Miracle-dz/UniFAR-FTUs huggingface dataset:
Role of Foeniculum vulgare oil on the antimicrobial activity of some antibiotics against resistant pathogenic Gram-negative bacteria

In this manuscript, the antimicrobial efficacy of fennel oil alone and combined with antibiotics were studied by the agar diffusion method. Fifty samples from edible food were collected from supermarkets in the El-Giza governorate, Cairo, Egypt. The presence of multi drug resistant bacteria in the edible food is reported. The aim of this work focuses the sensitivity improvement of the most five resistant Gram negative bacterial isolates due to the presence of fennel oil in the agar medium. Isolation was carried out by classical method using a selective medium followed by biochemical tests. Â The results showed that the identified isolates include 50 pathogenic bacteria like Staphylococcus spp. 10 isolates (40%), Micrococcus spp. 1 isolate (4%), E. coli 11 isolates (44%), Citrobacter freundii 1 isolate (4%), Enterobacter species 1 isolate (4%), Enterobacter cloacae 1 isolate (4%) and P. aeruginosa 1 isolate (4%). There are significant improvements in the antimicrobial activity of tetracycline against E. coli isolated from milk due to the fennel oil contained medium. In addition, the sensitivity of Enterobacter spp. to meropenem was significantly increased in the medium containing fennel oil. Furthermore, the sensitivity of E. coli and Enterobacter spp. had significantly decreased to ciprofloxacin in the medium containing fennel oil.
SociUM : Adaptation and Personalisation in Social Systems : Groups , Teams , Communities Workshop Proceedings

We present a combined perspective over groupware systems and attentive user interfaces to address the balance between the rising needs for collaboration and the rising costs of not paying attention and being interrupted. We introduce a framework that derives attentive devices from groupware mediation modes to take into account attentional phenomena. Finally, we demonstrate the framework’s role in a brainstorming tool, explain what the attentive devices do, and provide preliminary results from a pilot experiment.
DIGITAL AGENDA FOR EUROPE

Since 1995, information and communication technologies (ICTs) have driven productivity gains and growth in the EU[1]. Over the past three decades, technological ‘convergence’ has been blurring the boundaries between telecommunications, broadcasting and IT. The Commission launched the digital single market in 2015 to deliver the main legislative proposals, such as boosting e-commerce, copyright, ePrivacy, harmonisation of digital rights, harmonised VAT rules and cybersecurity.
Importance and Role of Programming Languages in Software Quality Improvement

The quality of a software product depends upon the features of the product which meets the need of customers and thereby provide product satisfaction. The success and failure of a software product is dependent on the satisfaction of the customer/user. If the user is able to use and modify the things easily for a long time and remains satisfied then only a software succeeds. And a Software fails- When its users are dissatisfied, When it is error prone, When it is difficult to change and even harder to use. We believe that the programming tool plays an important role in the success and failure of a software product. When we plan for a software solution, we have many different programming languages to choose from, and it's easy to get lost in the intricacies of each one. The choice of a programming language therefore constitutes a strategic decision in achieving software quality. Here in this paper we have analysed various programming languages based on various characteristics and shown their impact on software quality.
Neural Networks for Fine-grained Entity Type Classification ∗ Sonse Shimaoka

In this thesis, we investigate several neural network architectures for fine-grained entity type classification and make four key contributions. First, we incorporate pretrained word embeddings to enable our models to use the information of similarities between word meanings and establish that hand-crafted features and word embeddings complement each other. Second, we propose a novel attention-based neural network model for the task that unlike previously proposed models recursively composes representations of entity mention contexts. Through both qualitative and quantitative analysis we establish that the attention mechanism learns to attend over syntactic heads and the phrase containing the mention, both of which are known to be strong handcrafted features for our task. Third, despite using the same evaluation dataset, the literature frequently compare models trained using different data. We demonstrate that the choice of training data has a drastic impact on performance, which decreases by as much as 9.85% loose micro F1 score for a previously proposed method. Despite this discrepancy, our best model achieves state-of-the-art results with 75.36% loose micro F1 score on the well-established FIGER (GOLD) dataset and we report the best results for models trained using publicly available data for the OntoNotes dataset with 64.93% loose micro F1 score. Fourth, We introduce parameter sharing between labels through a hierarchical encoding method, that in low-dimensional projections show clear clusters for each type hierarchy.
Direct Torque Control of Induction Motor Using Three-Level Neutral Point Clamped Inverter

The direct torque control strategy of squirrel-cage induction motor using three-level neutral point clamped inverter is presented. The strategy used for controlling the torque of induction motor includes the change in applied voltage to the squirrel-cage induction motor . The variable voltage is provided with the help of look up table to the inverter. It is observed that the torque ripples are much in three-level inverter as compared to three level ineverter. This is because of the high dv/dt ratio of the output voltage of inverter. The current ripple produces torque ripples in steady state. The performance of motor in transient state and steady state are shown. The parameters of machine are given and the controlling strategy is performed using MATLAB/Simulink software. The control strategy is simulated on a 5 hp SQIM drive with three-level insulated-gate bipolar transistor (IGBT) inverter in MATLAB/Simulink software.
Development of Three-Phase Wireless Power Transfer System with Reduced Radiation Noise

A three-phase wireless power transfer (WPT) system, which has six primary coils and six secondary coils is proposed in this paper. The three-phase WPT system reduces the radiation noise by canceling the noise using pairs of coils placed opposite to each other. However, a magnetic interference among the multiple coils decreases the transmission efficiency due to a circulating current among the primary coils, and the secondary coils in WPT systems with multiple coils. The proposed three-phase WPT system cancels out the effect due to the interference among the six coils on each side. First, the WPT system with the 12 coils is proposed. Then, a canceling condition of the magnetic interference among the coils is mathematically introduced from the voltage equation on the coils. Finally, the proposed WPT system is experimentally demonstrated with the 3-kW prototype. The experimental result shows that the radiation noise at the fundamental frequency is suppressed from 12.2 dBμA to 2.1 dBμA.
Deep Feature Learning for EEG Recording Using Autoencoders

In this era of deep learning and big data, the transformation of biomedical big data into recognizable patterns is an important research focus and a great challenge in bioinformatics. An important form of biomedical data are electroencephalography (EEG) signals, which are generally strongly affected by noise and there exist notable individual and environmental differences. In this paper, we focus on learning discriminative features. Inspired by traditional image compression techniques to learn a robust representation of an image, we introduce and compare three strategies for learning features from EEG using three specifically designed autoencoders. Channel-wise autoencoders focus on features in a certain channel while Image-wise autoencoders instead learn features from the whole trial. The GANbased autoencoders are further designed for EEG data filtering. While in this paper we will only focus on elimination of some information of EEG images using GAN-based autoencoders. We used a UCI EEG dataset. Our results show that using both Channel-wise and Image-wise autoencoders achieve good performance for discriminating a classification problem with nearly state of art accuracy. A further experiment using shared weights showed that the shared weights technique only slightly influenced learning but it reduced training time significantly. The experiment on GAN-based autoencoders shows it can it can successfully remove the disease information in nearly 70% EEG images.
Extremal number of theta graphs of order 7

For our purposes a graph G is finite, undirected and has no loops or multiple edges. We denote the vertex set of G by V (G) and the edge set of G by E(G). The cardinalities of these sets are denoted by v(G) and E(G), respectively. The cycle on n vertices is denoted by Cn. A theta graph θn is defined to be a cycle Cn to which we add a new edge that joins two non-adjacent vertices. The neighbor set of a vertex u of G in a subgraph H of G, denoted by NH(u), consists of the vertices of H adjacent to u. The joint G1 ∨G2 of two vertex disjoint graphs G1 and G2 is the graph whose vertex set V (G1)∪V (G2) and edge set consists of E(G1)∪E(G2) together with all the edges joining V (G1) and V (G2). For vertex disjoint subgraphs H1 and H2 of G, we let E(H1, H2) = {xy ∈ E(G) : x ∈ V (H1), y ∈ V (H2)} and E(H1, H2) = |E(H1, H2)| . For a proper subgraph H of G we write G[V (H)] and G−V (H) simply as G[H ] and G − H , respectively (G[V (H)] is the induced subgraph). In this paper, we consider the Turán-type extremal problem with the θ-graph being the forbidden subgraph. Since a bipartite graph contains no odd θ-graph, we consider nonbipartite graphs. First, we recall some notation and terminology. For a positive integer n and a set of graphs F, let G(n;F) (and H(n;F)) denote the class of non-bipartite F-free graphs (class of non-bipartite Hamiltonian F-free graphs) on n vertices, and
Grammars of Organising and SenseMaking Paper number 03 / 12

The issue of organisational sense-making has been much researched and written about in recent years. However, despite the extensive literature that has been devoted to articulating the crucial aspects of sense-making little has been written about how structurally such sense-making attempts are actually facilitated and realised. Instead much of the attention tends to be focused on the features of sense-making or the sequence of steps involved. In this paper we explore the underlying organising grammars that enable the sense-making process to be accomplished, sustained and extended. Grammar is what makes collective meaning possible and in this paper we examine three organising grammars of sense-making for legitimising and justifying managerial actions and decision-making within the context of a family-owned newspaper called the Courier. We do this through a study of the narratives employed in the sense-making process.
Oral Joint Health Supplements : Chemistry , Pharmacology , and Administration Guidelines ❯ ❯

Complementary and alternative medi cal therapies, including the use of oral nutritional supplements, have become increasingly popular in the veterinary community, particularly the equine industry. Among these, joint health supplements are ubiquitously employed. Oral joint health supplements are popular not only because of the high incidence of osteoarthritis (OA; degenerative joint disease) in the equine population but also because of limitations of conventional medical treatment. Despite the widespread availability and administration of oral nutritional supplements, these products are not considered to be drugs by the FDA. As a result, nutritional supplements, including equine oral joint health supplements, are poorly regulated and typically lack important pharmacologic information, such as absorption, distribution, metabolism, excretion, recommended dosages, and safety information. This dearth of basic scientific information makes it challenging for practicing veterinarians to identify quality oral joint health supplements. Comprehensive reviews have been published regarding the medical management of equine OA and the use of nutraceuticals in horses with OA (both of these reviews include an up-to-date description of the pathophysiology of OA) as well as future OA management strategies. Together, these lay an excellent foundation for this discussion, which focuses on the rationale for the administration of various oral joint health supplements, including glucosamine, chondroitin sulfate, methylsulfonylmethane (MSM), Oral Joint Health Supplements: Chemistry, Pharmacology, and Administration Guidelines
C Y ] 2 4 D ec 2 01 7 Inference of Personal Attributes from Tweets Using Machine Learning

Using machine learning algorithms, including deep learning, we studied the prediction of personal attributes from the text of tweets, such as gender, occupation, and age groups. We applied word2vec to construct word vectors, which were then used to vectorize tweet blocks. The resulting tweet vectors were used as inputs for training models, and the prediction accuracy of those models was examined as a function of the dimension of the tweet vectors and the size of the tweet blocks. The results showed that the machine learning algorithms could predict the three personal attributes of interest with 60–70% accuracy.
Probabilistic Graphical Models 10-708 , Spring 2018 22 : A Hybrid of Deep Learning and Graphical Models

Generative Adversarial Networks (GAN) assumes a implicit generative model without Markov Chains assumption, which result in the best samples to human eyes. The procedure for GAN is to map noise to the data distribution, where it trains a generator and a discriminator alternatively. The goal for the generator is to generate samples which fools the discriminator, while the discriminator tries to identify the samples from true data distribution and samples generated by the generator. The final objective function becomes: min G max D Ex∼pdata(x)[log(D(x))] + Ez∼pdata(z)[log(1−G(D(z)))], (1)
Communication Error Control of Multiple-Precision MLFMA

We introduce and demonstrate a new error control scheme for the computation of far-zone interactions in the multilevel fast multipole algorithm when implemented within a multiple-precision arithmetic framework. The proposed scheme provides the optimum truncation numbers as well as the machine precisions given the desired relative error thresholds and the box sizes for the translation operator at all frequencies. In other words, unlike the previous error control schemes which are valid only for high-frequency problems, the proposed scheme can be used to control the error across both lowand high-frequency problems. Optimum truncation numbers and machine precisions are calculated for a wide range of box sizes and desired relative error thresholds with the proposed error control scheme. The results are compared with the previously available methods and numerical surveys.
ESTUDO ETNOBOTÂNICO DO CAJUEIRO (Anacardium ocidentale L.): UMA ÁRVORE NATIVA DO BRASIL

Cashew tree (Anacardium occicentale L.) is a plant native to Brazil and of great importance for the socioeconomic development of several regions of the world. Its antimicrobial activity has been studied scientifically in order to obtain new alternative sources of treatment for oral diseases. The present study carried out an ethnobotanical and bibliographical survey on this medicinal plant through scientific research published in PUBMED, SCIELO and LILACS databases. Eight articles that analyzed the cashew inhibitory potential against pathogenic species of the oral microbiota were included in the research. Antimicrobial, antioxidant and anticrugigenic activities have been reported and attributed to tannin compounds. Among the parts used stand the fruits, the stem bark and the leaves extracts. Anacardium occidentale L. is a promising alternative for the development of phytotherapeutic drugs with inhibitory potential.
A Study to Assess the Prevalence of Attention Deficit Hyperactivity Disorder among Primary School Children at Selected Schools of Kancheepuram District in Tamilnadu

Background: Attention Deficit Hyperactivity Disorder (ADHD) is a Neurobiological disorder characterised by Inattention, Hyperactivity, and Impulsivity. It is one of the rising public health problems in the world. Aim: To assess the prevalence of ADHD among primary school children. Materials and methods: Cross sectional descriptive research design was adopted. Study was conducted at selected primary schools of Kancheepuram district in Tamilnadu. Sample consisted of 865 children with the age group of 4-10 years from five different primary schools. Modified Conner’s teachers rating scale was used to identify the symptoms of Attention deficit hyperactivity disorder among primary school children. For data analysis Descriptive and inferential statistics was used. Results: Results showed that out of 865 children total number of males was 407, females was 458. ADHD symptoms were identified 37(69%) male children and 17(31%) female children were indentified. Prevalence of ADHD was more in boys than girls. Conclusion: Prevalence of ADHD estimates in school children ranging from 3-12% and worldwide prevalence of ADHD in children is estimated to approximately 5%. Study reported that 6.3% of primary school children with symptoms of ADHD were identified. If found out symptoms early, can reduce the Incidence of ADHD among children in future.
Error Control Techniques For Digital Communication

error control techniques for digital communication is available in our book collection an online access to it is set as public so you can download it instantly. Our digital library saves in multiple countries, allowing you to get the most less latency time to download any of our books like this one. Kindly say, the error control techniques for digital communication is universally compatible with any devices to read.
Robotic Manipulation with a Human in the Loop - Accuracy Estimation of the Baxter Robot

This paper illustrates the design and implementation of a robotic software system based on robot-human interactions, which increases the applications of low-cost, inaccurate robots such as Baxter. The first four parts of the paper discuss the motivation, market & industry, IP strategy and system workflow. Then the paper explains a specific technical contribution of the project in detail – estimating Baxter’s positioning accuracy. Based on forward kinematics and Jacobian matrix respectively, two models are built to convert the error tolerance of the joints to the error tolerance of the end effector in the Cartesian space. The second model based on Jacobian matrix is chosen as the final approach since it has linear complexity and it is more computationally efficient. The result gives a reasonable estimation of Baxter’s accuracy, which allows valid comparison with the task’s accuracy requirements. Thus we are able to determine how the human can interact with the robot and improve its performance.
Open Educational Resources: Opportunities and Challenges

Although learning resources are often considered as key intellectual property in a competitive higher education world, more and more institutions and individuals are sharing their digital learning resources over the Internet openly and for free, as Open Educational Resources. The OECD’s OER project asks why this is happening, who is involved and what the most important implications are of this development. In the following paper some preliminary findings are presented.
Patient specific dynamic hand splints produced through Selective Laser Sintering

The ability of Additive Manufacturing (AM) to produce on demand and patient specific medical devices has made it an attractive technology in the medical orthoses and prosthetic environment. Current available dynamic hand splints are not cost effective and have extended manufacturing lead times due to the patient specific and complex nature of the devices. This paper highlights the use of AM to locally manufacture cost effective and accessible patient specific dynamic hand splints. AM design principles such as lattice structures and in process assembly of parts were utilized to produce a dynamic hand splint with improved functionality, allowing for motion in a specific direction while restricting and supporting undesired motion.
Digital Place, Cognitive Space

To what extent does our use of digital devices to capture and process archaeological data affect our perceptions of what was there? Mark Altaweel (2018) has recently asked a similar question in relation to GPS technologies – how do these affect our understanding and experience of place? He suggests that they diminish our sense of place and experiences that we might otherwise have as we navigate according to their recommendations. Certainly, satnavs are notorious for taking our navigational cognitive load upon themselves and consequently leading drivers who are insufficiently aware of their surroundings into undesirable, even dangerous situations. We might think that the human cognitive load that is thereby freed up by such devices ought to be capable of being diverted into more useful, more extensive, areas – we literally have the space to think about bigger and deeper things as a consequence of their application. This kind of argument frequently arises in relation to the value of automation, for instance, and can be seen in the kinds of discussions surrounding the use of structure-from-motion photogrammetric recording on archaeological excavations, for example. But is this supposed release of cognitive space an unalloyed good? Or is this a case of the technologies distancing us from the physicality of the archaeological material and space in front of us?
DYNAMIC ANALYSIS OF INTERACTION BETWEEN VEHICLE WHEEL WITH A METAL PROTUBERANCE AND RAIL

A new mathematical model “Vehicle Track” developed from other mathematical models is used in the research to determine the interaction between the wheel with a metal protuberance and rail. Fourier series are used to mathematically describe the geometry of vehicle wheel with a metal protuberance. Calculations and analysed results, obtained by using the newly developed method, when a wheel defect has a metal protuberance, are presented in this work.
Implementation and field trials of SFN

The single frequency network structure based on terrestrial digital multimedia/ television broadcasting(DMB-T was implemented by synchronizing each signal frame in real time.A mega-frame initialization packet(MIP inserted in the transport stream(TS every mega-frame contains information on the network delay and synchronization stamp.A simple calculation gives the local additional delay which will allow synchronization of all the transmitters in the network.Field trials of the single frequency network validate the feasibility of scheme based on DMB-T.