International research collaboration in Africa: a bibliometric and thematic analysis

It is widely recognised that science in Africa will benefit from international research collaboration (IRC), and therefore studies have been done on IRC in Africa (hereafter: Africa-related IRC research). However, there is no information on the development of Africa-related IRC research, the geographical location of the scientists interested in the topic, the visibility of the literature and the themes researched. This information makes it possible to understand relevant aspects in the context of IRC in Africa, which are useful for identifying IRC strengths, weaknesses and opportunities. It also allows paving the way for future research on this topic. Using discipline–specific terms, bibliometric, and thematic analysis, I collected the literature on Africa-related IRC research indexed in the Web of Science Core Collection (WoS). The results showed that the number of publications on the topic has increased, few African countries have researched the topic, a third of the publications were written exclusively by African scientists, and the topic has high visibility. The panoply of publications revealed that patterns, driving factors, effects, networks, asymmetries, and policies concerning IRC were the main themes researched.

     

Validation of scientific topic models using graph analysis and corpus metadata

Probabilistic topic modeling algorithms like Latent Dirichlet Allocation (LDA) have become powerful tools for the analysis of large collections of documents (such as papers, projects, or funding applications) in science, technology an innovation (STI) policy design and monitoring. However, selecting an appropriate and stable topic model for a specific application (by adjusting the hyperparameters of the algorithm) is not a trivial problem. Common validation metrics like coherence or perplexity, which are focused on the quality of topics, are not a good fit in applications where the quality of the document similarity relations inferred from the topic model is especially relevant. Relying on graph analysis techniques, the aim of our work is to state a new methodology for the selection of hyperparameters which is specifically oriented to optimize the similarity metrics emanating from the topic model. In order to do this, we propose two graph metrics: the first measures the variability of the similarity graphs that result from different runs of the algorithm for a fixed value of the hyperparameters, while the second metric measures the alignment between the graph derived from the LDA model and another obtained using metadata available for the corresponding corpus. Through experiments on various corpora related to STI, it is shown that the proposed metrics provide relevant indicators to select the number of topics and build persistent topic models that are consistent with the metadata. Their use, which can be extended to other topic models beyond LDA, could facilitate the systematic adoption of this kind of techniques in STI policy analysis and design.

     

Modernization of Air Supply Unit for Oxidation Towers Used in Bitumen Production

Chemical and Petroleum Engineering - The hydrodynamics of oxidation towers used for bitumen production were studied using a model tower having transparent walls. Experiments were carried out in two...     

Modeling the Destruction of an Anisotropic Composite Barrier in Interaction with Slender Strikers at an Angle

Journal of Engineering Physics and Thermophysics - A numerical investigation has been made into the interaction of slender (5–20 calibers) steel cylinder strikers with orthotropic compost...     

Magnetically Modified Waste Bark of Aegle marmelos Tree as a Promising Biosorbent for Uranium(VI) Sorption

Radiochemistry - Magnetically modified waste bark of the Aegle marmelos tree was prepared by using green synthesis method and was used in a batch system for U(VI) removal from aqueous solution. The...     

Wall Rock Alteration,Uranium Mineralization,and Potentiality of Uranium and Iron Dissolution from Mineralized Abu Rusheid Gneiss Rock,South Eastern Desert,Egypt

Radiochemistry - Ferrugination, sericitization, desulfitization, chloritization, and kaolinitization of hydrothermal origin are the main wall rock alterations occurring within the NNW shear zones...     

Justification for the Use of Cohen’s Kappa Statistic in Experimental Studies of NLP and Text Mining

Modern metrics for evaluating agreement coefficients between the experimental results and expert opinion are compared, and the possibility of using these metrics in experimental research in automatic text processing by machine learning methods is assessed. The choice of Cohen’s kappa coefficient as a measure of expert opinion agreement in the NLP and Text Mining problems is justified. An example of using Cohen’s kappa coefficient for evaluating the level of agreement between the opinion of an expert and the results of ML classification and the measure of agreement of expert opinions in the alignment of sentences of the Kazakh-Russian parallel corpus is given. Based on this analysis, it is proved that Cohen’s kappa coefficient is one of the best statistical methods for determining the level of agreement in experimental studies due to its ease of use, computing simplicity, and high accuracy of the results.

     

Increasing the photocatalytic and fungicide activities of Ag3PO4 microcrystals under visible-light irradiation

The present study reports for the first time the performance of silver phosphate (Ag₃PO₄) microcrystals as photocatalyst (degradation of Rodamine B-RhB) and antifungal agent (against Candida albicans–C. albicans) under visible-light irradiation (455 nm). Ag₃PO₄ microcrystals were synthesized by a simple co-precipitation (CP) method at room temperature. The structural and electronic properties of the as-synthetized Ag₃PO₄ have been investigated before and after 4 cycles of RhB degradation under visible light using X-ray diffraction (XRD), micro-Raman spectroscopy, UV–Vis spectrophotometer and field emission scanning electron microscopy (FE-SEM) images. The antifungal activity was analyzed in planktonic cells and 48h-biofilm of C. albicans by colony forming units (CFU) counting, confocal laser and FE-SE microscopies. Statistical analysis was carried out using SPSS software. Morphological and structural modifications of Ag₃PO₄ were observed upon recycling. After 4 recycles, the material maintained its photodegradation property; an eightfold increase in the efficiency of Ag₃PO₄ was observed in planktonic cells and a two fold increase in biofilm when irradiated under visible light. Thus, higher antifungal effectiveness against C. albicans was obtained when associated with visible-light irradiation.     

An Efficient Modified Dragonfly Optimization Based MIMO-OFDM for Enhancing QoS in Wireless Multimedia Communication

Wireless Personal Communications - Multiple inputs multiple outputs (MIMO) is a reliable technique which can manage the increased wireless data traffic in the future generation of wireless...     

Personalized web service recommendation through mishmash technique and deep learning model

Multimedia Tools and Applications - Discovering the relevant web services for specific applications in the dynamically changing business world becomes very critical. Researchers have used many...