Miracle-dz/UniFAR-FTUs huggingface dataset:
Functional characterization of three ABC1-like kinases found in the plastoglobule proteome

Background: Prenylquinones are key compounds of the thylakoid membranes in chloroplasts. To understand the mechanisms involved in the response of plants to changing conditions such as high light intensity, the comprehensive analysis of these apolar lipids is an essential but challenging step. Conventional methods are based on liquid chromatography coupled to ultraviolet and fluorescence detection of a single or limited number of prenylquinones at a time. Here we present an original and rapid approach using ultra-high pressure liquid chromatography-atmospheric pressure chemical ionization-quadrupole time-of-flight mass spectrometry (UHPLCAPCI-QTOFMS) for the simultaneous profiling of eleven prenylquinones in plant tissues, including a-tocopherol, phylloquinone, plastochromanol-8 and plastoquinone-9. Results and discussion: Mass spectrometry and chromatography parameters were optimized using pure standards. Sample preparation time was kept to minimum and different extraction solvents were evaluated for yield, ability to maintain the redox state of prenylquinones, and compatibility with chromatography. In addition to precise absolute quantification of 5 prenyllipids for which standards were available, relative quantification of 6 other related compounds was possible thanks to the high identification power of QTOFMS. Prenylquinone levels were measured in leaves of Arabidopsis grown under normal and high light intensities. Quantitatively, the obtained results were consistent with those reported in various previous studies, demonstrating that this new method can profile the full range of prenylquinones in a very short time. Conclusion: The new profiling method proves faster, more sensitive and can detect more prenylquinones than current methods based on measurements of selected compounds. It enables the extraction and analysis of twelve samples in only 1.5 h and may be applied to other plant species or cultivars.
The Price of Football

The first edition of The Price of Football quickly established itself as the go-to guide to understanding football club finance for the serious fan. Kieran Maguire, one of the UK's top football finance analysts, shows how professional clubs operate as businesses and explains, in non-technical language, how to read, understand and interrogate club accounts.As a clear-headed analysis and presentation of the financial imperatives and challenges facing football clubs across the English and Scottish Leagues, it has become a welcome resource not only for students of the industry, but by a wider constituency of supporters looking to understand their club's latest transfer deal, or season ticket price.This fully revised and updated edition includes analysis of the most recent club accounts, the latest legal rulings on club affairs, as well as the impact of Covid-19 on the game's finances.
INTERDISCIPLINARY TAKE ON FOOD CONSUMPTION

The main aim of this paper is to present economic and social aspects of food consumption studies. At the beginning, consumption is located among other sciences. Then, the methods used to study food consumption is presented, with particular attention paid to the method of econometric analysis and panel analysis. The last part of the paper presents the current state of studies in this area.
Novel aspects of quorum quenching in the rhizosphere : a tool to develop biocontrol strategies against plant pathogens

La regulation Quorum-sensing (QS) couple l'expression genique chez les bacteries, a la densite cellulaire par l'intermediaire des molecules signal, dont les plus courantes sont les N-acyl homoserine lactones (NAHLs). L'analyse d'un metagenome bacterien de sol a permis l'identification d'un clone et d'un gene, qlcA codant une enzyme de 24kD de type NAHL lactonase a large spectre, definissant une nouvelle classe de ces lactonases. L'analyse bioinformatique du clone revele l'existence de 20 orfs. Un cluster d'organisation inconnue chez les bacteries, compose de 9 orfs (argFJADBCRGH), est implique dans la synthese de l'arginine. Neuf des proteines putatives codees par les 20 orfs sont orthologues a des proteines d'Acidobacteries (communes dans les sols, pour la plupart non cultivables) suggerant une telle origine pour le clone. Une souche sauvage de Pectobacterium carotovorum exprimant qlcA ne peut plus infecter les tubercules de pomme de terre, demontrant l'interet de l'approche metagenomique pour identifier des genes d'interet agronomique. Les bacteries issues d'environnements naturels capables de degrader l'ester methylique du 3-hydroxy palmitate (3-OH PAME), le signal QS de Ralstonia solanacearum, ont ete identifiees par enrichissement sur des analogues du 3-OH PAME. Co-inoculees aux vegetaux avec R. Solanacearum, certaines de ces souches ralentissent la progression de la maladie et diminuent sa gravite. Les souches les plus efficaces appartiennent aux genres et especes Acinetobacter sp. , Chryseobacterium daejeonense, Pseudomonas sp. , et Delftia spp. Ces travaux valident l'interet agronomique de strategie d'interference avec le QS, pour des signaux autres que les NAHLs.
Development of Path Planning Algorithm Using Probabilistic Roadmap Based on Ant Colony Optimization

Path Planning, Probabilistic Roadmap (PRM), Ant colony optimization, B-spline curve. In this paper, a unique combination among probabilistic roadmap, ant colony optimization, and third order B-spline curve has been proposed to solve path-planning problem in complex and very complex environments. This proposed method can be divided into three stages. First stage is to construct a random map depending on the environment complexity using probabilistic roadmap algorithm. This could be done by sampling N nodes randomly in complex and very complex static environments, then connecting these nodes together according to some criteria or conditions. The constructed roadmap contains huge number of possible random paths that may connect the start and the goal points together. Second stage includes finding path within the pre-constructed roadmap. Ant colony optimization is selected to find or to search the best path between start and goal points. Finally, the third stage uses B-spline curve to smooth and reduce total length of the found path in the previous stage where path’s length has been reduced by 1% in first environment and by 15% in second environment. The results of the proposed approach ensure feasible path between start and goal points in complex and very complex environment. In addition, the path is guaranteed to be shortest, smooth, continues and safe. How to cite this article: M. I. Abdulakareem and F. A. Raheem, “Development of path planning algorithm using probabilistic roadmap based on ant colony optimization,” Engineering and Technology Journal, Vol. 38, Part A, No. 03, pp. 343-351, 2020. DOI: https://doi.org/10.30684/etj.v38i3A. 389
Precedent Behavioral Extraction System For Personalization Recommendation

: Hosting a compilation of billions of videos, YouTube presents one of the leading scale and most precious videos personalization recommendation system in existence. The recommendation system works on to personalized set of videos to users based on their past actions on the website. In this paper, we highlight the some of the major challenges that the system faces and how to address them. To tackle these issues, we have proposed a Precedent Behavioral Extraction Module (PBEM), which also deals with large-scale heterogeneous information to fulfill the requirements of the potential users. PBEM approach especially focus on the remarkable performance enhancements brought by machine learning. PBEM is a new approach as it works on discovering the precise web browsing behavior from uncertain keywords and defines the semantic measurement with user recommendation of keywords within the user query
MARPL: A crosslayer approach for Internet of things based on neighbor variability for mobility support in RPL

Internet of things (IoT) proposes the use of devices with low energy capacity, processing, and memory power for a range of applications such as environmental monitoring and smart health. Such devices usually have sensing and wireless communication capabilities. Low power and lossy networks on mobile devices are a common type of wireless network in IoT applications. This article proposes the mobility aware RPL (MARPL), which is an extension of the IPv6 routing protocol for low‐power and lossy network (RPL) in order to enhance its performance in networks with mobile nodes. The mobility of nodes increases packet loss in the canonical RPL protocol. The MARPL mobility mechanism adopts a crosslayer approach. The network layer uses signal strength measurements from the media access layer to calculate a node's variability neighborhood. Performance evaluation results obtained by the Cooja simulator confirm the effectiveness of MARPL regarding link disconnection prevention, packet delivery rate, low overhead, and energy consumption when compared with other protocols.
Identificação das áreas de pesquisa no IFTM usando técnica de agrupamento

Este artigo propoe a analise de frequencia de palavras-chave de resumos publicados no Seminario de Iniciacao Cientifica (SIN) do Instituto Federal do Triangulo Mineiro (IFTM) para diagnosticar as areas de pesquisa atuantes na instituicao e em seus campi . Este artigo tambem tem como objetivo o agrupamento de docentes para facilitar possiveis pesquisas em conjunto. Como instrumento de coleta, utilizou-se 370 resumos do SIN 2017. O agrupamento foi realizado com E xpectation Maximization e K-means. Os resultados mostraram que a iniciacao cientifica do IFTM contempla 298 palavras-chave e que alguns docentes de campi distintos possuem areas de pesquisa em comum.
Beyond Borders: Governmental Fragmentation and the Political Market for Growth in American Cities

Political fragmentation has been conceptualized as a phenomenon which increases competition for mobile citizens and jobs between local governments within the same region. However, the empirical basis for this nexus between governmental fragmentation and increased competition for development is surprisingly lacking. Utilizing a newly constructed database that matches political fragmentation indices (horizontal, vertical, and bordered) to a nationwide survey of economic development officials in 2014, we begin to fill this gap by analyzing the influence fragmentation has on the use of tax incentives, regulatory flexibility, and community development tools in U.S. cities. Applying the political market framework and a Bayesian inferential approach, we find that the proliferation of local governments increases incentive use. However, more specialized governance increases the probability of using community development activities.
Dynamic Modelling of 3-RUS Spatial Parallel Robot Manipulator

Parallel manipulators are characterized as having closed-loop kinematic chains. Parallel robots have received increasing attention due to their inherent advantages over conventional serial mechanism, such as high rigidity, high load capacity, high velocity, and high precision. A definite advantage of parallel robots is the fact that, in most cases, actuators can be placed on the truss, thus achieving a limited weight for the moving parts, which makes it possible for parallel robots to move at a high speed. These advantages avoid the drawbacks on serial ones and make the mobile platforms of the parallel manipulators carry out higher performances. Therefore, parallel manipulators have been applied to the industrial manufacturing, flight simulation, medical resuscitation, and so on. The basis for model-based control of parallel manipulators is an efficient formulation of the motion equations. In this paper a formulation of the motion equations in redundant coordinates is presented for parallel manipulators. The fully coupled non-linear equations of motion of 3-RUS spatial parallel manipulator having 3 DOF with Revolute-Universal-Spherical joints are obtained by using the Lagrange equations with multipliers for constrained multibody systems.
The Crustacean stomatogastric system : a model for the study of central nervous systems

A power forging press in which a press stand is provided with a drive having a flywheel, a spindle and a drive device, and a workpiece support. A ram is mounted for relative movement with respect to the workpiece support and a wedge is housed in the press stand and acts on the ram, with the flywheel-spindle drive being arranged with the axis of the flywheel and its spindle extending transversely to the direction of movement of the ram, the spindle and wedge being operably connected.
Towards Building A Neural Conversation Chatbot Through Seq2Seq Model

: Improvements in computation and processing power paved a way for Machine learning to be applied more efficiently in real-time and in a lot of applications. In which most prominent area is Natural Language Processing and Natural Language Understanding, which helps the computer to process and understands the natural language used by people. Thanks to deep learning models and architectures which made this process of making the system process and understand natural language, which makes the system more intelligent. Chatting agent’s AKA-Chatbot is one of the major use cases of Natural Language Processing and Natural Language Understanding, which can be used in different domains to engage customers and provide a response to customer’s queries. Though many chatbots use a retrieval-based model with the recent advancement of Deep Learning, we in this work use Neural Networks to train a chat model with a question and answer datasets that make models understand the patterns in it and behave intelligently. Here we build a domain-specific generative chatbot using Neural Networks to train a conversational Model which reads the pattern of data and reply answer when a new question is asked. Finally, we conclude by validating how relevant the response generated by the model to test data or test question and provide a further area of improvements to make the system more efficient and intelligent.
Carbohydrate Building Blocks

The Raw Materials. Carbohydrate Acetal Derivatives. Other Selectively Protected Sugars. Oxidation Products: Aldonic Acids and Lactones. Reduction Products: Carbohydrate Polyols. 1,6--Anhydro sugars. Unsaturated Sugars. Products of Base Treatment. Products of Acid Treatment. Disaccharides. Miscellaneous Carbohydrate Products. Compendium of Building Blocks. Indexes.
Synthetic Data Generation Through Statistical Explosion: Improving Classification Accuracy of Coronary Artery Disease Using PPG

Synthetic data generation has recently emerged as a substitution technique for handling the problem of bulk data needed in training machine learning algorithms. Healthcare, primarily cardiovascular domain is a major area where synthetic physiological data can be used improve accuracy of machine learning algorithm. This paper presents a novel approach of generating synthetic Photoplethysmogram (PPG) data using statistical explosion. Synthetic data is subsequently used to classify Coronary Artery Disease (CAD) using a two stage cascaded classifier. Proposed classifier along with synthetic data removes class bias and provides better accuracy compared to state of art. The proposed data generation and cascaded classifier is generic enough to be used to improve machine learning algorithm on any time series signal.
Role of food and nutrition and prevention in pathogenesis of the arterial occlusive disease

Admission Atherosclerosis is a chronic inflammatory disease of complex etiopathogenesis. Improper diet, genetic predisposition, lack of physical activity, and smoking are just a few of the major factors contributing to the development of atherosclerotic plaque. Diet in atherosclerosis, treatment is based. Antiatherosclerotic diet is one of many components, which should provide not only the treatment of such a state, but primarily prevention. Accordingly, balanced nutrition regimen can reduce cholesterol synthesis in the liver, which contributes to the development of atherosclerosis. Limiting the intake of trans fatty acids and saturated fatty acids allows for inhibiting the development of atherosclerotic plaque. Aim The aim of the study is to analyze the role of food and nutrition in the prevention and pathogenesis of atherosclerosis of the lower extremities. Material and methods A review of available literature. Results Adequate intake of potassium in the diet contributes significantly to reducing the risk of atherosclerosis and hypertension. Potassium determines many important functions in the body. Due to the fact that the monounsaturated fatty acids reduce LDL cholesterol levels, the proportion should be in the diet increased to 15% and for the secondary prevention of up to 20%. In the prevention of atherosclerosis is very important to maintain an appropriate ratio of omega-6 to omega-3 ratio is absolutely should be no more than 4. It is extremely important in the diet because distorted value for the benefit of omega-6 favors the formation of atherosclerotic lesions. respective supply of carbohydrates also has a huge impact on the development of atherosclerotic lesions. The recommended amount of a ntiatherosclerotic dietary up to 60% provided that the people do not apply to such ailments as hypertension, overweight or obesity, elevated fasting blood sugar levels, decreased HDL cholesterol and elevated triglycerides. Conclusions General nutritional recommendations play the role of a signpost, which you should use expecting to improve health. It should be noted, however, that is not all. Nutritional prevention is significant, but equally important is lifestyle modification. Atherosclerotic diet is an important part of the treatment of the disease and prevent further growth of atherosclerotic plaque. Atherosclerosis requires the use of low-fat diet that is necessary to beat high blood cholesterol levels.
Women’s Participation in Informal Peace Processes

Women’s greater presence in informal peace processes is often noted in works on peace processes, but there has been little systematic evidence about this involvement. This article is the first systematic study of women’s participation in informal peace processes. We find that women are a significant presence in civil society efforts to forge peace outside formal negotiation rooms: nearly three-fourths of identifiable informal peace processes have clear evidence of involvement from women’s groups. This research indicates that women advocate to be included in formal peace processes, work to legitimate formal negotiations and organize for peace, advocate for the inclusion of women’s rights issues in the final peace agreement, provide information on human rights violations to participants in the formal peace process, engage in local conflict resolution, and advocate as partisans for one or another side in the conflict.
DNN-Based Speech Presence Probability Estimation for Multi-Frame Single-Microphone Speech Enhancement

Multi-frame approaches for single-microphone speech enhancement, e.g., the multi-frame minimum-power-distortionless-response (MFMPDR) filter, are able to exploit speech correlations across neighboring time frames. In contrast to single-frame approaches such as the Wiener gain, it has been shown that multi-frame approaches achieve a substantial noise reduction with hardly any speech distortion, provided that an accurate estimate of the correlation matrices and especially the speech interframe correlation (IFC) vector is available. Typical estimation procedures of the IFC vector require an estimate of the speech presence probability (SPP) in each time-frequency (TF) bin. In this paper, we propose to use a bi-directional long short-term memory deep neural network (DNN) to estimate the SPP for each TF bin. Aiming at achieving a robust performance, the DNN is trained for various noise types and within a large signal-to-noise-ratio range. Experimental results show that the MFMPDR in combination with the proposed data-driven SPP estimator yields an increased speech quality compared to a state-of-the-art model-based SPP estimator. Furthermore, it is confirmed that exploiting interframe correlations in the MFMPDR is beneficial when compared to the Wiener gain especially in adverse scenarios.
Generating and Protecting Against Adversarial Attacks for Deep Speech-Based Emotion Recognition Models

The development of deep learning models for speech emotion recognition has become a popular area of research. Adversarially generated data can cause false predictions, and in an endeavor to ensure model robustness, defense methods against such attacks should be addressed. With this in mind, in this study, we aim to train deep models to defending against non-targeted white-box adversarial attacks. Adversarial data is first generated from the real data using the fast gradient sign method. Then in the research field of speech emotion recognition, adversarial-based training is employed as a method for protecting against adversarial attack. We then train deep convolutional models with both real and adversarial data, and compare the performances of two adversarial training procedures - namely, vanilla adversarial training, and similarity-based adversarial training. In our experiments, through the use of adversarial data augmentation, both of the considered adversarial training procedures can improve the performance when validated on the real data. Additionally, the similarity-based adversarial training learns a more robust model when working with adversarial data. Finally, the considered VGG-16 model performs the best across all models, for both real and generated data.
Caracterização genotípica de amaostras de Toxoplasma gondii isoladas de ovinos de abatedouro

Toxoplasma gondii is a parasite with high importance to the animal production and public health, being important opportunistic pathogen in immunocompromised patients. This study was aimed to determine the seroprevalence of toxoplasmosis in ovines in slaughterhouses from State of de São Paulo, and the genotypic variability of the obtained isolates. T. gondii antibodies were researched in 602 serum samples by indirect fluorescent antibody test (IFAT) and modified agglutination test (MAT), with methanol(AM) and formalin-fixed antigen (AF). Bioassay in mice and the research of DNA by polymerase chain reaction (PCR) of gene 529 base pairs (bp), 300 times repetitive in parasite genome, was assayed with brain, lung and muscle (“pool” of diaphragm and heart) from seropositive ovines. Genotyping of the PCR positive samples was performed by multilocus-, nested-PCR and restriction fragment lenght polymorphism (RFLP-PCR) in 12 loci (SAG1, 5’SAG2, 3’SAG2, alt-SAG2, SAG3, BTUB, GRA6, c22-8, c29-2, L358, PK1, Apico and CS3), added of ROP18Del and ROP18UPS, beyond the confirmation by 18S rRNA locus, to differentiate Hammondia hammondi, Neospora caninum, Sarcocystis neurona, S. moulei, S. miescheriana, S. hominis, S. capracanis and S. tenella. 66/602 (11.0%) serum samples were positive to, at least, one serological test with high sensitivity to MAT-AF, used as screening test. Tissue samples of 20/66 (30.3%) animals were positive to the isolation, being detected cysts in 12, tachyzoites in four and in other four only positive result to the serology. DNA of the parasite was detected in samples of 22/66 (33.3%) animals. The complete genotype was detected in only 13/22 (59.1%). Ten different genotypes were identified, with six new genotypes. Two samples presented type II, isolated from Polwarth (Ideal) breed, bred extensively in Santana do Livramento and Uruguaiana, RS. Two other samples, from the same cities, presented coinfection with Sarcocystis tenella, detected by sequencing of nested-PCR