Miracle-dz/UniFAR-FTUs huggingface dataset:
Preparation of a Reinforced Polymeric Coating with Inorganic Nano Additives as UV-Stabilizers and Protect Oil Pipelines from Corrosion

- In this research a nano polymeric coating has been prepared to be used for the protection of the external surface of oil pipelines (medium carbon steel (CK50)) from corrosion in salt water (3.6% NaCl) . This coating is reinforced by inorganic (nano and micro) additives to apply a high resistance against chemicals and salts. These oxides protect the epoxy resin from degradation by preventing the epoxy molecules and active functional groups from absorbing ultraviolet light in the range (290-315) nm strongly.This coating is also resistant to the high and low temperatures, humidity, scratch and water. This coating was prepared from the reaction of 2-[[4-[2-[4-(Oxiran-2-ylmethoxy) phenyl] propan-2-yl] phenoxy] methyl] oxirane (Diglycidyl Ether of Bisphenol A) and the hardener (EDA). The mixing ratio of the two parts was (4:1). Reinforced with inorganic (nano and micro) additives such as titanium dioxide (TiO 2 ) and zinc oxide (ZnO) which have been used as an anticorrosion. These additives are non-toxic , thermally stable and have a high degree of the miscibility with epoxy. The weight percentages of the mixing are (0 and 10 % wt). The corrosion rate results show that using (nano and micro) coating give good results in increasing the corrosion resistance compared with the (non additives) epoxy.This coating was characterized using different spectroscopic methods (FT-IR, UV/Vis). Several tests were conducted , including differential scanning calorimetry (DSC), thermogravimetric analysis (TGA) , mechanical tests and evaluation of corrosion resistance was made by using static potential test.
University of Groningen Cross-Feeding among Probiotic Bacterial Strains on Prebiotic Inulin Involves the Extracellular exo-Inulinase of Lactobacillus paracasei Strain W20 Boger,

Probiotic gut bacteria employ specific metabolic pathways to degrade dietary carbohydrates beyond the capabilities of their human host. Here, we report how individual commercial probiotic strains degrade prebiotic (inulin type) fructans. First, a structural analysis of commercial fructose oligosaccharide-inulin samples was performed. These -(2-1)-fructans differ in termination by either glucose (GF) or fructose (FF) residues, with a broad variation in the degrees of polymerization (DPs). The growth of individual probiotic bacteria on short-chain inulin (sc-inulin) (Frutafit CLR), a -(2-1)-fructan (DP 2 to DP 40), was studied. Lactobacillus salivarius W57 and other bacteria grew relatively poorly on sc-inulin, with only fractions of DP 3 and DP 5 utilized, reflecting uptake via specific transport systems followed by intracellular metabolism. Lactobacillus paracasei subsp. paracasei W20 completely used all sc-inulin components, employing an extracellular exo-inulinase enzyme (glycoside hydrolase family GH32 [LpGH32], also found in other strains of this species); the purified enzyme converted high-DP compounds into fructose, sucrose, 1-kestose, and F2 (inulobiose). The cocultivation of L. salivarius W57 and L. paracasei W20 on sc-inulin resulted in cross-feeding of the former by the latter, supported by this extracellular exo-inulinase. The extent of cross-feeding depended on the type of fructan, i.e., the GF type (clearly stimulating) versus the FF type (relatively low stimulus), and on fructan chain length, since relatively low-DP -(2-1)-fructans contain a relatively high content of GF-type molecules, thus resulting in higher concentrations of GF-type DP 2 to DP 3 degradation products. The results provide an example of how in vivo cross-feeding on prebiotic -(2-1)-fructans may occur among probiotic lactobacilli. IMPORTANCE The human gut microbial community is associated strongly with host physiology and human diseases. This observation has prompted research on preand probiotics, two concepts enabling specific changes in the composition of the human gut microbiome that result in beneficial effects for the host. Here, we show how fructooligosaccharide-inulin prebiotics are fermented by commercial probiotic bacterial strains involving specific sets of enzymes and transporters. Cross-feeding strains such as Lactobacillus paracasei W20 may thus act as keystone strains in the degradation of prebiotic inulin in the human gut, and this strain–exo-inulinase combination may be used in commercial Lactobacillus-inulin synbiotics.
Features detecting bad violin playing

The research presented in this paper looks at the violin’s entire timbre space and how it is influenced by the player. It differs from existing violin sound analyses research in that it includes beginner player sound. Three features which are accurate representational measures from which a computer can determine a violinist’s playing standard are detailed in this paper. These features analyse content which falls into the frequency region below the normal playing range of the violin. This means below G3 which is approximately 196 Hz when a violin is tuned to A440. Research influencing this work comes from many areas including violin acoustics, music teaching methods and aids, music information retrieval, automatic accompaniment systems, speech recognition and player-instrument relationships. Given that much existing work has focused on how to best represent violin sound for use within instrument recognition systems [1, 2] and also from an instrument quality perspective [3], little reflects or represents the relationship between player and sound produced. The outcomes of this research can be applied in various systems including the development of a violin or bowed string instrument teaching aid.
Exposure of vehicular pollution in altering the pulmonary functions in traffic policemen in Multan city

The objectives of this study was to assess the effect of traffic air pollution on the pulmonary functions among the traffic policemen and general policemen posted at various chowks and police stations respectively in Multan city. Pulmonary function test (PFT) were recorded on the basis of age, smoking history and body mass index (BMI) matched 50 traffic policemen (study case group) and 50 general policemen (control group) of male category. In altering lung function, chronic smoking was known to be a critical factor. Between the smokers as well as nonsmokers of both the groups, pulmonary function test parameters were compared. In non-smokers group, significant decreased was found to be in vehicle control (VC) (4.54±0.12), peak inspiratory flow (PIF) (192.4±15.29), forced expiratory flow (FEF-25) (6.04±0.68) and forced respiratory volume in 1 second (FEV1) (3.97±0.11) in study case group as compared to that of control group. Similarly, in smokers group, significant decrease was found to be in VC (4.26±0.11), peak expiratory flow (PEF) (78.62±2.42), forced respiratory volume in 1 second (FEV1) (3.45±0.09), FEF-25 (5.28±0.23), maximum voluntary ventilation (MVV) (87.4±4.69) and PIF (238.6±14.33) in study case group as compared to that of the control group. These changes showed that in the traffic policemen group restriction to the lung expansion, narrowing of the air ways and obstruction were to be found as compared to the general policemen group. Decreased functional capacity of the lungs and chronic smoking worsens the condition are due to the exposure to vehicular pollution for several hours in a day for many years.
3D Technologies to Acquire and Visualize the Human Body for Improving Dietetic Treatment

This research aims to improve adherence to dietetic-nutritional treatment using state-of-the-art RGB-D sensor and virtual reality (VR) technology. Recent studies show that adherence to treatment can be improved by using multimedia technologies which impact on the body awareness of patients. However, there are no studies published to date using 3D data and VR technologies for this purpose. This paper describes a system capable of obtaining the complete 3D model of a body with high accuracy and a realistic visualization for 2D and VR devices to be used for studying the effect of 3D technologies on adherence to obesity treatment.
Parabolic Equations with Multiple Singularities

Models of flow of multiple immiscible fluids in a porous matrix and/or phenomena of multiple transitions of phase, result into quasilinear parabolic equations, with measurable coefficients and exhibiting multiple singularities and/or degeneracies (in the sense made precise in Section 1.1 below). We discuss the problem of the continuity of the transition parameters, for example saturation in the flow of immiscible fluids, or temperature in isothermal phase transitions. We review and summarize the main points of the theory and will present some recent results in this direction, pointing to the new mathematical tools generated by these investigations. We will also indicate the main open questions of physical and mathematical interest and discuss their relevance. AMS Subject Classification. 35K20, 35K40, 35K55, 35K65, 35K99, 35Q35
Dynamic Torque Limitation Principle in the Main Line of a Mill Stand: Explanation and Rationale for Use

This paper substantiates why it is necessary to limit the dynamic loads in stand shafts when closing angular gaps. The paper is a feasibility study of a concept developed specifically to limit each of the factors that affect amplitude of the dynamic torque; limitations applied are determined on a case-by-case basis. The research team studied the components of elastic torque in a dual-mass electromechanical system of Mill 5000 caused by vibrations arising from the elasticity of transmission as well as from the vibrations caused by elastic collision itself. It is shown that the lowest possible pre-acceleration is necessary for decreasing the dynamic coefficient at a near-nominal load torque. A principle of limiting dynamic loads when closing an angular gap is proposed, which implies collecting tachograms of an electric drive subjected to positive or negative acceleration before and after the fed metal is captured. The research team has developed drive control principles to implement this approach. The recommendation is to upgrade the electric drives of the reversing stand in Mill 5000.
Quality of life of people with hansen’s disease assisted in a reference hospital, Paraíba-Brazil

Objective: Evaluate the degree of impairment of the quality of life of people with Hansen’s disease, according to social demographic and clinical variables Method: Descriptive, transversal, quantitative study, involving 45 patients from a reference hospital located in João Pessoa, Paraíba, Brazil. For obtaining data, interviews were performed based on a semi-structured questionnaire, including social demographic and clinic variables of the participants; to evaluate their life quality the instrument Dermatology Life Quality Index was used, after approval in the Committee of Ethics in Research of the Federal University of Paraíba. In the data analysis, the nonparametric Test of the Chi-square of Pearson was used with level of significance of 5% (p<0,05), being used the Yates correction continuity, when necessary. Results: It is highlighted a prevalence of male, brown, single, aged 18 to 40 individuals, with family income lower than three minimum salaries and low schooling. From this total, 88,9% presented the clinical multibacillary form of the Hansen’s disease and 60% of them, with level of impairment of quality of life varying between moderate and very serious, according to scores of the instrument used.
Continuous Adaptation in Multi-agent Competitive Environments

In a multi-agent competitive environment, we would expect an agent who can quickly adapt to environmental changes may have a higher probability to survive and beat other agents. In this paper, to discuss whether the adaptation capability can help a learning agent to improve its competitiveness in a multi-agent environment, we construct a simplified baseball game scenario to develop and evaluate the adaptation capability of learning agents. Our baseball game scenario is modeled as a two-player zero-sum stochastic game with only the final reward. We propose a modified Deep CFR algorithm to learn the strategies of agents in a half-inning game. We also propose a strategy adaptation mechanism that continuously updates strategies based on the anticipation of the opponent’s strategy in the inference time. We form several teams, with different teams adopting the same adaptation mechanism but different initial strategies, trying to analyze (1) whether an adaptation mechanism can help in increasing the winning percentage and (2) what kind of initial strategies can help a team to get a higher winning percentage. The experimental results show that the winning percentage can be increased for the team with an initial strategy learned from the modified Deep CFR algorithm. Nevertheless, those teams with deterministic initial strategies actually become less competitive.
Normed Dinosaurs in a Creative Chaos? Software Development as Controlled Learning Process

Since the end of the 1960s, the software engineering discipline strives to develop models for work processes for developing software. The ‘software crisis’, i.e. the phenomenon that the cost for hardware was falling while the cost for software was rising, was one of the reasons to investigate into the work processes which are adequate for developing software, since the chaotic and often unsystematic work process in software development was seen as one of the main reasons for this crisis. As the most important goal in many situations, project success in the form of customer satisfaction has been identified. In practical projects, two causes of customer dissatisfaction are paramount: Defects in the product, and cost as well as time overruns in the process. In this context, a base for planning was searched for as well as some means which allow to establish transparency with respect to the reached level of progress in the process and of correctness of the implemented part of the product. This transparency is to be used to recognize problems with respect to process or product as early as possible, in order to be able to find countermeasures. Since the developed software product is the result of the software development process, and thus measures for better product quality are are to be integrated into a software development process, it is the software process where enhancements should start. In the course of the three decades since the end of the sixties, a plethora of models and meta models for conceptualizing and fixing software development processes by describing them have been developed. Examples are the cleanroom approach, the capability maturity model, SPICE, ISO 9000 and the V model. Each of them has a descriptive component, i.e. each presents a conceptual model to describe software development processes. Some have an evaluative component, i.e. they are used for assessing software development processes. Some of them also have a prescriptive component, i.e. they prescribe some necessary content of adequate processes, or they make at least recommendations about the next steps to be taken to enhance an existing software development process. Typically, it is the middle management which has the responsibility to implement some process enhancement. This primary assignment of responsibility for the software development process to the management is one reason for the enhancement activities often being ineffective. The problem lies in the acceptance of the processes by the software developers. Often, the latter feel the described processes to be not very helpful. They often perceive prescribed processes and the clerical work connected to them as an almost useless and nasty overhead with no benefit. The fixed process definition is not understood as an instrument which helps to find the right direction for the work process, but rather as some kind of chains which one tries to get rid of. Additionally, developers see written process not so much as one of their work means, but rather as the property of a methods
Operating Modes Analysis and Control Strategy of Single-Stage Isolated Modular Multilevel Converter (I-MMC) for Medium Voltage AC/DC Grid

For the medium-voltage (MV) AC/DC grid integrating with renewable sources, this paper introduces a single-stage isolated modular multilevel converter (I-MMC) topology. Compared with the conventional modular multilevel converter with DC transformer, I-MMC has the advantages of smaller size and simpler control strategy, which can realize single-stage power conversion among MVAC, MVDC and LVDC ports. Its basic circuit working process is given and three representative working modes of the I-MMC are discussed in detail. Coordinative control strategy based on double modulation freedoms is proposed for different modes of I-MMC. Moreover, an (10kV AC, ±10kV DC, 760V DC) I-MMC system is established in MATLAB/SIMULINK, and a scale-down experimental platform is built to verify the proposed control strategy.
Congestion Avoidance in Vehicular Networks: A Contemporary Survey

Congestion in vehicular ad hoc networks affects the performance of delay-sensitive applications when exchanging emergency or general information sharing messages. In particular, during emergencies on roads like road accidents and security warnings demand high reliability and low latency. However, in traditional solutions, such messages use the same control channel for transmission leading up to a saturated or congested channel. Furthermore, the highly dynamic nature of vehicular networks leading up to unpredictable routing patterns, subsequently degrading the network performance. An uneven deliverance of these critical messages can be catastrophic for the delay-sensitive applications. Thus, congestion control remains one of the most challenging problems within the domain of vehicular networks. This paper provides a comprehensive overview of the working of vehicular networks, the recent research advances to cater for congestion in such networks, and open problems and challenges relevant to congestion avoidance.
Vacuum Switchgear; Past, Present, and Future

This paper briefly reviews the evolution of vacuum circuit breaker (VCB) and vacuum interrupter (VI) technology from the early days up to the present day, and then looks at future trends and applications for the technology. The paper starts with a simple overview of the basic principles which both provide the excellent performance of vacuum interrupters in switching current, and which are also responsible for the limitations of this technology. The next section is a brief review of how VI & VCB technology has developed over the past 60 years and has been applied in circuit breakers up to the present day. Finally, future requirements and applications are discussed together with the strengths and weaknesses of the technology in meeting these new challenges.
A Knowledge Graph Framework for Software-Defined Industrial Cyber-Physical Systems

Automatic code generation is a critical step towards flexible manufacturing processes. In the last decade, Model-Driven Engineering is commonly adopted for code generation while requiring tight coupling between the model and its corresponding code, which increases the difficulty of dynamic reconfiguration in the system. To improve the flexibility and efficiency of industrial software design and development processes, Knowledge Graph is proposed to be applied in knowledge-driven code generation process in this paper. The knowledge-driven query system can conduct parameter searching, variable calculation, ontology reasoning, and code invocation to assist code generation. In addition, a structure of domain-specific knowledge graph combined with SQL database and reasoning rules are proposed to improve performance. The feasibility of our method is demonstrated through the dynamic AGV route planning example.
Model Learning and Model Checking of IPSec Implementations for Internet of Things

With the development of Internet of Things (IoT) technology, the demand for secure communication by smart devices has dramatically increased, and the security of the IoT protocol has become the focus of cyberspace. Recently, some scholars have attempted to extend the IPSec protocol to IPv6 over Low-Power Wireless Personal Area Networks (6LoWPAN) to ensure end-to-end security, which makes it essential to analyze the vulnerability of the IPSec protocol to enhance the security of the IoT. In this study, we use a method combining model learning and model checking to analyze the dynamic vulnerability of IPSec protocol implementations. This method automatically infers the black-box model and compares it with the relevant specifications to expose the defects of the system implementation and search its logic vulnerabilities. We first employ model learning on three IPSec implementations to infer state machine models; then, we use model checking to verify that these models satisfy basic security properties and conform to the RFCs. Our analysis reveals three new security issues: a wrong interaction causing server exception and two violations of the standard.
Motor Imagery EEG Signals Decoding by Multivariate Empirical Wavelet Transform-Based Framework for Robust Brain–Computer Interfaces

The robustness and computational load are the key challenges in motor imagery (MI) based on electroencephalography (EEG) signals to decode for the development of practical brain-computer interface (BCI) systems. In this study, we propose a robust and simple automated multivariate empirical wavelet transform (MEWT) algorithm for the decoding of different MI tasks. The main contributions of this study are four-fold. First, the multiscale principal component analysis method is utilized in the preprocessing module to obtain robustness against noise. Second, a novel automated channel selection strategy is proposed and then is further verified with comprehensive comparisons among three different strategies for decoding channel combination selection. Third, a sub-band alignment method by utilizing MEWT is adopted to obtain joint instantaneous amplitude and frequency components for the first time in MI applications. Four, a robust correlation-based feature selection strategy is applied to largely reduce the system complexity and computational load. Extensive experiments for subject-specific and subject independent cases are conducted with the three-benchmark datasets from BCI competition III to evaluate the performances of the proposed method by employing typical machine-learning classifiers. For subject-specific case, experimental results show that an average sensitivity, specificity and classification accuracy of 98% was achieved by employing multilayer perceptron neural networks, logistic model tree and least-square support vector machine (LS-SVM) classifiers, respectively for three datasets, resulting in an improvement of upto 23.50% in classification accuracy as compared with other existing method. While an average sensitivity, specificity and classification accuracy of 93%, 92.1% and 91.4% was achieved for subject independent case by employing LS-SVM classifier for all datasets with an increase of up to 18.14% relative to other existing methods. Results also show that our proposed algorithm provides a classification accuracy of 100% for subjects with small training size in subject-specific case, and for subject independent case by employing a single source subject. Such satisfactory results demonstrate the great potential of the proposed MEWT algorithm for practical MI EEG signals classification.