Field Of Science Research Articles

Artificial intelligence applied to MRI data to tackle key challenges in multiple sclerosis.

Artificial intelligence (AI) is the branch of science aiming at creating algorithms able to carry out tasks that typically require human intelligence. In medicine, there has been a tremendous increase in AI applications thanks to increasingly powerful computers and the emergence of big data repositories. Multiple sclerosis (MS) is a chronic autoimmune condition affecting the central nervous system with a complex pathogenesis, a challenging diagnostic process strongly relying on magnetic resonance imaging (MRI) and a high and largely unexplained variability across patients. Therefore, AI applications in MS have the great potential of helping us better support the diagnosis, find markers for prognosis to eventually design more powerful randomised clinical trials and improve patient management in clinical practice and eventually understand the mechanisms of the disease. This topical review aims to summarise the recent advances in AI applied to MRI data in MS to illustrate its achievements, limitations and future directions.

Mapping science through editorial board interlocking: connections and distance between fields of knowledge and institutional affiliations

AbstractResearch is a global enterprise underpinned by the general belief that findings need to be true to be considered scientific. In the complex system of scientific validation, editorial boards (EBs) play a fundamental role in guiding journals’ review process, which has led many stakeholders of sciences to metaphorically picture them as the “gatekeepers of knowledge.” In an attempt to address the academic structure that governs sciences through editorial board interlocking (EBI, the cross-presence of EB members in different journals) and social network analysis, the aim of this study is threefold: first, to map the connection between fields of knowledge through EBI; second, to visualize and empirically test the distance between social and general sciences; and third, to uncover the institutional structure (i.e., universities) that governs these connections. Our findings, based on the dataset collected through the Open Editors initiative for the journals indexed in the JCR, revealed a substantial level of collaboration between all fields, as suggested by the connections between EBs. However, there is a statistically significant difference between the weight of the edges and the path lengths connecting the fields of natural sciences to the fields of social sciences (compared to the connections within), indicating the development of different research cultures and invisible colleges in these two research areas. The results also show that a central group of US institutions dominates most journal EBs, indirectly suggesting that US scientific norms and values still prevail in all fields of knowledge. Overall, our study suggests that scientific endeavor is highly networked through EBs.

Absolutism of The Caliphate During the Abbasid Dynasty

The Abbasid Dynasty was the second Caliphate to rule Baghdad for more than five centuries (132H/750 AD to 656H/1258 AD) after conquering the Umayyad Caliphate against the background of the Umayyad Dynasty's oppression of the Abbasid Dynasty. During the five centuries of rule the Abbasid Caliphate reached its heyday in the field of science, both general science and religion. The Abbasid system of government refers to four aspects. In the first and third periods of Abbasid rule, Persian culture was greatly influenced and in this period more emphasis was placed on the cultivation of Islamic civilization and culture than territorial expansion. In the second and fourth periods influenced by Turkish culture which was very dominant in politics and government. While the fifth period was marked by the entry of the Seljuks into Baghdad until the fall of Baghdad to the Mongols. Each dynasty had its own style of leadership as well as the Abbasid Dynasty which applied absolutism in its leadership. Where the Caliph has authority over matters related to the state and religion. The caliph has unlimited authority and can only be replaced when the caliph dies.

Bibliometric Analysis of Scientific Publications on Communicative Behavior Problems

Purpose of research. The purpose of the study is to analyze the dynamics of the publication activity of scientific research in the field of studying communicative behavior. Communicative behavior is an object with an interdisciplinary research status. It falls into the area of research interest of various scientific fields. A bibliometric analysis of publication activity was carried out in connection with solving several tasks: to find out areas of knowledge in which the greatest publication activity is concentrated, to study the methods that are used in various fields of communicative behavior analysis, to identify organizations that are included in this research search.Methods. The study was conducted in two scientific electronic databases: the Russian Scientific Electronic Library Elibrary.ru and the international open platform for researchers and scientific organizations Lens. The bibliometric analysis was used as the research method. It involves the quantification of documentary information flows and it is based on quantitative research indicators reflecting the state of science as a whole or its individual branches.Results. As a result of the bibliometric analysis of publication activity on the problems of scientific research in the field of communicative behavior, communicative behavior in the digital environment and communicative behavior in social networks, a significant increase in publication activity was revealed in both international and Russian information databases over the past 10 years (2013 - 2023). It is also noted that the predominant number of publications on the issues studied is concentrated in the field of psychology. However, we can trace a shift in the focus of foreign research on communicative behavior towards digitalization in information technology, and Russian research towards the field of digital technologies in the educational environment.Conclusion. The results obtained indicate the high relevance, as well as the scientific and practical significance of the research topic on the problems of communicative behavior in general, as well as communicative behavior in the digital environment and social networks, in particular.

ProQuiz

ProQuiz is an app designed for educational purposes, specifically to help users prepare for multiple-choice exams, especially in the field of computer science. The app aims to make studying enjoyable by incorporating elements of gamification. The primary objective of ProQuiz is to assist users in getting ready for subjective tests used in admissions and recruitment processes, with a focus on the computer science domain. The app is organized into three main modules: computer science, reasoning, and analytical skills. Each of these modules covers various sub-categories to address different subjects. During the quiz, users have access to helpful features such as hints, the ability to skip questions, and a pause/life-lines option. These features can be used only once per user. The app also provides feedback on progress throughout the quiz, and upon completion, it displays the user's results. The overall aim is to provide users with an engaging platform for practicing and enhancing their knowledge in a variety of subjects related to computer science. This research paper examines the development and effectiveness of ProQuiz. Through user testing and analysis, we evaluate its usability and engagement. Additionally, we propose enhancements, including personalized learning paths and social features. This paper contributes insights into innovative educational technology and suggests avenues for future improvement of ProQuiz.

Identifying interdisciplinary emergence in the science of science: combination of network analysis and BERTopic

Global scientific output is expanding exponentially, which in turn calls for a better understanding of the science of science and especially how the boundaries of scientific fields expand through processes of emergence. The present study proposes the application of embedded topic modeling techniques to identify new emerging science via knowledge recombination activities as evidenced through the analysis of research publication metadata. First, a dataset is constructed from metadata derived from the Web of Science Core Collection database. The dataset is then used to generate a global map representing a categorical scientific co-occurrence network. A research field is defined as interdisciplinary when multiple science categories are listed in its description. Second, the co-occurrence networks are subsequently compared between periods to determine changing patterns of influence in light of interdisciplinarity. Third, embedded topic modeling enables unsupervised association of interdisciplinary classification. We present the results of the analysis to demonstrate the emergence of global interdisciplinary sciences and further we perform qualitative validation on the results to identify what the sources of the emergent areas are. Based on these results, we discuss potential applications for identifying emergence through the merging of global interdisciplinary domains.

Surveying the Landscape of Environmental Social Science: A Bibliometric and Network Analysis

Abstract Social science research on the environment has grown exponentially in the past four decades alongside increasing awareness that environmental risks, such as climate change, cannot be understood by natural science interventions alone. While prior research examines how specific disciplines, like sociology, have attended to the environment or how specific problems have been engaged across disciplines, less attention has been offered to the entire landscape of research on the environment in the social sciences. In this article, we ask: What is the landscape of environmental social science? Focusing on 124,906 social scientific articles from the Web of Science, we analyze the relationship between journals publishing research on the environment. Specifically, we construct journal citation networks and topic models on bibliographic records from 1990 to 2022. Results suggest that journals form coherent communities associated with both disciplinary and interdisciplinary research topics, indicating that journal communities may be a central organizing feature of ESS. Moreover, research topics prevalent in this field have changed over time, potentially in relation to the ongoing neoliberalization of climate change politics. As scholars want to influence policy and industrial practice, their research implicitly reflects values consistent with the current political economic order. We conclude by highlighting the implications of these findings for the field of environmental social science.

A systematic review to determine the effect of strategies to sustain chronic disease prevention interventions in clinical and community settings: study protocol

BackgroundThe primary purpose of this review is to synthesise the effect of strategies aiming to sustain the implementation of evidenced-based interventions (EBIs) targeting key health behaviours associated with chronic disease (i.e. physical inactivity, poor diet, harmful alcohol use, and tobacco smoking) in clinical and community settings. The field of implementation science is bereft of an evidence base of effective sustainment strategies, and as such, this review will provide important evidence to advance the field of sustainability research.MethodsThis systematic review protocol is reported in accordance with the Preferred Reporting Items for Systematic review and Meta-Analysis (PRISMA) checklist. Methods will follow Cochrane gold-standard review methodology. The search will be undertaken across multiple databases, adapting filters previously developed by the research team, data screening and extraction will be performed in duplicate, strategies will be coded using an adapted sustainability-explicit taxonomy, and evidence will be synthesised using appropriate methods (i.e. meta-analytic following Cochrane or non-meta-analytic following SWiM guidelines). We will include any randomised controlled study that targets any staff or volunteers delivering interventions in clinical or community settings. Studies which report on any objective or subjective measure of the sustainment of a health prevention policy, practice, or programme within any of the eligible settings will be included. Article screening, data extraction, risk of bias, and quality assessment will be performed independently by two review authors. Risk of bias will be assessed using Version 2 of the Cochrane risk-of-bias tool for randomised trials (RoB 2). A random-effect meta-analysis will be conducted to estimate the pooled effect of sustainment strategies separately by setting (i.e. clinical and community). Sub-group analyses will be undertaken to explore possible causes of statistical heterogeneity and may include the following: time period, single or multi-strategy, type of setting, and type of intervention. Differences between sub-groups will be statistically compared.Discussion/conclusionThis will be the first systematic review to determine the effect of strategies designed to support sustainment on sustaining the implementation of EBIs in clinical and community settings. The findings of this review will directly inform the design of future sustainability-focused implementation trials. Further, these findings will inform the development of a sustainability practice guide for public health practitioners.Systematic review registrationPROSPERO CRD42022352333.

Exploring the Role of Self-Adaptive Feature Words in Relation Quintuple Extraction for Scientific Literature

Extracting relation quintuple and feature words from unstructured text is a prelude to the construction of the scientific knowledge base. At present, the prior works use explicit clues between entities to study this task but ignore the use and the association of the feature words. In this work, we propose a new method to generate self-adaptive feature words from the original text for every single sample. These words can add additional correlation information to the knowledge graph. We allow the model to generate a new word representation and apply it to the original sentence to judge the relation type and locate the head and tail of the relation quintuple. Compared with the previous works, the feature words increase the flexibility of relying on information and improve the explanatory ability. Extensive experiments on scientific field datasets illustrate that the self-adaptive feature words method (SAFW) is good at ferreting out the unique feature words and obtaining the core part for the quintuple. It achieves good performance on four public datasets and obtains a markable performance improvement compared with other baselines.

Using policy codesign to achieve multi-sector alignment in adolescent behavioral health: a study protocol

BackgroundPolicymaking is quickly gaining focus in the field of implementation science as a potential opportunity for aligning cross-sector systems and introducing incentives to promote population health, including substance use disorders (SUD) and their prevention in adolescents. Policymakers are seen as holding the necessary levers for realigning service infrastructure to more rapidly and effectively address adolescent behavioral health across the continuum of need (prevention through crisis care, mental health, and SUD) and in multiple locations (schools, primary care, community settings). The difficulty of aligning policy intent, policy design, and successful policy implementation is a well-known challenge in the broader public policy and public administration literature that also affects local behavioral health policymaking. This study will examine a blended approach of coproduction and codesign (i.e., Policy Codesign), iteratively developed over multiple years to address problems in policy formation that often lead to poor implementation outcomes. The current study evaluates this scalable approach using reproducible measures to grow the knowledge base in this field of study.MethodsThis is a single-arm, longitudinal, staggered implementation study to examine the acceptability and short-term impacts of Policy Codesign in resolving critical challenges in behavioral health policy formation. The aims are to (1) examine the acceptability, feasibility, and reach of Policy Codesign within two geographically distinct counties in Washington state, USA; (2) examine the impact of Policy Codesign on multisector policy development within these counties using social network analysis; and (3) assess the perceived replicability of Policy Codesign among leaders and other staff of policy-oriented state behavioral health intermediary organizations across the USA.DiscussionThis study will assess the feasibility of a specific approach to collaborative policy development, Policy Codesign, in two diverse regions. Results will inform a subsequent multi-state study measuring the impact and effectiveness of this approach for achieving multi-sector and evidence informed policy development in adolescent SUD prevention and treatment.

Statistical data transformation in agrarian sciences for variance analysis: a systematic review

In statistical analyses, a common practice for enhancing the validity of variance analysis is the application of data transformation to convert measurements into a different mathematical scale. This technique was first employed in 1898 by Edgeworth and remains relevant in current scientific publications despite the proliferation of more modern and advanced techniques that obviate the need for certain assumptions. Data transformations, when appropriately used, can make the model error terms approximate a normal distribution. It is also possible to use the technique to correct the heterogeneity of variances or to render an additive model, ensuring the validity of the analysis of variances. Given that this technique can be hastily applied, potentially leading to erroneous or invalid results, we conducted a systematic literature review of studies in the field of agrarian sciences that utilized data transformations for the validation of analysis of variances. The aim was to check the transformations employed by the scientific community, the motivation behind their use, and to identify possible errors and inconsistencies in applying the technique in publications. In this study, we identified shortcomings and misconceptions associated with using this method, and we observed incomplete and inadequate utilization of the technique in 94.28% of the analysed sample, resulting in misguided and erroneous conclusions in scientific research outcomes.

The Title of the Growth of New Dynasties in Spain Maghrib and Iran

This research aims to examine the birth and development of new dynasties in the regions of the Spanish Maghrib and Iran after the collapse of major powers such as the Umayyad Caliphate in Spain and the Abbasid Caliphate in Iran. Employing a literature research approach, this study traces the background of the emergence, expansion processes, consolidation of power, as well as the contributions of these dynasties to the intellectual and cultural development in the regions they ruled. In the Spanish Maghrib, the Almoravid and Almohad Dynasties emerged as new powers after the fall of the Umayyad Caliphate. Both dynasties succeeded in uniting the regions of Spain and the Maghrib, albeit with different methods and ideologies. Meanwhile, in Iran, the Ilkhanid, Jalayirid, Timurid, and Safavid Dynasties rose after the collapse of the Abbasid Caliphate, each exerting significant influence and contributions to the political, cultural, artistic, and scientific development. The research findings indicate that the birth and development of these new dynasties not only brought about political changes but also contributed significantly to intellectual and cultural advancements in both regions. The periods under their rule are known as golden ages in the fields of art, architecture, literature, mathematics, astronomy, philosophy, and other sciences. These dynasties fostered the exchange of ideas among various ethnic and religious groups and created a conducive environment for the growth of knowledge and creativity. Overall, this study highlights the importance of the new dynasties in the dynamics of history and civilization, as well as their contributions in shaping new political landscapes and catalyzing the growth of rich knowledge, art, and culture.

Jogos de linguagem e neodocumentalismo

This article aims to establish relationships between a theory of Neodocumentalism in Information Science and issues exposed in the philosophical systems of Ludwig Wittgenstein's Philosophy, especially in its second phase, as exposed in his work Philosophical Investigations. In this sense, it is intended to establish converging relationships between the concept of language-games and aspects related to the document as an instrument for conveying information, language and social practice. After an introduction to the topic, concepts of Neodocumentalism in the field of Information Science will be presented. Then, a presentation of Wittgenstein's system will be made, especially the system of its second phase and, soon after, aspects and considerations will be approached between Neodocumentalism and language-games.

“Recovery is Complicated”: A Qualitative Exploration of Canadian University Students’ Diverse Recovery Experiences

ABSTRACT While the field of recovery science has burgeoned over the past two decades, little research has considered the experiences of university students in recovery from addiction, particularly in Canada. Addressing this gap, using a recovery capital framework, 16 qualitative interviews were conducted to explore students’ meanings, experiences, and barriers/facilitators to recovery from problematic substance use and/or behaviors. Reflexive thematic analysis revealed three main themes: 1. multiple recovery pathways and identities; 2. stigma and disclosure; and 3. proximity to campus community and resources. Recommendations to create more recovery-friendly campuses are provided.

Opinion: New directions in atmospheric research offered by research infrastructures combined with open and data-intensive science

Abstract. The acquisition and dissemination of essential information for understanding global biogeochemical interactions between the atmosphere and ecosystems and how climate–ecosystem feedback loops may change atmospheric composition in the future comprise a fundamental prerequisite for societal resilience in the face of climate change. In particular, the detection of trends and seasonality in the abundance of greenhouse gases and short-lived climate-active atmospheric constituents is an important aspect of climate science. Therefore, easy and fast access to reliable, long-term, and high-quality observational environmental data is recognised as fundamental to research and the development of environmental forecasting and assessment services. In our opinion article, we discuss the potential role that environmental research infrastructures in Europe (ENVRI RIs) can play in the context of an integrated global observation system. In particular, we focus on the role of the atmosphere-centred research infrastructures ACTRIS (Aerosol, Clouds and Trace Gases Research Infrastructure), IAGOS (In-service Aircraft for a Global Observing System), and ICOS (Integrated Carbon Observation System), also referred to as ATMO-RIs, with their capabilities for standardised collection and provision of long-term and high-quality observational data, complemented by rich metadata. The ATMO-RIs provide data through open access and offer data interoperability across different research fields including all fields of environmental sciences and beyond. As a result of these capabilities in data collection and provision, we elaborate on the novel research opportunities in atmospheric sciences which arise from the combination of open-access and interoperable observational data, tools, and technologies offered by data-intensive science and the emerging collaboration platform ENVRI-Hub, hosted by the European Open Science Cloud (EOSC).

Investigation of Polymer-Asphalt Compatibility Using Molecular Dynamics Simulation.

Polymer modification is a promising approach to enhancing the performance of asphalt binders. However, a major issue plaguing polymer mixing with asphalt is the phase separation of these two components post-mixing. In the field of polymer science, the Flory-Huggins theory has been long established as the way to describe the conditions under which a mixture is stable or unstable. This Flory-Huggins interaction parameter χ and the molecular weights of the components are required under this theory. This work uses molecular dynamics simulations to calculate χ between various polymers found in waste plastics and asphalt. The compatibility of these polymers with the asphalt binder is discussed as a function of binder composition, molecular weight, and temperature. Four common polymers (polyethylene, polystyrene, polypropylene, and polybutadiene) were tested. While none of the polymers showed good compatibility with asphalt, PE was the most compatible. Stable compatibilization of plastics with asphalt will require additives or chemical modification of the plastic.

The human and financial costs of conservation for local communities living around the Greater Serengeti Ecosystem, Tanzania

Protected areas have long been recognized globally as an important strategy for conserving biodiversity. However, the establishment of protected areas has often adversely impacted local livelihoods, particularly where people and their livelihoods are exposed to wildlife threats. Understanding the magnitude and the types of human and livelihood losses to wildlife can help to reduce the losses in the future. Here we collected and analysed a large and comprehensive historical data sets on crop damage, livestock depredation, and human attacks over eight years from January 2015 to October 2022 from Serengeti District and Ngorongoro Conservation Area to understand human and livelihood losses to wildlife in the Greater Serengeti Ecosystem (GSE). The data were government records of loss and compensation. Additionally, we performed individual interviews on what communities lose to wildlife in the area. We found that wildlife causes serious annual losses of crops (value estimated at USD 489,000) and livestock (USD 17,600). On average 22 people from villages beside or within the protected areas were injured each year and eight people were killed, usually by elephants. Compensation paid by the government to local communities only covered <20% of their total financial losses, and was also very little for the injury or loss of human life. Given our estimates are only for two administrative areas i.e. Serengeti District and Ngorongoro Conservation Area, the figure will be much higher if we include all districts around the GSE. These findings contribute to the broader conservation science field and the global discourse on human-wildlife conflict and coexistence. Protected area authorities should: a. take greater responsibility for protecting local communities and their assets from wildlife attacks, and b. assist the local communities with implementing deterrence and in establishing problematic animal prevention units in hotspot areas. In particular, we recommend that the Tanzanian Government should review the current compensation regulations to reflect the actual loss.

Exploring Gender Differences in Scientific Aptitude among Secondary School Students: A Comparative Analysis Between Boys and Girls

Present study explores the Numerical ability and Science information (Scientific aptitude) among boys’ and girls’ students. It is aimed to find out the difference between boys’ and girls’ students in terms of Numerical ability and Science information. A sample of 100 (50 each from boys and girls) students has been taken from government secondary schools of Goalpara district, Assam. For the selection of sample schools, Researcher used random sampling technique. The data were collected with the help of standardized tool. For the research work, researcher used Scientific Aptitude Test Battery (SATB) developed by Agarwal, K.K and Aurora, S. In this study descriptive research design is used. The study employed quantitative method and include standardized tests. The major findings of the study revealed that the Boys possess more Numerical ability than Girls. Again, there is no informational difference between boys and girls in the field of science.

Predicting low-cycle fatigue-induced fracture in reinforcing bars: A CNN-based approach

In low-damage structures such as rocking columns in bridges where the column ends are protected from spalling through confinement, the longitudinal reinforcing bars undergo reversing strain cycles, leading to fracture due to low-cycle fatigue. Several challenges arise due to the unsuitability of strain gauges to measure high strain ranges, in addition to the inability to visually inspect reinforcing bars after seismic events due to the use of confining details at the ends. Building on previous research that identified the fracture of reinforcing bars using column ends’ rotation to estimate reinforcing bars’ strains in conjunction with low-cycle fatigue models, this paper presents substantial development to predict the low-cycle fatigue-induced fracture of reinforcing bars using convolutional neural networks (CNNs) solely from strain time series data. The fracture was identified through strain measurements measured from a shake table testing of a quarter-scale, two-span resilient bridge specimen subjected to seismic excitations at the Earthquake Laboratory at the University of Nevada, Reno. The developed CNN model utilizes the Markov Transition Field technique to encode the strain time series into images and then uses the encoded images as input for channels in the input layer. These images are stacked in sequence to create a 3D array with 11 channels, one for each of the 11 different earthquake excitations that caused the damage. A three-layered CNN architecture with Adam optimizer was employed in training the model, achieving an accuracy of 100 % during training and more than 96 % during testing. To evaluate the model's performance, three distinct training/testing scenarios are proposed. The results demonstrate the efficacy of using CNNs to detect and characterize damage in structural elements using strain data. This approach has the potential to revolutionize the estimation of material fracture due to low-cycle fatigue in scientific fields using only the recoded strains.

Effect of Austempering and Martempering on Mechanical Properties and Structure of Bearing Steel (En31)

EN31 steel is easily available and cheap having all material properties that are acceptable for many applications. Heat treatment on low carbon steel is to improve ductility, to improve toughness, strength, hardness and tensile strength and to relive internal stress developed in the material. Here basically the experiment of harness and ultimate tensile strength is done to get idea about heat treated low carbon steel, which has extensive uses in all industrial and scientific fields.