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Financial literacy has been widely discussed in various countries with a wide range of subject areas, focuses, and loci. The purpose of this paper is to map the trends of scientific publications and map the network of authors on financial literacy, especially in the MSME sector. We have developed bibliometric analysis through VOSviewer software, supplemented by literature reviews. A total of 126 articles were obtained from Scopus related to the topics "financial literacy" and "micro small medium enterprise". We present trends in financial literacy research, author productivity, and journals, as well as detailing the network of co-authorships who have researched and published in the scientific domain. The results of the study are known that 1) The application of financial literacy in MSMEs only appeared in 2010 and experienced a significant upward trend. 2) Penulis most productive comes from china, where there are 2 authors each produce 3 articles. 3) Co-authorship has not been established between writers in each country and between countries. 4) Indonesia contributes financial literacy publications in MSMEs the most compared to other countries, with the number of publications as many as 34 articles. Lastly, the mapping provides an overview of which countries and writers are concentric and collaborate with each other on the topic of financial literacy in MSMEs.

Quantitative systems pharmacology (QSP) has been proposed as a scientific domain that can enable efficient and informative drug development. During the past several years, there has been a notable increase in the number of regulatory submissions that contain QSP, including Investigational New Drug Applications (INDs), New Drug Applications (NDAs), and Biologics License Applications (BLAs) to the US Food and Drug Administration. However, there has been no comprehensive characterization of the nature of these regulatory submissions regarding model details and intended applications. To address this gap, a landscape analysis of all the QSP submissions as of December 2020 was conducted. This report summarizes the (1) yearly trend of submissions, (2) proportion of submissions between INDs and NDAs/BLAs, (3) percentage distribution along the stages of drug development, (4) percentage distribution across various therapeutic areas, and (5) nature of QSP applications. In brief, QSP is increasingly applied to model and simulate both drug effectiveness and safety throughout the drug development process across disease areas.

Agroecology is recognised as a socio-political and agricultural praxis and as a scientific domain. However, the dominant anthropocentric narrative that views nature as an exploitable resource is st...

espanolJose Felipe Flores es uno de los cientificos del siglo XVIII mas olvidados hoy en dia. Sin embargo, siempre estuvo muy activo en varios ramos de las ciencias. Obro ademas por el desarrollo del conocimiento cientifico en Guatemala. Por eso quiso viajar por Europa. De este periplo quedan algunas cartas y un diario, inedito y desconocido hasta hoy, debido a una equivocada identificacion de su autor. En este articulo, es este diario el que vamos a glosar y analizar. Trataremos la cuestion de su autor y de su historia y estudiaremos su dimension cientifica, con la mencion que en el se hace de los avances cientificos y de los sabios con los cuales se encuentra el doctor Flores. EnglishJose Felipe Flores is one of the scientists of the eighteenth century who is totally forgotten by now. However, he always was very active in several sections of the scientific domain. Moreover, he always did what he could for the development of the scientific knowledge in Guatemala. That is why he travelled through Europe. Of this travel, he left letters and a diary, unpublished and unknown until today, because of a wrong identification of its author. With this article, we intend to study this particular diary. After the evocation of its author and its history, we will observe its scientific dimension, with the mentions of the scientific development and of the contacts between the Guatemalan doctor and the European scientists.

Philosophical discussions of disagreement typically focus on cases in which the disagreeing agents are aware that they are disagreeing and can pinpoint the proposition that they are disagreeing about. Scientific disagreements are not, in general, like this. Here we consider several case studies of disagreements that do not concern first-order factual claims about the scientific domain in question, but rather boil down to disputes regarding methodology. In such cases, it is often difficult to identify the point of contention in the dispute. Philosophers of science have a useful role to play in pinpointing the source of such disagreements, but must resist the temptation to trace scientific debates to disputes over higher-level philosophical accounts.

Introducción: Las pseudociencias utilizan herramientas discursivas falaces para inmiscuirse en la sociedad. Estudios recientes investigan a diferentes colectivos profesionales para identificar, caracterizar y subvertir estos discursos. Objetivo: Analizar la percepción de las pseudociencias en el colectivo médico español. Método: Se usó una metodología cualitativa basada en entrevistas en profundidad. Los datos se analizaron mediante un modelo de análisis inductivo con la intención de identificar los patrones comunes presentes en las entrevistas. Resultados: Los entrevistados definieron las pseudociencias como manifestaciones carentes de método científico y que derivan de la autoridad de un supuesto especialista. Se muestran reticentes ante su uso. La connotación espiritual de las pseudociencias, junto con la instrumentalización del efecto placebo, su disfraz de natural e innocuo, y el acompañamiento emocional se identificaron como las causas principales de su expansión. Conclusiones: 1) para la prevención de las pseudociencias debe contarse con el apoyo coordinado de las autoridades sanitarias; 2) la precarización de los servicios asistenciales puede ser una de las causas de su expansión; 3) en el contexto de la posverdad, los argumentos emocionales o espirituales adquieren una mayor autoridad que los científicos, causando una pérdida de confianza en el marco epistemológico científico. Introduction: Pseudoscience’s use fallacious arguments to expand in society. Different groups of professionals are being analyzed in order to identify, characterize and eventually undermine these major communicative patterns. Objective: To analyze the Spanish healthcare professionals’ perception of pseudoscience. Methodology: A qualitative approach was used, consisting of in-depth interviews and questionnaires. Data was analyzed using an inductive analysis with the intention to identify the main patterns present in the subjects. Results: Interviewees defined pseudoscience as those practices lacking any scientific method and created by false specialists. The spiritual character of pseudoscience, together with the exploitation of the placebo effect, its disguise of natural and innocuous, and the emotional support of the preceptors of the false therapies are highlighted as the main causes of its spread. Conclusions: 1) For pseudoscience’s prevention, healthcare professionals should be supported by coordinated strategies from the authorities; 2) the decline in public investment in the care services can be one of the causes of its expansion; 3) in the post-truth context, the emotional and spiritual arguments acquire a greater authority than the scientific ones, thus provoking a loss of confidence of the epistemological scientific framework.

Computational analysis and modeling of the evolution of trends is an important area of research in Natural Language Processing (NLP) because of its socio-economic impact. However, no large publicly available benchmark for trend detection currently exists, making a comparative evaluation of methods impossible. We remedy this situation by publishing the benchmark TRENDNERT, consisting of a set of gold trends and downtrends and document labels that is available as an unrestricted download, and a large underlying document collection that can also be obtained for free. We propose Mean Average Precision (MAP) as an evaluation measure for trend detection and apply this measure in an investigation of several baselines.

The primary intention of any scientific work is to share the gained knowledge and to contribute to the knowledge and progress in the scientific domain. The wide range of journals and conferences, each with specific submission requirements, can be difficult to navigate, especially for young scientists without extensive experience. But a suitable publication strategy can be helpful, especially at the beginning of a scientific career. Using the annual conference of the German Association for Medical Informatics, Biometry and Epidemiology (GMDS) e.V. as an example, this editorial highlights fundamental differences, advantages and disadvantages, as well as assistance in selecting the right form of submission.

International audience; Delineating scientific domains in the literature using the CorTexT platform

Free-space optical (FSO) communication offers much higher data rates when compared to other available underwater communication technologies. It has been used for decades in scientific and military applications, but until recently no commercial products were available. With the advent of commercially available FSO technology, the number of applications in the commercial and scientific domain has greatly expanded. This paper provides a short overview over commercially available FSO technology and highlights their use in current and future projects.

The modern Digital Universe changes and expands at a speed that every two years double the amount of data. It leads to a situation when huge accumulated flows of information can no longer be covered by traditional scientific search and built into a relevant scientific research framework. The authors argue that there is a need for using modern statistics and scientometric application packages for solving research tasks in the primary trends of the information economy. The article presents a comparative analysis of various scientometric programs and describes a new approach to identifying and visualizing patterns and transient regularities in the scientific literature on the basis of a study of global publication flows in the last 25 years in the subject area of «labour economics» represented in the Web of Science.The authors conceptualize and visualize scientific domain of «labour economics» within the framework of the timing diagram of the evolution of research fronts. They introduce the search algorithm for active research fronts in the global information flow using CiteSpace V.0 and highlight the most critical trends and principal points of research clusters for the past decade on labour economics and its core studies. The paper determines most perspective citation spikes that could potentially become the center of new scientific knowledge in this area and outlines opportunities for future research.

In recent decades the use of forensic science in investigations and therefore its subsequent presentation within the courts has increased exponentially, fuelled by an increase in scientific advances, development of databases and greater access to scientists and their expertise. This explosion in the use of forensic evidence has not been limited to one single scientific domain, as there are a broad range of scientific disciplines, encompassed by the general umbrella term' forensic science'. Many of these involve commonly applied methodologies and are accepted by the courts with limited scrutiny. Where tensions exist concerning the use of science in the courtroom is when novel or emerging sciences and scientific techniques are introduced. This may be particularly evident when the demands of the investigatory phase, where those working want to apply all possible tools at their disposal to gather as much evidence as possible and the needs of the courts, where the evidence must scientifically robust and admissible for it to be presented before a jury, come together. This paper examines the implications for the court for emerging or novel sciences and scientific techniques. In such cases, the potential rewards of implementing the scientific process and the information these may contribute to an investigation provides a temptation to investigators to push for their operational use, with the unintended consequence of posing an issue to the court when considering whether to admit the evidence into the judicial process.

Science mapping (SM) is an effective and useful methodology for studying and understanding the structural and dynamic features of a scientific domain through constructing, analysing, and visualising bibliometric networks. Hence, using the method has been given substantial attention in many fields, including the built environment (BE). Research in BE involves many diverse domains, subjects, or topics. Objective mapping and understanding of the knowledge in these domains warrants SM. This chapter contains an introduction to the topic of applying SM in BE research. The purpose, essentially, is to contribute to addressing the broader question of how to use SM in BE. A tutorial is included to demonstrate, step by step, how three software packages, VOSviewer, CiteSpace, and Gephi, can be applied together to conduct robust/deep SM-based research. This chapter could help researchers and other interested stakeholders to undertake quality research using SM.

This issue of the JSE includes a retraction of a paper by Alejandro Parra that we published in 2017. As far as I can determine, it’s the journal’s first official retraction of a published paper. The reason for this action is the author’s extensive plagiarism, both in that paper and in other published work (including a recent book whose publisher has since recalled all copies). It’s a sad state of affairs, of course—and perhaps the first of its kind in this particular and admittedly minor scientific domain. But it reminds me that six years ago, in Volume 29(2), we published a paper on retractions in science, and in that issue I seized the opportunity to editorialize further on the subject. I recycle that Editorial below. But before that, I must note that careful examination has found no additional evidence of plagiarism in the one other research article (in 2018) and the one book review we’ve published by Parra. I must also mention that, henceforth, the JSE will run routine plagiarism tests on papers accepted for publication. I thought this was a chore I’d left behind when I retired from teaching. However, I don’t want the JSE to emulate the person who said “I’ve learned from my mistakes, and I’m certain I can repeat them exactly.” EDITORIAL FROM JSE VOLUME 29(2), 189–192

Relational databases are prevalent in handling large and complex databases; however, writing the SQL queries can be a tedious task for databases. Recent studies for automating the task of translating natural language text to SQL query are not robust to queries having multi-table dependencies. Also, considering the lack of such research in scientific domain, we introduce ACL-SQL, a dataset with complex queries depending on up to five tables and benchmark the dataset on a simple approach. Evaluation shows that our approach is reasonably precise and can be adopted for practical applications. The dataset and codes are available at https://github.com/rohitshantarampatil/sql-nlp.

With the increasing demand for inventive products, finding out inventive design solutions hidden in different industrial engineering domains has always been a challenge for engineers. In addition, patent documents are full of the latest inventive knowledge inside. In this paper, we rely on the assumption that an engineering problem may have an inventive practical solution in another scientific domain as long as they are similarly described. Therefore, we focus on applying machine learning techniques, more particularly neural networks to determine the similarity between patent problems. Technically, a trained bidirectional LSTM neural network, called Manhattan LSTM is integrated into our approach named SAM-IDM to predict the similarity between sentences. We experimentally show that Manhattan LSTM outperforms other baseline approaches in a labelled sample dataset of SNLI corpus. We then experiment our approach on a real-world U.S. patent dataset and we demonstrate that it presents promising results in terms of sentence similarity matching and inventiveness. An inventive design case is detailed to illustrate its performance and practicality.

Transfer learning technologies have not been well explored in the scientific domain of audio signal processing. This chapter provides a brief introduction to transfer learning followed by a generic tool for feature space adaptation, which comprises a fundamental step toward the successful application of such technologies.

Optimization problems frequently appear in any scientific domain. Most of the times, the corresponding decision problem turns out to be NP-hard, and in these cases genetic algorithms are often used to obtain approximated solutions. However, the difficulty to approximate different NP-hard problems can vary a lot. In this paper, we analyze the usefulness of using genetic algorithms depending on the approximation class the problem belongs to. In particular, we use the standard approximability hierarchy, showing that genetic algorithms are especially useful for the most pessimistic classes of the hierarchy.

To explain the origins of new scientific ideas, historians and philosophers of science point to examples where scientists appear to have drawn analogies between their scientific domain and some very different domain. By contrast, research from the psychology lab suggests that those kinds of analogies are very difficult to obtain in even the simplest situations. To resolve this potential conflict, we examine the analogies that occur in psychology lab group and formal colloquium settings. This approach can be viewed as a crosssectional approximation of an historical analysis. We find that as the setting moves further away from the original discovery, the way different types of analogies appear to be used changes. In particular, analogies between very different domains are never used in reasoning in the lab group, whereas they are frequently used in reasoning in formal colloquium presentations. Yet, we find that analogy between very similar domains remains an important source of new ideas and a method for solving problems in scientific settings.

In this paper, I present a critique of taxonomic pluralism, namely the view that there are multiple correct ways to classify entities into natural kinds within a given scientific domain. I argue that taxonomic pluralism, as an anti-essentialist position, fails to provide a realist alternative to taxonomic monism, i.e., the view that there is only one correct way to classify entities into natural kinds within a given scientific domain. To establish my argument, I first explain why the naturalist approach to natural kinds adopted by pluralists requires them to give up the mind-independence criterion of reality presupposed by monists. Next, I survey two types of pluralist account. I argue that, while the modest pluralist account is not pluralistic enough, the radical pluralist account fails to come up with an alternative criterion of reality that is robust enough to differentiate its position from anti-realism about natural kinds. I conclude by drawing out the implications of my critique for the essentialism/anti-essentialism debate about natural kinds.

Mobility of doctoral students is considered a critical factor which contributes to the doctoral graduate research performance and the knowledge transfer. The research productivity of doctoral students is still more critical for those novel research groups which have to overcome several barriers before they reach a reasonable stability in research productivity. Getting started with a novel group could take several years until the group reaches a minimum productivity, depending on the field of study. Besides, internationalization of a novel group means its regular participation in the international research networks in the respective scientific domain. This contribution presents a case study of the impact of international mobility of doctoral students in the global research productivity of the hosting novel research group. The increase in research productivity due to mobility of doctoral students is shown analyzing the evolution of the number of articles published and comparing it to the critical decisions of internationalization taken by the group, suggesting a relationship between both arguments. Results show that the impact of the doctoral mobility reaches 45% of the total productivity in a period of 12 years.

Domain knowledge map, a.k.a., scholarly network, construction as an important method can describe the significant characters of a selected domain. In this research, we will address three fundamental problems for scholarly network generation. Firstly, two different methods will be investigated to associate keywords on the graph: Co-occur Domain Distance and Citation Probability Distribution Distance. Secondly, this paper will construct domain (core journals and conference proceedings) knowledge and domain referral (domain citation) scholarly networks, and propose a novel method to integrate those graphs by optimizing the nodes and their linkage. Finally, the paper will propose an innovative method to evaluate the accuracy and coverage of scholarly networks based on training keyword oriented Labeled-LDA model and validate different domain or domain referral graphs.

As a typical representative of research in various scientific domains, methods and models always play as a critical role. These methods and models are numerous and heterogeneous, and usually need to be manually sorted out and classified systematically, which is often time-consuming and laborious. Therefore, this paper proposes a solution for methods and models classification automatically based on community detection algorithms in the scientific domain. The co-words network extracted from the literature data could be divided into different communities based on different detection algorithms. Meanwhile, the keywords of methods and models are automatically divided into different categories. As a case study, this paper analyzed the literature data in the human resource management (HRM) domain. We compared the results obtained by six community detection algorithms, such as Louvain, Girvan Newman (GN), with technical indicators and expert validation. At last, the keywords of the methods and models in the HRM domain classified into 12 communities. The results shown that our research provides an effective method that can effectively classify the methods and models automatically in the scientific domain.

As a cross-disciplinary scientific domain, a great deal of research on landscape geochemistry has been conducted since its establishment. However, the used methods lack the ability of revealing the...

This paper studies the combined effect of affiliation with prestigious universities, underwriters, and venture capitalists on the valuation of biotech ventures at IPO and their post-IPO performance. We argue that affiliation to a prestigious university provides the affiliated firm with a quality signal in the scientific domain. The pure quality signaling effect of the affiliation is isolated from the substantive benefits it provides by performing a difference-in-difference approach based on the scientific reputation of scientists in firms' upper echelons. The signal is stronger the weaker is the scientific reputation of scientists of the focal IPO-firm and is additive to those provided by prestigious venture capitalists and underwriters. Results for a sample of 254 European biotech ventures that went through an IPO between 1990 and 2009 confirm our predictions.

Dendrimers and dendrimer-based delivery systems are potential biomedicines in the rapidly growing field of nanomedicine. At present, dendrimers are drawing attention in the scientific domain due to their unique structural features, physiological properties and biological attributes. These multifunctional nanomaterials provide unique platforms for targeting, imaging, diagnostics and theranostics. The rationale of this article is to offer insight into the pulmonary delivery of these multifunctional nanomaterials. This review examines reports on inhaled dendrimers which have been published in the last few years. The article begins by describing the relevant background knowledge of dendrimers, dendrimer synthesis schemes and their potential advantages as nanomaterials. It progresses to the pulmonary applications of dendrimers, with special emphasis on pressurized metered-dose inhalers (pMDIs), soft mist inhalers (SMI), nebulizers and dry powder inhalers (DPI). Additionally, this review article contains a dedicated section discussing the biocompatibility challenges and clinical outcomes of dendrimer-based nanotherapeutics. In summary, this review is the first comprehensive account of inhaled dendrimers to appear in recent years.

The number of journal articles in the scientific domain has grown to the point where it has become impossible for researchers to capitalize on all findings in their relevant discipline. Information is stored in these articles in a number of ways, including figures that describe important results. In organic chemistry, these figures often present chemical schematic diagrams that graphically define the structures of carbon-based compounds. These diagrams are intuitive for an expert to comprehend, but they are not designed for machines. This work presents ChemSchematicResolver, a software tool that can be used to identify chemical schematic diagrams within the figure of a document, resolve any R-group substituents within them, and convert the resulting diagrams to a machine-readable format in a high-throughput, autonomous fashion. The tool includes a new algorithm that is used to identify relevant diagrams and a mechanism that combines these data with contextual information from the rest of the document for the creation of highly relational databases. It includes support for a variety of general R-group structures, the first time this is available in any open-source chemical schematic diagram extraction tool. It is presented alongside a self-generated evaluation set, on which the most important assessment metric, precision, achieved 83-100% for all assessed areas. The ChemSchematicResolver tool is released under the MIT license and is available to download from www.chemschematicresolver.org.

The problem of incomplete data and its implications for drawing valid conclusions from statistical analyses is not related to any particular scientific domain, it arises in economics, sociology, education, behavioural sciences or medicine. Almost all standard statistical methods presume that every object has information on every variable to be included in the analysis and the typical approach to missing data is simply to delete them. However, this leads to ineffective and biased analysis results and is not recommended in the literature. The state of the art technique for handling missing data is multiple imputation. In the paper, some selected multiple imputation methods were taken into account. Special attention was paid to using principal components analysis (PCA) as an imputation method. The goal of the study was to assess the quality of PCA‑based imputations as compared to two other multiple imputation techniques: multivariate imputation by chained equations (MICE) and missForest. The comparison was made by artificially simulating different proportions (10–50%) and mechanisms of missing data using 10 complete data sets from the UCI repository of machine learning databases. Then, missing values were imputed with the use of MICE, missForest and the PCA‑based method (MIPCA). The normalised root mean square error (NRMSE) was calculated as a measure of imputation accuracy. On the basis of the conducted analyses, missForest can be recommended as a multiple imputation method providing the lowest rates of imputation errors for all types of missingness. PCA‑based imputation does not perform well in terms of accuracy. Problem występowania danych niekompletnych i ich wpływu na wyniki analiz statystycznych nie jest związany z żadną konkretną dziedziną nauki – pojawia się w ekonomii, socjologii, edukacji, naukach behawioralnych czy medycynie. W przypadku większości klasycznych metod statystycznych wymagana jest kompletna informacja o zmiennych charakteryzujących badane obiekty, a typowym podejściem do brakujących danych jest po prostu ich usunięcie. Prowadzi to jednak do niewiarygodnych i obciążonych wyników analiz i nie jest zalecane w literaturze przedmiotu. Rekomendowaną metodą postępowania z brakującymi danymi jest imputacja wielokrotna. W artykule rozważono kilka wybranych jej metod. Szczególną uwagę zwrócono na wykorzystanie analizy głównych składowych (PCA) jako metody imputacji. Celem pracy była ocena jakości imputacji opartej na PCA na tle dwóch innych technik uzupełniania braków danych: imputacji wielokrotnej za pomocą równań łańcuchowych (MICE) i metody missForest. Porównania metod imputacji dokonano, wykorzystując podejście symulacyjne i generując braki danych w 10 kompletnych zbiorach danych z repozytorium baz danych Uniwersytetu Kalifornijskiego w Irvine, z uwzględnieniem różnych mechanizmów generowania braków danych oraz różnych proporcji (10–50%) brakujących wartości. Do imputacji brakujących wartości zastosowano metodę równań łańcuchowych, metodę missForest oraz metodę opartą na głównych składowych (MIPCA). Znormalizowany pierwiastek kwadratowy błędu średniokwadratowego (NRMSE) wykorzystano jako miarę dokładności imputacji. Na podstawie przeprowadzonych analiz metoda missForest może być rekomendowana jako ta metoda wielokrotnej imputacji, która zapewnia najwyższą dokładność imputacji braków danych. Imputacja oparta na analizie głównych składowych (PCA) nie prowadzi do zadowalających wyników.

Spin-polarization can be essential in many cases of vital importance to the procedures of chemical and biological function. Its realization and utilization have been drawing intensively growing attention for over half a century, whereby numerous strategies get developed with related mechanisms proposed. Furthermore, spintronics has evolved as a scientific domain in which efforts are made to better understand the electron's intrinsic quantum properties based on its angular momentum. To date, an effective approach for aligning the electrons’ spin usually employs an external magnetic field, which may not be viable or efficient in all applications. This review emphasizes on the advances of spintronics where the polarization of spin is able to be implemented by other means than an external magnetic field. The key role of chiral structures for filtering the electrons on spin along with the approaches applied to monitor the polarization of spin will get introduced. Moreover, theoretical frameworks rationalizing the experimental results obtained are also presented herein. The thread running through all of these will be the proposal and evolution of Chiral-Induced Spin Selectivity (CISS) effect.