Miracle-dz/UniFAR-FTUs huggingface dataset:
Nuevas rutas de permeabilidad en Plasmodium falciparum: consideraciones como blanco farmacológico y avances de los potenciales inhibidores

Con base en la persistencia de los casos de malaria, dados por múltiples razones, entre las cuales se encuentra la resistencia de Plasmodium falciparum a los antimálaricos establecidos para su tratamiento, surge la necesidad de encontrar nuevos compuestos antimaláricos frente a otros blancos terapéuticos. En vista de ello, las Nuevas Rutas de Permeabilidad (NPP) han sido un objetivo promisorio y a partir de su descubrimiento, se han realizado diversos estudios enfocados en comprender su mecanismo y los componentes utilizados para el transporte de solutos y otras moléculas a través de la membrana del eritrocito. El objetivo de esta revisión de tema es presentar una recopilación de los estudios más significativos realizados en torno a las NPP. Para ello, se revisó la literatura para conocer el estado del desarrollo de las investigaciones referentes al tema, consultando bases de datos electrónicas y combinando los descriptores o palabras clave: (NPP AND malaria, AND Plasmodium falciparum AND inhibitors), además, se realizaron búsquedas secundarias en las listas de referencias bibliográficas de los artículos identificados. Luego de revisar los artículos de la literatura publicados entre los años 1980 y 2019, se concluye que muchos estudios han sido dedicados a la búsqueda de inhibidores de esta vía con fines terapéuticos y hay gran cantidad de moléculas candidatas como el híbrido MA-DFO y las diaminidas que han mostrado actividad en modelos de malaria tanto in vitro como in vivo.
Passivity-Oriented Design of LCL-Type Grid-Connected Inverters With Luenberger Observer-Based Active Damping

The frequency-domain passivity theory offers an effective way to assess the stability of inverters in a complex grid. In this article, a unified impedance model, suitable for either inverter current control (ICC) or grid current control (GCC) of <italic>LCL</italic>-type grid-connected inverters with observer-based capacitor current feedback active damping, is built to facilitate the passivity-based stability assessment and controller parameter design. With the passivity analysis, it is found that when the antiresonant frequency of <italic>LCL</italic> filter is in certain ranges, i.e., (0.056<inline-formula><tex-math notation="LaTeX">$\omega _s$</tex-math></inline-formula>, 0.20<inline-formula><tex-math notation="LaTeX">$\omega _s$</tex-math></inline-formula>) for ICC and (0.046<inline-formula><tex-math notation="LaTeX">$\omega _s$</tex-math></inline-formula>, 0.23<inline-formula><tex-math notation="LaTeX">$\omega _s$</tex-math></inline-formula>) for GCC, all frequencies’ passive output admittance of the inverter can be achieved via proposed parameter design guidelines. Due to the utilization of the observer and all frequencies’ passive output admittance property, not only extra current sensors for active damping can be saved, but also the inverter can be connected and stably operated in a grid regardless of the grid impedance. The validity of the theoretical analysis and effectiveness of the proposed method are verified by using experimental results on a laboratory prototype.
Cytotec – es wird bitter fehlen!

Das Mittel Cytotec wird in Deutschland nicht mehr vertrieben. Darauf haben sich das Bundesinstitut für Arzneimittel und Medizinprodukte (BfArM) sowie die Arzneimittel importierenden Unternehmen geeinigt. Hintergrund waren Berichte über schwere Nebenwirkungen bei der Geburtseinleitung mit Cytotec. Das Medikament werde bitter fehlen, schreibt Hebamme Kareen Dannhauer und begründet, warum es wichtig ist, über den Tellerrand des Kreißsaals hinauszuschauen. Ein Beitrag zur aktuellen Diskussion.
Learning Dynamic Systems Using Gaussian Process Regression with Analytic Ordinary Differential Equations as Prior Information

SUMMARY Recently the data-driven learning of dynamic systems has become a promising approach because no physical knowledge is needed. Pure machine learning approaches such as Gaussian process regression (GPR) learns a dynamic model from data, with all physical knowledge about the system discarded. This goes from one extreme, namely meth-ods based on optimizing parametric physical models derived from physical laws, to the other. GPR has high ﬂexibility and is able to model any dynamics as long as they are locally smooth, but can not generalize well to unexplored areas with little or no training data. The analytic physical model derived under assumptions is an abstract approximation of the true system, but has global generalization ability. Hence the optimal learning strategy is to combine GPR with the analytic physical model. This paper proposes a method to learn dynamic systems using GPR with analytic ordinary di ﬀ er-ential equations (ODEs) as prior information. The one-time-step integration of analytic ODEs is used as the mean function of the Gaussian process prior. The total parameters to be trained include physical parameters of analytic ODEs and parameters of GPR. A novel method is proposed to simultaneously learn all parameters, which is realized by the fully Bayesian GPR and more promising to learn an optimal model. The standard Gaussian process regression, the ODE method and the existing method in the literature are chosen as baselines to verify the beneﬁt of the proposed method. The predictive performance is evaluated by both one-time-step prediction and long-term prediction. By simulation of the cart-pole system, it is demonstrated that the proposed method has better predictive performances.
Determinants of Active Online Learning in the Smart Learning Environment: An Empirical Study with PLS-SEM

A smart learning environment, featuring personalization, real-time feedback, and intelligent interaction, provides the primary conditions for actively participating in online education. Identifying the factors that influence active online learning in a smart learning environment is critical for proposing targeted improvement strategies and enhancing their active online learning effectiveness. This study constructs the research framework of active online learning with theories of learning satisfaction, the Technology Acceptance Model (TAM), and a smart learning environment. We hypothesize that the following factors will influence active online learning: Typical characteristics of a smart learning environment, perceived usefulness and ease of use, social isolation, learning expectations, and complaints. A total of 528 valid questionnaires were collected through online platforms. The partial least squares structural equation modeling (PLS-SEM) analysis using SmartPLS 3 found that: (1) The personalization, intelligent interaction, and real-time feedback of the smart learning environment all have a positive impact on active online learning; (2) the perceived ease of use and perceived usefulness in the technology acceptance model (TAM) positively affect active online learning; (3) innovatively discovered some new variables that affect active online learning: Learning expectations positively impact active online learning, while learning complaints and social isolation negatively affect active online learning. Based on the results, this study proposes the online smart teaching model and discusses how to promote active online learning in a smart environment.
A Fast Discrete Two-Step Learning Hashing for Scalable Cross-Modal Retrieval

Recently, some cross-modal hashing methods are proposed to search data for different modality effectively. Hashing has received wide attention because of its low storage and high efﬁ-ciency. Hashing-based methods project the data instances from different modalities into a Hamming space to learn hash codes for retrieval between different modality. Although obtaining promising performance, hashing-based methods have still several common limitations. First, they learn the hash codes by constructing semantic similarity matrices, resulting in the loss of information. Second, most existing methods simultaneously learn the hash codes and the hash functions, which bring a high computational complexity. Third, they utilize the relaxation-based optimization strategy to generate the hash codes which leads to the large quantization error of the hash codes. To solve the above problems, we propose a novel fast supervised hashing method, termed Fast Discrete Two-Step Learning Hashing (FDTLH) for scalable cross-modal retrieval, which learns the discriminative hash codes by adopting a effective two-step learning scheme. Extensive experiments show that the FDTLH outperforms several state-of-the-art hashing methods in terms of retrieval performance and learning efﬁciency.
NEXT GENERATION SEQUENCING TECHNOLOGIES TOWARDS EXPLORATION OF MEDICINAL PLANTS

With the ever-increasing population, the plant cover is decreasing at an alarming rate. The medicinal plants are most affected by this because they are present in the last tier of cultivation. Let it be pharmaceutical companies or people using it for herbalism, medicinal plants have been exploited without getting a chance to flourish in their natural environment. Modern biotechnology acts as a bridge between the cultivation and utilization of medicinal plants. Next Generation Sequencing (NGS) technology which is a decade old but emerging field helps to unveil the importance of medicinal plants. Thus, it paves the way for sustenance of medicinal plants by molecular breeding, micropropagation, large-scale tissue culture, and other methods to conserve the plants with great medicinal value. Various NGS technologies can be found in the market like Ilumina, PacBio, Ion Torrent, and others. The present review will summarize the NGS technologies and their potential use to study the genomes, transcriptome, epigenome, and interactome of medicinal plants towards the identification of bioactive compounds.
Statistical Analysis of Amir Schoor’s Algorithm in Sequential and Parallel Environment

Matrix multiplication is an essential constituent of most of the computer models and systems implementing Numerical Algorithms, Signal and image processing, Graph theory, Digital control. So reduction of multiplication time can influence drastically the overall system performance. This paper gives a statistical analysis of average time complexity for matrix multiplication with two dense square matrices of order ‘n’ and achieves an empirical O emp (n 2 ) complexity in sequential and O emp (n) complexity in parallel computing environment with Amir Schoor’s Algorithm using different probability distributions characterizing the matrix elements. Amir Schoor’s algorithm, although initially developed for sparse matrices, also performs well for dense matrices for two reasons. First, it is faster to work with rows only (as in Schoor’s algorithm) than to work with both rows and columns (as in classical matrix multiplication). Secondly, as we have shown, the n 2 comparisons turn out to be “heavier” (in terms of weight, with time of an operation being considered as its weight) than the O(d 1 d 2 n 3 ) multiplications on the average, wherein lies the concept of a weight based statistical bound whose empirical estimate over a finite feasible range is empirical O emp (n 2 ) in our case. Here d 1 and d 2 are the densities of the pre and post factor matrices.
Exhumation of the Ronda Peridotite During Hyper‐Extension: New Structural and Thermal Constraints From the Nieves Unit (Western Betic Cordillera, Spain)

The Ronda peridotite (Betic Cordillera, Southern Spain) is the largest alpine‐type peridotite massif worldwide. Yet, the emplacement mechanism of these mantle rocks is still a highly debated topic. In this study, we aim at better constraining their context of exhumation by focusing on the Nieves Unit, which is mostly composed of Mesozoic metasediments displaying HT metamorphism and deformation along the contact with peridotite. The topmost parts of the peridotites and the bottom parts of the Nieves Unit share the same planar/linear fabric parallel to the contact accompanied by component of sinistral kinematic indicators. Raman Spectroscopy on Carbonaceous Material geothermometry then shows a contraction of peak‐temperature conditions within metasediments of the Nieves Unit, as well as a north‐eastward decrease along strike, highlighting a strong thinning of the unit and a significant obliquity of the isograds to the contact with the peridotites. Local magnetite ores and ophicalcite bodies are finally observed nearby the contact, suggesting a hyper‐extension context for the mantle exhumation. Indeed, the Nieves Unit, the Ronda peridotite and the Jubrique Unit, where a strong thinning has also been documented, are all in contact at a triple junction between the western contact of the peridotite and the Nieves/Jubrique contact. Altogether, these features support the idea that the western shear zone limiting the peridotites from the Nieves and Jubrique units is a tilted large‐scale extensional detachment that has exhumed mantle rocks from beneath the continental basement (Jubrique Unit) and its Mesozoic cover (Nieves Unit) during an episode of hyper‐extension.
IMPACT OF MACHINE TRANSLATION ON UNIVERSITY STUDENTS’ TRANSLATION ABILITY: SOUTH EASTERN UNIVERSITY OF SRI LANKA AS A MODEL

Machine Translation (MT) is a unique tool in the field of translation. It is used all over the world. In accordance with, the undergraduates who are following Specialization in Linguistics and Translation at the department of Arabic language from South Eastern University of Sri Lanka face obstacles when they translate between Tamil, English & Arabic. Due to, they focus on MT to translate. According to this, the current research aims to identify the impact of MT on their translation activities. This research uses the descriptive analysis methodology. Primary data were collected from observation and questionnaire that was given to the undergraduates who are following Specialization in Linguistics and Translation at the department of Arabic language from South Eastern University of Sri Lanka in the academic year 2018/2019. Secondary data were gathered from research papers, books, research articles, and websites. The findings of this research declares that the undergraduates in the selected area have desires in the translation field and face the obstacles when translating. Thus, they try to use MT for getting accurate translation, idea of the source text, understanding the unknown words. Due to it, they couldn’t omit the MT in their translation activities. Because, it is easy to use and helps to save the time. At the time, they assume that non-use of MT will effect negatively in their translation ability.
TaxoTracker: A collaborative platform for taxonomic resource maintenance

Taxonomy is foundational to all biological sciences. Names allow us to organize and communicate information about biological groups. This process is critical for understanding and preserving the biodiversity of our planet. There are an estimated 8.7 million extant eukaryotes (Mora et al. 2011) and possibly as many as 1 trillion microbial species (Locey and Lennon 2016), with untold numbers of extinct taxa yet to be discovered in the fossil record. Accounting for all these taxa and maintaining their nomenclatural resources is one of the great challenges in biology. A few major hurdles in overcoming this challenge are the inability to find, share, and update taxonomic resources efficiently in real time. Efforts to standardize and continually update taxonomic names in a sustainable way have been limited. The problem is complex, and solutions must deal with the large backlog of names, a constant stream of new names, the confusing merging and splitting of taxonomic synonyms, the subjective nature of taxonomic concepts, and the fundamental limitations on available expertise and curators' time to prepare and maintain such resources. Hyperdiverse groups such as arthropods are especially challenging as there are relatively few experts on any given lineage and changes in taxonomy can be rapid as new species are continually being discovered and described. After struggling to wrangle taxonomic resources in support of specimen digitization efforts, I began development of TaxoTracker as a proof-of-concept, web-based platform for facilitating expert curation and dissemination of biological taxonomies. TaxoTracker is still in development, but its current and planned functionalities will be shown through a combination of demonstration and discussion. TaxoTracker identifies and implements features that attempt to simplify the production and maintenance of expert-curated resources, while also limiting the responsibilities that are placed on individual experts who are often already overburdened and underfunded. These features include: Centralized, searchable, and easily obtained resources in useful formats Community-driven, citation-based curatorial suggestions Expert-reviewed curatorial recommendations Consensus-driven curatorial decisions Effort tracking and credit for suggestions and reviews Centralized, searchable, and easily obtained resources in useful formats Community-driven, citation-based curatorial suggestions Expert-reviewed curatorial recommendations Consensus-driven curatorial decisions Effort tracking and credit for suggestions and reviews
Review on Connecting the Complex Dots of Environmental Problems in Greater Accra Metropolitan Area (GAMA) of Ghana

For years, Accra has been facing huge environmental challenges. Efficient policy frameworks coupled with prudent urban management are deemed as reasonable balance to environmental benefits. Research reveals urban areas in Ghana are confronted with the rapid loss of natural resources as urbanization increases. This synthesis report examines the ramifications of major issues faced by the Greater Accra region based on existing literature by (i) highlighting contemporary environmental problems in Accra (ii) probing into human-induced and natural factors that alterate environmental harmony in the study area (iii) discussing measures on safeguarding the environment through a sustainable approach in Accra, and (iv) presenting policy implications of environmental problems in Accra. Findings indicated urbanization, poverty and inappropriate urban planning systems influence environmental degradation in the study domain. Anthropogenic activities such as pollution and natural hazards like: flooding, drought and windstorms events have altered the physical properties of Accra. This paper reveals the assumption and execution of values to safeguard environmental resources in the Greater Accra Metropolitan Area.
Strategic Process of Recovery and Development of the Romanian Economy

The sequence of rapid transformations from a material resource-based society to a society based on intelligence and creativity demonstrates the need to accept, integrate and implement knowledge-based management in any organization, regardless of its status. Major changes, both globally and nationally, oblige us to reflect carefully on the diversity of requirements and to identify the best strategies for the recovery of the Romanian economy. A critical assessment of the situation of Romanian organizations in all fields of activity, compared to changes at international level, will lead to the approach of new strategies and rapid measures for the recovery and development of the economy, with a view to maintaining the pace of competitiveness, with the major players in the international market. Change and economic evolution mean intelligence, information and creativity. The external environment is a competitive, and in need of survival. It depends on the social, legal, economic evolution, the technologies and services used, but also on the adaptation to evolutionary changes in order to resist the competitive market. We must be aware, however, that each country has its peculiarities, and I am referring here to the mentality, customs, but also to the relief, demographic state, national and human resources that Romania has. We're looking to keep up to date with the new research on the respective domain. The research of the literature, in order to identify the most effective and affordable strategies for the recovery of the Romanian economy, are extremely beneficial, but we must have the capacity to adapt them to the existing reality both nationally and globally.
Unsupervised Bayesian Adaptation of PLDA for Speaker Verification

This paper presents a Bayesian framework for unsupervised domain adaptation of Probabilistic Linear Discriminant Analysis (PLDA). By interpreting class labels as latent random variables, Variational Bayes (VB) is used to derive a maximum a posterior (MAP) solution of the adapted PLDA model when labels are missing, referred to as VB-MAP. The VB solution iteratively infers class labels and updates PLDA hyperparameters, offering a systematic framework for dealing with unlabeled data. While presented as a general solution, this paper includes experimental results for domain adaptation in speaker veriﬁcation. VB-MAP estimation is applied to the 2016 and 2018 NIST Speaker Recognition Evaluations (SREs), both of which included small and unlabeled in-domain data sets, and is shown to provide performance improvements over a variety of state-of-the-art domain adaptation methods. Additionally, VB-MAP estimation is used to train a fully unsupervised PLDA model, suffering only minor performance degradation relative to conventional supervised training, offering promise for training PLDA models when no relevant labeled data exists.
Financial Performance as a Mediator of Risk Management on Organizational Performance

Sharia Bank is a bank that conducts business activities based on sharia principles, or Islamic legal principles stipulated in the fatwa of the MUI such as the principles of justice and balance, benefit, universalism. This study aims to examine the effect of risk management represented by Capital Adequacy Ratio (CAR), Operational Efficiency (BOPO), and Nonperforming Loans (NPL), on organizational performance by mediating financial performance that is represented by Return on Assets (ROA) on Sharia Banking Companies recorded in IDX from 2013 up to 2017. The data used in this study were obtained from their Financial Statements. After passing the purposive sample stage, six Islamic Banking companies recorded in IDX were eligible for use. The results of the study show that risk management influences organizational performance, while financial performance does not mediate the effect of risk management on organizational performance. Thus, Sharia banking operations must be adjusted to sharia principles and the bank is expected to pay more attention to the efficiency of the operations to improve risk management. Companies must think about the benefits and risks of lending funds to other parties so that the company value remains optimal.