrid model are in excellent agreement with those from the LES results, while the wind-power production estimated with the hybrid model is within 10% of that observed. Three additional wind farms with larger inter-turbine spacing than at Lillgrund are also considered, and a similar agreement with LES results is found, proving that the hybrid parametrization works well with any wind farm regardless of the spacing between turbines. These results indicate the wind-turbine position, wind direction, and added TKE are essential in accounting for the wind-farm effects on the surroundings, for which the hybrid wind-farm parametrization is a promising tool.
THE HELLENIC THORACIC SOCIETY ( HTS ) THE GREEK BRONCHOLOGIC SOCIETY ( GBS )

An structured abstract should be provided of not more than 250 words. It should consist of four paragraphs, labelled Background, Methods, Results, and Conclusions. They should briefly describe, respectively, the problem being addressed in the study, how the study was performed, the most important results, and what the authors conclude from the results. Up to 5 key words should be added taken, from those recommended by the US National Library of Medicine’s Medical Subject Headings (MeSH) browser list at http://www.nlm. nih.gov/mesh/ meshhome.html. Text. The paper should nclude the following sections:
Remote service of system calls in microkernel hypervisor

This paper presents further development of Sevigator hypervisor-based security system. Original design of Sevigator confines users’ applications in a separate virtual machine that has no network interfaces. For trusted applications Sevigator intercepts networkrelated system calls and routes them to the dedicated virtual machine that services those calls. This design allows Sevigator protect networking from malicious applications including highlevel intruders residing in the kernel. Modern microkernel-based hypervisors opened the door to redesign of Sevigator. Those hypervisors are small operating systems by nature, where management of virtual machines as well as most of hardware operations are isolated in processes with low priority level. Compromising such a process does not result in compromising the whole hypervisor. In this paper we present an experimental design of Sevigator based on NOVA hypervisor where system calls of trusted applications are serviced by a dedicated process in the hypervisor rather than a separate VM. The experiment shows about 25% performance gain due to reduced number of context switches.
Visual classification of feral cat $ \ textit { Felis silvestris catus } $ vocalizations

Cat vocal behavior, in particular, the vocal and social behavior of feral cats, is poorly understood, as are the differences between feral and fully domestic cats. The relationship between feral cat social and vocal behavior is important because of the markedly different ecology of feral and domestic cats, and enhanced comprehension of the repertoire and potential information content of feral cat calls can provide both better understanding of the domestication and socialization process, and improved welfare for feral cats undergoing adoption. Previous studies have used conflicting classification schemes for cat vocalizations, often relying on onomatopoeic or popular descriptions of call types (e.g., “miow”). We studied the vocalizations of 13 unaltered domestic cats that complied with our behavioral definition used to distinguish feral cats from domestic. A total of 71 acoustic units were extracted and visually analyzed for the construction of a hierarchical classification of vocal sounds, based on acoustic properties. We identified 3 major categories (tonal, pulse, and broadband) that further breakdown into 8 subcategories, and show a high degree of reliability when sounds are classified blindly by independent observers (Fleiss’ Kappa K1⁄4 0.863). Due to the limited behavioral contexts in this study, additional subcategories of cat vocalizations may be identified in the future, but our hierarchical classification system allows for the addition of new categories and new subcategories as they are described. This study shows that cat vocalizations are diverse and complex, and provides an objective and reliable classification system that can be used in future studies.
Orchestration of software packages in data science workflows

Nowadays, Data Science applications are complex workflows composed of binary executions, MPI simulations, multithreaded applications, and user-defined analysis (possibly written in Java, Python, C/C++, or R). Our proposal integrates this heterogeneity into a single task-based programming model capable of orchestrating the execution of the different frameworks in a transparent way and without modifying nor its behaviour, nor its syntax. Thus, our prototype is designed for non-expert users that want to build complex workflows where some steps require a highly optimised state of the art software packages.
How uncertain is the market about managers' reporting objectives? Evidence from structural estimation

Theory suggests that the market’s uncertainty about managers’ reporting objectives is an important source for reporting biases (Fischer and Verrecchia 2000), yet little empirical work exists on gauging such uncertainty. We derive a simple structural estimator of this uncertainty, incorporating cross-sectional properties of prices, earnings and restatements. This approach enables us to assess an average level of uncertainty. We show that investors’ uncertainty about reporting incentives, albeit non-zero, are generally small. Given the link between uncertainty and reporting biases, our large sample evidence also supports the conjecture that earnings management is not as rife as what prior accounting academic publications would make one believe (Ball 2013). We also characterize the variation in the magnitude of uncertainty across industries and subsamples of firm size and growth.
GSM Sensor

In the recent years a wide range of sensors has been developed in the field of human presence detection for user-centered applications. Some of them are not focused on detecting people themselves but the electronic gadgets that they use to carry, which are basically mobile phones. On this basis, and taking into account that almost everyone owns a cellular phone nowadays, the overall goal of this thesis is to explore a new way to passively detect persons by means of their mobile phone emissions. Modern phones make use of several technologies, most of them valid for the realization of sensors. However, this thesis will be exclusively focused on the Global System for Mobile Communications (GSM) that has been used for cellular telephony from the early nineties to the present day. The work relies on the literature as a starting point for a complete understanding of the intricacies of the second-generation digital cellular networks. A method for detecting nearby mobile phones that are not currently being used is proposed. The method is implemented as a proof of concept using a Software Defined Radio (SDR) peripheral together with the proper open-source software to test the feasibility of the whole idea. While the detection of inactive mobile phones could not be shown using the proposed method, the reliable detection of actively used phones has proven to be possible. As the initial approach could not be implemented successfully, the aforementioned sensor will be limited to the detection of active mobile phone users.
SUSTAINABLE IMPACT OF Zn 2 + INDUCED MILD STRESS ON EDIBLE SPIRULINA SPECIES : RESPONSES OF PHOTOSYNTHESIS , OXIDATIVE BIOMARKER AND ANTIOXIDANT DEFENSE SYSTEM

Since Zinc (Zn 2+ ) is an important microelement due to its ability to defend organisms against free radicals, we investigated the effects of Zn 2+ (as ZnCl2) on growth, photosynthetic and oxidative response of exponential phase cultures of two cyanobacterial species, Spirulina maxima (S. maxima) and Spirulina platensis (S. platensis) as a method of producing Zn 2+ enriched medium for their cultivation. The cyanobacterial strains were cultured in Zarrouk’s medium containing 46 μg Zn 2+ L -1 as control, and further treated with additional Zn 2+ , considered as low, middle and high doses which correspond to 2.5, 3.5 and 4.5 mg L -1 respectively. Measurement was based on differential response of organism with and without Zn 2+ treatment after 72 and 144 h of incubation. Results showed that Zn 2+ at low dose stimulated the growth and other physiological parameters, and such stress adapted biomass of Spirulina may be used as a matrix for functional food containing zinc for human wellbeing. Keywords— Spirulina maxima, Spirulina platensis, mild oxidative stress; Zinc (Zn 2+ ); photosynthetic and antioxidant activity.
GUIANENSIS AUBL : EVALUATION OF ITS ANTIDEPRESSANT ACTIVITY IN MICE

Couroupita guianensis Aubl. (Family: Lecythidaceae) popularly known as “cannon ball tree” contains triterpenoids which have been implicated in antidepressant activity. Therefore the present research was aimed to evaluate the potential antidepressant activity of methanolic extract of Couroupita guianensis (CGM) root in mice. This extracts was administered orally in a dose range of 125, 250 and 500 mg/kg of the body weight. The antidepressant activity was evaluated using tail suspension test (TST), forced swim test (FST) and reserpine antagonism in mice. Results of the activity showed significantly decrease in the immobility time in TST and FST, similar to that of the imipramine (10 mg/kg) which served as a positive control. In reserpine antagonism showed significantly decrease in duration of catalepsy & degree of ptosis in tested mice. The significance of difference among the various treated groups and control group were analyzed by means of one-way ANNOVA followed by Dunnett’s tests. In conclusion, methanolic extract of Couroupita guianensis root possesses potential antidepressant activity (through noradrenergic mechanisms) and has therapeutic potential in the treatment of CNS disorders and provides evidence at least at a preclinical level.
The Huntsman Approach to Flotation Frothers

Mineral separation efficiency in flotation depends, to an extent, on the type of frother used. Huntsman develops and manufactures unique frothers which are suited for mineral processing applications. This paper discusses the Huntsman approach to understanding the industry’s flotation frother requirements to optimise frother selection and introduce the Huntsman’s POLYFROTH® frother range. Specific case studies where the frothers are used are discussed.
T-CELL EPITOPE PREDICTION BY SEQUENCE-BASED METHODS AND MOLECULAR DOCKING OF PROTEINS FROM BOOPHILUS MICROPLUS

The tick Rhipicephalus (Boophilus) microplus is an obligate haematophagousectoparasite that feeds on variety of domestic animals and mainly on cattle. B. microplus is distributed worldwide principally in tropical and subtropical regions. This parasite causes blood loss and bodyweight reduction. It transmits numerous pathogen-causing diseases and death [1,2]. The protozoan parasitesBabesiabovis, Babesiabigemina and the obligate intracellular bacteria Anaplasmamarginale, responsible for the infectious diseases babesiosis and anaplasmosis, respectively, are some of most prevalent worldwide disease-causing agents [1]. This impacts significantly the economy in cattle breeding worldwide [2-4]. Tick control is strongly desired in terms of adverse animal health effects and economic losses to cattle producers. One of the most common approaches for treatment ticks is to apply chemical acaricides in infected regions. Recently, it has been reported an increase in tick resistance against all classes acaricides [5-7]. Additionally, the intensive use of acaricides raises concerns of potential presence of chemical residues in food and environment [8,9]. Moreover, the toxic effect of organophosphorous class of acaricides in human is proven [10-12]. An alternative approach for tick control is vaccination. The first anti-tick vaccine was developed and commercialized by Willadsen et al. [13, 14]. It is based on a glycoprotein Bm86, which has been isolated from the gut epithelium of an Australian tick strain Abstract. Ticks are blood-sucking parasites that feed on variety of domestic animals. Rhipicephalus (Boophilus) microplus is a hard tick found in tropical and subtropical regions and feeds on cattle. The development of vaccine is very important in order to save the livestock. Threeglycosylphosphatidylinisotol(GPI)-anchored proteins (Contig2828, Contig7420, and CK181624) from the gut of B. microplus were selected by VaxiJen server as highly immunogenic. As the proteins will be tested further on BalbC mice (haplotype d), the T-cell epitope predictions were performed on mouse major histocompatibility complex (MHC) class II proteins IAd and IEd. The predictions were made by three sequence-based methods implemented in the servers MHCPred, NetMHCII and RANKPEP and by one structure-based method – molecular docking. Based on the consensus prediction by the sequenceand structure-based methods, the peptides 1-14, 31-47 and 49-67 from Contig2828, peptides 6-32 and 75-101 for Contig7420, peptides 1-26 and 45-67 for CK181624 were selected for further experimental studies.