Recent Research Trends Research Articles

Therapeutic potential and roles of dietary seaweeds in food: A systematic review

Food security is a significant global concern as a result of the burden that the fast-expanding global population has placed on finite resources, such as arable land for farming. Additionally, the hunt for more nutritious food alternatives has been prompted by a growing understanding of health, nutrition, and diet. Seaweeds are simple-to-grow aquatic plants that are underused for food and medicine. Recent studies have focused on gaining access to and using these readily available natural resources for nutrition and medicinal objectives. This review systematically evaluated trends of recent research on seaweed, for therapeutic possibilities and product development. After examining several documents, this analysis discovered that seaweeds are incredibly beneficial algae for both nutrition and medicine, and may be further explored in innovative food products, in meeting the increasing global need for food.

Peer Pressure: A Comprehensive Literature Review of the Last Two Decades

Peer pressure has long been recognized as a significant influence on individuals' behaviors, particularly in adolescence and young adulthood. This paper provides a detailed review of the literature over the past two decades on the peer pressure. Peer pressure remains a pervasive influence on individuals' behaviors, particularly during adolescence and emerging adulthood. Drawing upon a diverse array of studies, this review synthesizes findings on the definition, types, mechanisms, consequences, and interventions related to peer pressure. Peer pressure has long been recognized as a significant influence on individuals' behaviors, attitudes, and decision-making processes, particularly during adolescence. The review encompasses various dimensions of peer pressure, including its psychological, social, and cultural aspects, as well as its implications for health, education, and social development. The article also examines recent trends, advancements, and challenges in understanding and addressing peer pressure, offering insights for future research and intervention strategies. By examining recent research trends and emerging perspectives, this review offers insights into the complexities of peer influence and highlights avenues for future research. Through an examination of empirical studies, theoretical frameworks, and key findings, this review aims to elucidate the complex interplay between peer pressure.

Recent Research Trends in Neuroinflammatory and Neurodegenerative Disorders.

Neuroinflammatory and neurodegenerative disorders including Alzheimer's disease (AD), Parkinson's disease (PD), traumatic brain injury (TBI) and Amyotrophic lateral sclerosis (ALS) are chronic major health disorders. The exact mechanism of the neuroimmune dysfunctions of these disease pathogeneses is currently not clearly understood. These disorders show dysregulated neuroimmune and inflammatory responses, including activation of neurons, glial cells, and neurovascular unit damage associated with excessive release of proinflammatory cytokines, chemokines, neurotoxic mediators, and infiltration of peripheral immune cells into the brain, as well as entry of inflammatory mediators through damaged neurovascular endothelial cells, blood-brain barrier and tight junction proteins. Activation of glial cells and immune cells leads to the release of many inflammatory and neurotoxic molecules that cause neuroinflammation and neurodegeneration. Gulf War Illness (GWI) and myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) are chronic disorders that are also associated with neuroimmune dysfunctions. Currently, there are no effective disease-modifying therapeutic options available for these diseases. Human induced pluripotent stem cell (iPSC)-derived neurons, astrocytes, microglia, endothelial cells and pericytes are currently used for many disease models for drug discovery. This review highlights certain recent trends in neuroinflammatory responses and iPSC-derived brain cell applications in neuroinflammatory disorders.

Building Stock Models for Embodied Carbon Emissions—A Review of a Nascent Field

Building stock modeling emerges as a critical tool in the strategic reduction of embodied carbon emissions, which is pivotal in reshaping the evolving construction sector. This review provides an overall view of modern methodologies in building stock modeling, homing in on the nuances of embodied carbon analysis in construction. Examining 23 seminal papers, our study delineates two primary modeling paradigms—top-down and bottom-up—each further compartmentalized into five innovative methods. This study points out the challenges of data scarcity and computational demands, advocating for methodological advancements that promise to refine the precision of building stock models. A groundbreaking trend in recent research is the incorporation of machine learning algorithms, which have demonstrated remarkable capacity, improving stock classification accuracy by 25% and urban material quantification by 40%. Furthermore, the application of remote sensing has revolutionized data acquisition, enhancing data richness by a factor of five. This review offers a critical examination of current practices and charts a course toward an environmentally prudent future. It underscores the transformative impact of building stock modeling in driving ecological stewardship in the construction industry, positioning it as a cornerstone in the quest for sustainability and its significant contribution toward the grand vision of an eco-efficient built environment.

The Circular Economy: Recent debates and research trends

The Circular Economy is one of the most prominent cross-disciplinary and cross-sectoral concepts to emerge in recent decades. It has permeated academia, policymaking, business, NGOs, and the general public, leading to numerous applications of the concept, some of which only partially overlap. In this article, we review recent debates and research trends in the Circular Economy, outlining the ten most common groups of its conceptualizations using the PRISMA (Preferred Items for Systematic Reviews and Meta-Analysis) method. We then propose a post disciplinary and transnational research program on the Circular Economy that would not only combine hard and soft sciences in unprecedented ways but also have important practical applications, such as developing tools to embed the Circular Economy in natural, technical, economic, and socio-cultural settings.

Employing neural density functionals to generate potential energy surfaces.

With the union of machine learning (ML) and quantum chemistry, amid the debate between machine-learned functionals and human-designed functionals in density functional theory (DFT), this paper aims to demonstrate the generation of potential energy surfaces using computations with machine-learned density functional approximation (ML-DFA). A recent research trend is the application of ML in quantum sciences in the design of density functionals such as DeepMind's Deep Learning model (DeepMind21, DM21). Though science reported the state-of-the-art performance of DM21, the opportunity to utilize DeepMind's pretrained DM21 neural networks in computations in quantum chemistry has not yet been tapped. So far in the literature, the Deep Learning density functionals (DM21) have not been applied to generate potential energy surfaces. While the superior accuracy of DM21 has been reported, there is still a scarcity of publications that apply DM21 in calculations in the field. In this context, for the first time in literature, neural density functionals inferring 2D potential energy surfaces (ML-DFA-PES) based on machine-learned DFA-based computational method is contributed in this paper. This paper reports the ML-DFA-generated PES for C4H8, H2O, H2, and H2+ by employing a pretrained DM21m TensorFlow model with cc-pVDZ basis set. In addition, we also analyze the long-range behavior of DM21 based PES to investigate the ability to describe a system at long ranges. Furthermore, we compare PES diagrams from DM21 with popular DFT functionals (b3lyp/ PW6B95) and CCSD(T). In this method, 2D potential energy surfaces are obtained using a method that relies upon the neural network's ability to accurately learn the mapping between 3D electron density and exchange-correlation potential. By inserting Deep Learning inference in DFT with a pretrained neural network, self-consistent field (SCF) energy at different geometries along the coordinates of interest is computed, and then, potential energy surfaces are plotted. In this method, first, the electron density is computed mathematically, and this computed 3D electron density is used as a ML feature vector to predict the exchange correlation potential as a ML inference computed by a forward pass of pre-trained DM21 TensorFlow computational graph, followed by the computation of self-consistent field energy at multiple geometries, and then, SCF energies at different bond lengths/angles are plotted as 2D PES. We implement this in a python source code using frameworks such as PySCF and DM21. This paper contributes this implementation in open source. The source code and DM21-DFA-based PES are contributed at https://sites.google.com/view/MLfunctionals-DeepMind-PES .

Recent Research Trends for Metal Oxide Nanostructures Based Chemoresistive Gas Sensors

In the modern era, advanced industrial and process technologies in various fields are known to produce harmful gases. These gases typically leak at low concentrations, but continuous exposure can cause serious harm to health and safety. Since human sensory organs cannot detect these risks or leaking hazardous gases, there has been significant interest in developing high-performance gas sensors capable of rapidly detecting harmful and hazardous gas leaks. Metal oxides possess several advantages for such applications, including ease of manufacturing, affordability, and high sensitivity to harmful gases. In this review, we highlight recent progress in the field of chemo-resistive gas sensors based on metal-oxide nanostructures. It begins by discussing the features of various nanostructure morphologies such as 0-dimensional nanospheres to nanocomposites of nanowires. It then describes methods for fabricating metal-oxide nanostructures. Finally, we describe recent advances in the design and fabrication of nanostructures for metal-oxide gas sensors using four different morphologies: 0-dimensional (0 D, nanosphere and nanoparticle), 1-dimensional (1 D, nanowire and nanorod), 3-dimensional (3 D, nanoflower and nanocomposite), and heterojunctions. Based on their morphology-dependent sensing properties, there are various fields of application for gas sensors, with different target gases. This review can serve as an overview of recent research trends and offer insights into the future development of next-generation high-performance gas sensors.

Food security and sustainability dimensions of organic farming in the context of India: a comprehensive scientometric review (2010-2023).

The study investigated the scientific output, collaboration, and impression of research on organic farming due to the increasing interest of commoners in food quality and sustainability. Efforts to enhance agroecological sustainability call for assessing the structural overview of the numerous research works done so far to understand the growth in diverse subject areas in organic farming. The scientometric method is considered for analyzing 639 documents extracted from the Scopus and WoS online database from 2010 till January, 2023. The pulled-out data is analyzed via VOSviewer and RStudio, revealing prominent contributing authors (Groot J. with eight documents and 186 citations under Wageningen University and Research), maximum cited references (R Core Team& R lang env.2019), the significant collaboration between the countries (USA with Netherlands), and co-occurrence of author keywords ("organic farming" occurring 148 times) using analysis of co-authorship, co-occurrence, and citation count. Furthermore, as the existing literature suggests a substantial advancement in organic cultivation in India, thus, an immediate evaluation of its performance is necessitated. Hence, the current study performed the bibliographic coupling of documents, sources, authors, and global collaboration of India. The study found that a total of 241 Indian authors have contributed 102 documents in collaboration with 54 nations towards organic farming which are available in 39 different sources under the Scopus and WoS databases. This study helps to comprehend the recent growth trend of organic agricultural research and can enhance academic as well as research and development policies based on brainstorming to action formulation.

학문 목적의 한국어 읽기 교육 연구 동향 분석

The purpose of this thesis is to examine the research trends related to reading education in the Korean language curriculum for academic purposes and to find a systematic and efficient educational direction for reading education through this. For this discussion, this article analyzed master's and doctoral dissertations on Korean reading education published in 2011-2021. In language education, reading can be
 said to be a key area directly connected to the achievement of language education. Despite the importance of learning, the results of reading education are to identify and analyze recent trends in educational research for international students by conducting trend analysis on master's and doctoral dissertations on the subject of reading Korean for international students. To this end, data on doctoral dissertations published from 2011 to 2021 were collected through the Academic Research Information Service (RISS), and 32 collected papers were classified into 'education theory, education plan, curriculum, educational materials, learning patterns, and learner variables'. And based on this, the distribution and trend of reading education research for international students were identified. Based on the final analysis results, the direction of future reading education research for international students was suggested, and the limitations of this study were also described.

Recent Domestic and International Clinical Research Trends in Gua Sha Therapy: A Scoping Review

Recent Domestic and International Clinical Research Trends in Gua Sha Therapy: A Scoping Review

Editorial for Clean Energy Science and Technology (Volume 1 Issue 2)

In the era of industrial revolution, from powering factories to keeping our digital world humming, energy resources are the hidden engine behind modern economic activity, fueling production, transportation, and every click of a keyboard[1]. However, these commercial endeavors generate contaminants and toxins, which are extremely harmful for the environment and public health. To overcome these concerns, the utilization of clean energy is the main focus to enhance the economic growth and environmental preservation. During this time, many researchers and academicians are pivoted to study and research on clean energy technologies. Their successful research work helped us in publishing one commentary and six review articles, centered around the efficient use of resources, sustainable development, and environmental protection, in issue 2, volume 1 of this journal. It offers readers an overview of the most recent research trends in clean energy technology.

The peroxisome: an update on mysteries 3.0.

Peroxisomes are highly dynamic, oxidative organelles with key metabolic functions in cellular lipid metabolism, such as the β-oxidation of fatty acids and the synthesis of myelin sheath lipids, as well as the regulation of cellular redox balance. Loss of peroxisomal functions causes severe metabolic disorders in humans. Furthermore, peroxisomes also fulfil protective roles in pathogen and viral defence and immunity, highlighting their wider significance in human health and disease. This has sparked increasing interest in peroxisome biology and their physiological functions. This review presents an update and a continuation of three previous review articles addressing the unsolved mysteries of this remarkable organelle. We continue to highlight recent discoveries, advancements, and trends in peroxisome research, and address novel findings on the metabolic functions of peroxisomes, their biogenesis, protein import, membrane dynamics and division, as well as on peroxisome-organelle membrane contact sites and organelle cooperation. Furthermore, recent insights into peroxisome organisation through super-resolution microscopy are discussed. Finally, we address new roles for peroxisomes in immune and defence mechanisms and in human disorders, and for peroxisomal functions in different cell/tissue types, in particular their contribution to organ-specific pathologies.

Genre Awareness in Teaching Writing: A Case Study of Public High School Teachers in Nepal

Recent research trends on Teaching English as a Foreign or Second Language (EFL/ESL) have shown that conscious knowledge of the genre-based approach significantly enhances genre awareness in teaching writing in EFL/ESL contexts. This research examines how English language teachers in Nepal strengthen their understanding of genre awareness by integrating genre-based writing activities such as story writing, job application writing, journal writing, email writing, and essay writing within a high school teaching context. Based on the data generated from semi-structured interviews with four teachers and analysis of students’ written artifacts, the study indicates that teachers’ awareness of genre plays a prominent role in enhancing their self-reflection and academic writing skills. This awareness is shown to positively impact their understanding of pedagogical content knowledge and genre-specific writing conventions. However, the findings also demonstrate that the teacher participants possess unconscious familiarity with the genre, especially in terms of writing instruction and analyzing the genre-specific content in classroom teaching, since they appeared to lack awareness of the complex nature of the interactions between their belief systems, real-world classroom practices, and current educational and sociocultural needs. The study suggests that teachers’ pedagogical content knowledge of genres, reflective practices based on the learning achievements of learners, and ongoing genre-based teacher training, including workshops and seminars, should be organized to enhance their conscious awareness and understanding of the intricate nature of genre-based writing instruction.

Visualizing the evolution of touchscreen research by scientometric analysis

PurposeThis study aims to present recent trends in touchscreen research through scientometric analysis. Devices with touchscreen are powerful tools for performing specialized operations. The touch screens of tablets, smartphones, laptops and television play an important role in teaching, learning and research.Design/methodology/approachThe data was collected from Web of Science database from 2011 to 2021 and analysed using MS-Excel and VOSviewer software. After analysing 389 research papers, the authors identified the high impact journals, collaboration of countries, institutions, authors and growth trend of publications. Analysing the most used keywords, country-wise distribution of publications and research collaboration between institutions will help interpret the research trends in the selected time span.FindingsThe publications show an increase in number over the years from 2011 to 2021. Among the countries, USA has the highest number of 127 articles published, followed by England (61) and Canada (30). The results showed that the multiple authorship pattern in touchscreen publication is high when compared to single authors. The institutional analysis indicated that the organizations publishing more than five documents in the area were mostly from United Kingdom, Australia, USA and Korea. Timeline visualizations identified prominent keywords like touchscreen, performance, operant platform, Alzheimer’s disease, etc. in the subject. Interdisciplinary research is dominant in the subject, as seen from the most preferred journals and keywords.Research limitations/implicationsThe analysis does not include a comprehensive coverage of the research output, as only Web of Science database from 2011 to 2021 in a 10-year period is included.Practical implicationsThe study would benefit stakeholders, including manufacturers and researchers alike, to know the future of touchscreen research.Social implicationsThis study is pertinent to socio-psychological fields because touchscreen technology encourages social connection among older persons and may help foster early literacy skills.Originality/valueThis paper will provide an understanding of the global developments in touchscreen research with recommendations for future research.

An Emerging Foodborne Pathogen Spotlight: A Bibliometric Analysis and Scholarly Review of Escherichia coli O157 Research.

Foodborne infections pose a substantial global threat, causing an estimated 600 million illnesses and resulting in approximately 420,000 deaths annually. Among the diverse array of pathogens implicated in these infections, Escherichia coli (E. coli), specifically the O157 strain (E. coli O157), emerges as a prominent pathogen associated with severe outbreaks. This study employs a comprehensive bibliometric analysis and scholarly review focused on E. coli O157 research. The bibliometric analysis highlights the significant role played by the United States in the E. coli O157 research domain. Further exploration underscores the noteworthy contributions of the researcher Doyle MP, whose body of work, consisting of 84 documents and an impressive H-Index of 49, reflects their substantial impact in the field. Recent research trends indicate a discernible shift towards innovative detection methods, exemplified by the adoption of CRISPR-CAS and Loop-Mediated Isothermal Amplification. Moreover, high-throughput whole-genome sequencing techniques are gaining prominence for the expeditious analysis of pathogenic E. coli strains. Scientists are increasingly exploring antimicrobial agents, including phage therapy, to address the challenges posed by antibiotic-resistant E. coli strains, thereby addressing critical concerns related to multi-drug resistance. This comprehensive analysis provides vital insights into the dynamic landscape of E. coli O157 research. It serves as a valuable resource for researchers, policymakers, and healthcare professionals dedicated to mitigating E. coli O157 outbreaks and advancing global public health strategies.

Joint Special Issue: Advances in Design and Manufacturing for Sustainability

Abstract This special issue presents a collaborative initiative between the ASME Manufacturing Engineering Division (MED) and the Design Engineering Division (DED) to promote research in sustainability within the design and manufacturing communities. As the need grows for methodologies and tools capable of supporting sustainable systems, this compilation presents recent research trends exploring the integration of sustainability principles into and progression towards sustainability goals by the design and implementation of engineered systems.

Joint Special Section: Advances in Design and Manufacturing for Sustainability

Abstract This special issue presents a collaborative initiative between the ASME Manufacturing Engineering Division (MED) and the Design Engineering Division (DED) to promote research in sustainability within the design and manufacturing communities. As the need grows for methodologies and tools capable of supporting sustainable systems, this compilation presents recent research trends exploring the integration of sustainability principles into and progression towards sustainability goals by the design and implementation of engineered systems.

A Lightweight Arbitrarily Oriented Detector Based on Transformers and Deformable Features for Ship Detection in SAR Images

Lightweight ship detection is an important application of synthetic aperture radar (SAR). The prevailing trend in recent research involves employing a detection framework based on convolutional neural networks (CNNs) and horizontal bounding boxes (HBBs). However, CNNs with local receptive fields fall short in acquiring adequate contextual information and exhibit sensitivity to noise. Moreover, HBBs introduce significant interference from both the background and adjacent ships. To overcome these limitations, this paper proposes a lightweight transformer-based method for detecting arbitrarily oriented ships in SAR images, called LD-Det, which excels at promptly and accurately identifying rotating ship targets. First, light pyramid vision transformer (LightPVT) is introduced as a lightweight backbone network. Built upon PVT v2-B0-Li, it effectively captures the long-range dependencies of ships in SAR images. Subsequently, multi-scale deformable feature pyramid network (MDFPN) is constructed as a neck network, utilizing the multi-scale deformable convolution (MDC) module to adjust receptive field regions and extract ship features from SAR images more effectively. Lastly, shared deformable head (SDHead) is proposed as a head network, enhancing ship feature extraction with the combination of deformable convolution operations and a shared parameter structure design. Experimental evaluations on two publicly available datasets validate the efficacy of the proposed method. Notably, the proposed method achieves state-of-the-art detection performance when compared with other lightweight methods in detecting rotated targets.

Harnessing Natural Polymers for Nano-Scaffolds in Bone Tissue Engineering: A Comprehensive Overview of Bone Disease Treatment.

Numerous surgeries are carried out to replace tissues that have been harmed by an illness or an accident. Due to various surgical interventions and the requirement of bone substitutes, the emerging field of bone tissue engineering attempts to repair damaged tissues with the help of scaffolds. These scaffolds act as template for bone regeneration by controlling the development of new cells. For the creation of functional tissues and organs, there are three elements of bone tissue engineering that play very crucial role: cells, signals and scaffolds. For the achievement of these aims, various types of natural polymers, like chitosan, chitin, cellulose, albumin and silk fibroin, have been used for the preparation of scaffolds. Scaffolds produced from natural polymers have many advantages: they are less immunogenic as well as being biodegradable, biocompatible, non-toxic and cost effective. The hierarchal structure of bone, from microscale to nanoscale, is mostly made up of organic and inorganic components like nanohydroxyapatite and collagen components. This review paper summarizes the knowledge and updates the information about the use of natural polymers for the preparation of scaffolds, with their application in recent research trends and development in the area of bone tissue engineering (BTE). The article extensively explores the related research to analyze the advancement of nanotechnology for the treatment of bone-related diseases and bone repair.

An agenda for the future of Arctic snow research: the view from Svalbard

The Arctic region is warming at over twice the mean rate of the Northern Hemisphere and nearly four times faster than the globe since 1979. The local rate of warming is even higher in the European archipelago of Svalbard. This warming is transforming the terrestrial snow cover, which modulates surface energy exchanges with the atmosphere, accounts for most of the runoff in Arctic catchments and is also a transient reservoir of atmospherically deposited compounds, including pollutants. Improved observations, understanding and modelling of changes in Arctic snow cover are needed to anticipate the effects these changes will have on the Arctic climate, atmosphere, terrestrial ecosystems and socioeconomic factors. Svalbard has been an international hub of polar research for many decades and benefits from a well-developed science infrastructure. Here, we present an agenda for the future of snow research in Svalbard, jointly developed by a multidisciplinary community of experts. We review recent trends in snow research, identify key knowledge gaps, prioritize future research efforts and recommend supportive actions to advance our knowledge of present and future snow conditions pertaining to glacier mass balance, permafrost, surface hydrology, terrestrial ecology, the cycling and fate of atmospheric contaminants, and remote sensing of snow cover. This perspective piece addresses issues relevant to the circumpolar North and could be used as a template for other national or international Arctic research plans.