Miracle-dz/UniFAR-FTUs huggingface dataset:
Results from the COST 239 project. Ultra-High Capacity Optical Transmission Networks

The objective of COST 239 (Ultra-High Capacity Optical Transmission Networks) is to evaluate the feasibility of an optical overlay network interconnecting major cities within Europe. This European Optical Network employs wavelength routing to provide the required interconnection between network nodes. The study has a number of key activities and achievements relating to traffic modelling, transmission, network topologies and dimensioning, and protection strategies. In this paper the emphasis is on network rather than transmission aspects.
Calculation of Wind Farm Production Losses via MERRA Data in Consequence of Bat Based Temporary Wind Turbine Shut Downs

Summary In the presented study a comparison of the difference between 10­minute wind speed data and MERRA data based on calculations of annual power losses is performed to determine if MERRA data are sufficient for that purpose and to detect the possible uncertainties of the applied procedures. Further comparisons are based on real production and wind speeds of nacelle anemometers from existing turbines. Furthermore, possible alternative calculation methods are compared in order to find a realistic procedure with reduced uncertainties and reliable data set to predict the losses of bat caused shut down scenarios. The study shows that in general the course of the wind speeds of MERRA data accompany the course of the wind speeds of 10­minute data from nacelle anemometers, but with an all in all higher level of wind speed values. With the use of scaling factors it is possible to level the bat shut down losses estimated via MERRA data with the esti­ mated losses using 10­minute wind speed values from nacelle anemometers. However the uncertainties must be esti­ mated as high because of the large amount of influencing factors. Furthermore, the difference of wind speed values of a single month can be quite high, which is mainly due to the aspect of the established high amount of peaks in the MERRA wind speed values.
Electronic toll collection technologies: A state of art review

This work covers the state of art of various existing electronic toll collection (ETC) technologies. Also, the present study covers the technical and economical aspects associated with these technologies. All technologies understudy are reviewed in context of their suitability for Indian roads. In this direction, the pros and cons are discussed and compared to determine the conflict in tradeoffs among these technologies prior to implementation in India.
Peer Support and Overdose Prevention Responses: A Systematic ‘State-of-the-Art’ Review

Overdose prevention for people who use illicit drugs is essential during the current overdose crisis. Peer support is a process whereby individuals with lived or living experience of a particular phenomenon provide support to others by explicitly drawing on these experiences. This review provides a systematic search and evidence synthesis of peer support within overdose prevention interventions for people who use illicit drugs. A systematic search of six databases (CINAHL, SocINDEX, PsycINFO, MEDLINE, Scopus, and Web of Knowledge) was conducted in November 2020 for papers published in English between 2000 and 2020. Following screening and full-text review, 46 papers met criteria and were included in this review. A thematic analysis approach was used to synthesize themes. Important findings include: the value of peers in creating trusted services; the diversity of peers’ roles; the implications of barriers on peer-involved overdose prevention interventions; and the stress and trauma experienced by peers. Peers play a pivotal role in overdose prevention interventions for people who use illicit drugs and are essential to the acceptability and feasibility of such services. However, peers face considerable challenges within their roles, including trauma and burnout. Future interventions must consider how to support and strengthen peer roles in overdose settings.
The NOTCH3 Downstream Target HEYL Is Required for Efficient Human Airway Basal Cell Differentiation

Basal cells (BCs) are stem/progenitor cells of the mucociliary airway epithelium, and their differentiation is orchestrated by the NOTCH signaling pathway. NOTCH3 receptor signaling regulates BC to club cell differentiation; however, the downstream responses that regulate this process are unknown. Overexpression of the active NOTCH3 intracellular domain (NICD3) in primary human bronchial epithelial cells (HBECs) on in vitro air–liquid interface culture promoted club cell differentiation. Bulk RNA-seq analysis identified 692 NICD3-responsive genes, including the classical NOTCH target HEYL, which increased in response to NICD3 and positively correlated with SCGB1A1 (club cell marker) expression. siRNA knockdown of HEYL decreased tight junction formation and cell proliferation. Further, HEYL knockdown reduced club, goblet and ciliated cell differentiation. In addition, we observed decreased expression of HEYL in HBECs from donors with chronic obstructive pulmonary disease (COPD) vs. normal donors which correlates with the impaired differentiation capacity of COPD cells. Finally, overexpression of HEYL in COPD HBECs promoted differentiation into club, goblet and ciliated cells, suggesting the impaired capacity of COPD cells to generate a normal airway epithelium is a reversible phenotype that can be regulated by HEYL. Overall, our data identify the NOTCH3 downstream target HEYL as a key regulator of airway epithelial differentiation.
Automated design of waveguide components using hybrid mode-matching/numerical EM building-blocks in optimization-oriented CAD frameworks-state of the art and recent advances

Fast hybrid mode-matching/boundary-contour (MM/BC) and mode-matching/finite-element (MM/FE) waveguide building blocks are described for the optimization-oriented use in powerful circuit computer-aided design (CAD) tools and the automated design of waveguide components. The efficient electromagnetic (EM) CAD technique allows the accurate design of a comprehensive class of rectangular and circular waveguide components including realistic structures of higher complexity. The efficiency and flexibility of the hybrid CAD method is demonstrated at advanced EM design examples, such as broad-band circular-to-rectangular waveguide transitions including octagonal cross sections, waveguide resonator filters with rounded corners, optimum-shaped bends, dual-mode filters with coupling sections without tuning screws, ridged waveguide filters with rounded corners, and multiplexers. The designed components are directly amenable to cost-efficient fabrication techniques like computer-controlled milling methods. The theory is verified by available measurements.
Estimating the inhibitory effect of Lactobacillus isolated from different sources on some pathogens of urogenital infections in women group

This study was aimed to identify of pathogenic organism isolated from urogintal tract and estimate the effect of Lactobacillus which isolated from different sources on the growth of these pathogens including (Candida albicans, Staphylococcus aureus, Escherichia coli, Pseudomonas aeruginosa, Gardnerella viginals, Klebsiella oxytoca ,Proteus mirabilis). The results showed that Lactobacillus which was isolated from vagina on solid medium was effective against pathogenic isolates more than the Lactobacillus species isolated from yoghurt, cow milk, human milk with inhibition zone (12-16) mm, while the highs inhibitory effect of Lactobacillus isolated from vagina in liquid media with inhibition zone reached to(18)mm. Adversely, lowest inhibitory effect was shown with supernatant of Lactobacillus spp isolated from human milk with inhibition zone reached to(11)mm comparison with Lactobacillus spp isolated from yoghurt and cow milk with inhibition zone (13-15) mm. Also the result revealed that Lactobacillus spp isolated from vagina, human milk, cow milk and yoghurt by overlay method had no effect on pathogenic bacteria but high effect was shown only with the vaginal Lactobacillus isolates on C . albicans.
Digital touchscreens as a media for creativity during adolescence

Based on embodied representation theory (Pezzulo, 2011) considering creativity process as a predictive motor control process (Dietrich & Haider, 2015), this research was aimed at evaluating whether direct finger feedbacks on tablet could promote originality in drawings. Twenty-one adolescents aged 13/14 were asked to produce the most original house as possible on tablet with finger and stylus and on paper with a pen, and an unoriginal house with a pen on paper. Originality in drawing was scored with a rating scale comparing original drawings to a prototypical house, then comparing original drawings to unoriginal ones. Results revealed that original scores are higher for drawings on tablet (without difference between finger and stylus) than on paper. These findings highlight the role played by off-line simulation of action in the creative process.
Some properties of an open‐ended circular waveguide with one‐ and two‐sided ideal hard walls

The problem of radiation from a hard open‐ended circular waveguide excited in the dominant TEM mode is solved. The cases of one‐sided and two‐sided hard‐wall surfaces are considered. The rigorous solution obtained shows that the reflected TEM mode field in the latter case, unlike that in the former case, is completely concentrated at the surface outside the waveguide. © 2004 Wiley Periodicals, Inc. Microwave Opt Technol Lett 43: 160–164, 2004; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/mop.20407
Artificial neural network optimisation methodology for the estimation of the critical flashover voltage on insulators

To describe an artificial neural network (ANN) methodology in order to estimate the critical flashover voltage on polluted insulators is the objective here. The methodology uses as input variables characteristics of the insulator such as diameter, height, creepage distance, form factor and equivalent salt deposit density, and it estimates the critical flashover voltage based on an ANN. For each ANN training algorithm, an optimisation process is conducted regarding the values of crucial parameters such as the number of neurons and so on using the training set. The success of each algorithm in estimating the critical flashover voltage is measured by the correlation index between the experimental and estimated values for the evaluation set, and finally the ANN with the correlation index closest to 1 is specified. For this ANN and the respective algorithm, the critical flashover voltage of the test set insulators is estimated and the respective confidence intervals are calculated through the re-sampling method.
Network-based approach to modelling uncertainty in a supply chain

Supply chains are interlinked networks of suppliers, manufacturers, distributors and customers that provide a product or service to customers. Typical supply chains can be characterized by their complexity and by the inherent uncertainty in their operations. Therefore, modelling such supply chains is a difficult and challenging research task, particularly given the need to model the stochastic operations of typical supply chains. What is giving added urgency to the need to address this issue are the recent developments in communications, primarily based on Internet technologies, that offer the promise of connecting suppliers, assemblers and customers in a seamless network of information. This offers the promise of substantially improved decision-making and a consequent considerable improvement in operations. However, fulfilment of this promise is dependent on the development of a suitable modelling methodology for supply chains. A network-based methodology to model and analyse supply chain systems is proposed. The methodology represents the operation of a supply chain as an abstracted network. The approach allows for the inclusion of stochastic variables so that uncertainty in the operation of a supply chain can be modelled. The use of the methodology is illustrated using a case study based on company data. The contribution of this paper is threefold. First, an approach is presented that can represent the complex operation of a supply chain as an abstracted network. Second, the use of stochastic variables in this approach is described. The stochastic variables represent the uncertainty present in typical supply chains. Third, a case study is presented that illustrates how this approach can be used to improve the operation of a supply chain.
Objective evaluation of handling quality

Abstract Vehicle dynamics quality is generally evaluated by two approaches: subjective evaluations using driver ratings and objective measurements of vehicle dynamics characteristics. In both approaches it is important to define features of vehicle dynamics in order to cover all aspects, but without redundancy. For this reason, the first part of the paper tries to summarize the principal qualities and to how they might be organized. In the second part, the paper describes those procedures that can be used to obtain objective quality indices. First of all, criteria used in subjective testing (questionnaire design, jury selection, etc.) are described. Then it is determined which manoeuvres can be performed, and which physical quantities should be considered, in order to obtain objective parameters that correlate with subjective evaluation. After this, the paper briefly describes the statistical technique used to identify which measured variables best correlate with vehicle dynamics qualities. In the third part, the paper contains a practical application of the objective index identification procedure regarding handling quality. Some examples are given about how these indices are used in different phases of a new car development, from target setting to target deployment, and in target achievement and verification during final tuning.
Multilingual natural language processing: Towards universal translation with neural approaches

Main text: The quality of machine translation is approaching human parity for several language pairs [10]. The field is progressing rapidly further with recent advances in natural language processing and highly multilingual systems can be learned with a shared system for all languages [2]. As Tang and colleagues demonstrate, we are getting close to universal translation [9]. They combine the advantages of previous research (English or non-English centric) in shared [2] and massive multilingual models [3] with unsupervised techniques [4] and show that simultaneous, multi-lingual fine tuning can improve the training of translations significantly, especially for languages that do not offer large bilingual text collections. Works such as [2,3,4] bring us closer to the goal of universal communication, which could enable world-wide conversations. Even though it might be difficult to agree on what this generic and ambitious goal entails. We may agree that it involves the capability of transparently communicating in all (or a great proportion of) languages (no matter if they are spoken, signed or written). In any case, a system that allows for “universal” translation either can translate from/to any language or it can be extended to any language. There remain open challenges which include increasing the number of covered languages, dealing with non-written languages and producing robust and fair outputs.
Individualism as an improvised strategy in the dispersion of jihadist videos in YouTube

EN] Introduction: The jihadist global movement changes its mechanics of ideological diffusion when amplifying its message thanks to the viral expansion on social networks and the role of individual users. Methodology: This study analyses a total of 234 videos collected from the searches with more visualizations using four definitions considered by the UN about the jihadist organization Jabhat al Nusrah, which changed its name on July 2016 to Jabhat Fateh Al Sham. Results and conclusions: We confirm that jihadist organizations do not have the capacity to fully control their discourse on YouTube due to the huge spreading and to the role of individual users in the generation of new contents that easily avoid the platform’s restrictions. Besides, we conclude that the accessible videos are of amateur, violent type, with jihadist aesthetic, without barely any postproduction process and with scarce presence of traditional media acting as amplifiers for the violent discourse.
NANOTECHNOLOGICAL APPLICATIONS OF BIOMOLECULAR MOTOR SYSTEMS

Recent advances in understanding how biomolecular motors work have raised the possibility that they might find applications as nanomachines. For example, they could be used as molecule-sized robots that work in molecular factories where small, but intricate structures are made on tiny assembly lines, that construct networks of molecular conductors and transistors for use as electrical circuits, or that continually patrol inside "adaptive" materials and repair them when necessary. Thus biomolecular motors could form the basis of bottom-up approaches for constructing, active structuring and maintenance at the nanometer scale.
Models of Plans to Sup municat ion

Agents collaborating to achieve a goal bring to their joint activity different beliefs about ways in which to achieve the goal and the actions necessary for doing so. Thus, a model of collaboration must provide a way of representing and distinguishing among agents’ beliefs and of stating the ways in which the intentions of different agents contribute to achieving their goal. Furthermore, in collaborative activity, collaboration occurs in the planning process itself. Thus, rather than modelling plan recognition, per se, what must be modelled is the augmentation of beliefs about the actions of multiple agents and their intentions. In this paper, we modify and expand the SharedPlan model of collaborative behavior (Grosz & Sidner 1990). We present an algorithm for updating an agent’s beliefs about a partial SharedPlan and describe an initial implementation of this algorithm in the domain of network management.
Modeling Triple Friction Pendulum Bearings for Response-History Analysis

There are currently no applicable hysteresis rules or nonlinear elements available in structural analysis software that can be used to exactly model triple Friction Pendulum bearings for response-history analysis. Series models composed of existing nonlinear elements are proposed since they can be immediately implemented in currently available analysis software. However, the behavior of the triple Friction Pendulum bearing is not exactly that of a series arrangement of single concave Friction Pendulum bearings—though it is similar. This paper describes how to modify the input parameters of the series model in order to precisely retrace the true force-displacement behavior exhibited by this device. Recommendations are made for modeling in SAP2000 and are illustrated through analysis of a simple seismically isolated structure. The results are confirmed by (a) verifying the force-displacement behavior through comparison with experimental data and (b) verifying the analysis through comparison to the results obtained by direct numerical integration of the equations of motion.
Wide-Area Measurement Based Nonlinear Global Optimal Control for Power System Stability Enhancement

Centralized control using the wide-area information has been suggested to enhance the dynamic performance of large interconnected power systems. According to the inverse system method and LQR optimal control theory, this paper presents a nonlinear hierarchical global controller based on the wide-area information including the on-line measured center of rotor angle and total unbalanced power. Moreover, it has been verified that the optimal control in the sense of linear quadratic state regulator principle for the linearized system is equivalent to an optimal control in the sense of extended quadratic output regulator performance index for the primitive nonlinear system. So, the designed controller is an optimal controller for the nonlinear system digital simulation demonstrates that the multi-machine power system under the nonlinear global control has less settling time, swing times, oscillatory peak value and more critical clearing time and better voltage stability performance than that under PID control and nonlinear decentralized control.
A Survey: Identification of Different Thoracic Disease Using Convolutional Neural Network

: Thoracic disease affects various parts of the organ around the chest at different paces, and accounts for the number of deaths in India. We have vaccines and medicines to prevent the spread of infection-causing bacteria, viruses, and fungi in the organs, but many patients still die as a result of the inability in early detection of the disease. The diagnosis of thoracic disease relies on chest x-ray images that are manually interpreted by an expert. Chest x-ray images have their own set of flaws, which can lead to inaccuracy in judging infected areas or even the presence of infections. This paper focuses on using computer-assisted techniques, different algorithms present in machine learning and deep learning pre-trained CNN models (ResNet, DenseNet, CheXNet and VGG), and classification techniques(Logistic Regression, SVM, K-nn) in the medical and healthcare field for the classification of chest x-ray and diagnosis of thoracic disease.
Single-cycle quasi-resonant converter with controlled timing of the power switches

In this paper, aspects of the real operation of a single-cycle quasi-resonant power converter are analyzed and experimentally verified. In particular, electrical stresses and power losses in the complementary power switches are considered. A variable timing strategy of the switches, based on the direct measurement of the resonance period, is proposed and described. The experimental results and comparisons carried out on a laboratory prototype of the power converter are reported and discussed.
Deep Halftoning with Reversible Binary Pattern

Existing halftoning algorithms usually drop colors and fine details when dithering color images with binary dot patterns, which makes it extremely difficult to recover the original information. To dispense the recovery trouble in future, we propose a novel halftoning technique that converts a color image into binary halftone with full restorability to the original version. The key idea is to implicitly embed those previously dropped information into the halftone patterns. So, the halftone pattern not only serves to reproduce the image tone, maintain the blue-noise randomness, but also represents the color information and fine details. To this end, we exploit two collaborative convolutional neural networks (CNNs) to learn the dithering scheme, under a nontrivial self-supervision formulation. To tackle the flatness degradation issue of CNNs, we propose a novel noise incentive block (NIB) that can serve as a generic CNN plug-in for performance promotion. At last, we tailor a guiding-aware training scheme that secures the convergence direction as regulated. We evaluate the invertible halftones in multiple aspects, which evidences the effectiveness of our method.