Research In Field Research Articles

Textual Metafunction in The Choir Traditional Spiritual Song “Elijah Rock” By Moses Hogan

This research explores the textual metafunction of the choir song "Elijah Rock" by Moses Hogan through the lens of Systemic Functional Linguistics (SFL), employing Suzanne Eggins' model of analysis. By examining the song's lyrical structure, the study aims to uncover how thematic organization, cohesion, and information flow contribute to the overall meaning and emotional impact of the piece. The analysis identifies key thematic elements, such as the recurring motif of "Elijah," as topical theme; the use of other topical themes such as: “come on”, “tell”, “comin’ up”, “Satan”; “He”; and “I”; the use of textual theme “if” and “Oh” highlights the extensive use of repetition and parallelism, which enhance textual coherence. Through a qualitative content analysis, the research demonstrates how linguistic features not only create a unified text but also resonate with the cultural and historical significance of African American spirituals. The findings reveal that the interplay between textual structure and musical expression plays a vital role in conveying the song's message and engaging audiences. This study contributes to the growing body of literature on the intersection of linguistics and music, offering valuable insights for future research in both fields.

Some novel Dice similarity measures for picture fuzzy sets and their applications

The similarity measures, as an important tool for assessing the similarity between picture fuzzy sets, have attracted the attention of numerous scholars and achieved rich achievements. Although existing similarity measures have exhibited their unique research contributions, they still fail to distinguish between highly similar but different picture fuzzy sets. This phenomenon poses a major challenge in applications, limiting our ability to make accurate judgments in scenarios that necessitate meticulous differentiation of picture fuzzy sets. Furthermore, the current research focuses on proposing individual and specific calculation formulas, particularly in the realm of Dice similarity measures. However, the systematic, uniform construction of Dice similarity measures remains mostly untapped. The main objective of this article is to propose a method for constructing Dice similarity measures. Through this approach, we can not only integrate existing Dice similarity measures into a unified framework, but also generate novel similarity measures. Firstly, we introduce a function that satisfies specific conditions as the basis for constructing Dice similarity measures. Secondly, by selecting different functions, we obtain various similarity measures. Finally, we propose the pattern recognition algorithm, the face recognition algorithm and the cluster analysis algorithm, all based on the proposed similarity measures. These algorithms are then applied to various fields, including pattern recognition, face recognition, and clustering analysis. Experimental results demonstrate that the proposed similarity measures not only compensate for the shortcomings of existing similarity measures but also exhibit high reliability and practicality, offering a powerful new tool for research and applications in related fields.

Retail futures: Customer experience, phygital retailing, and the Experiential Retail Territories perspective

This paper contributes to the existing literature on the evolution of the physical retail space and its effect on customer experience (CX). Reflecting on previous research in the retail CX field, we explore the impact of accelerated change on the role of physical stores and the likely progression of CX management in the context of integrated physical and digital channels in the fashion retail domain. Qualitative exploratory research was conducted with industry experts using semi-structured interviews to reveal insights and projections regarding phygital retail and CX evolution. The Experiential Retail Territories (ERT) framework is introduced as a new perspective on the future of fashion retailing.

Glial Control of Cortical Neuronal Circuit Maturation and Plasticity.

The brain is a highly adaptable organ that is molded by experience throughout life. Although the field of neuroscience has historically focused on intrinsic neuronal mechanisms of plasticity, there is growing evidence that multiple glial populations regulate the timing and extent of neuronal plasticity, particularly over the course of development. This review highlights recent discoveries on the role of glial cells in the establishment of cortical circuits and the regulation of experience-dependent neuronal plasticity during critical periods of neurodevelopment. These studies provide strong evidence that neuronal circuit maturation and plasticity are non-cell autonomous processes that require both glial-neuronal and glial-glial cross talk to proceed. We conclude by discussing open questions that will continue to guide research in this nascent field.

Impact of RNA Enzymes and RNA Protein Complexes in Unleashing RNAInterference for Manyfold Crop Improvements: A Review

RNA interference, which enables more accurate downregulation of gene expression without interfering with the expression of various genes, is a beneficial instrument for gene silencing and a potential gene regulatory strategy in functional genomics that has a big impact on crop progress. Small interfering RNA molecules swift up the RNAi gene silencing machinery, effectually suppressing a target gene. Subsequently transgene proteins not present from genetically modified RNAi plants, it has a sum of rewards over orthodox transgenic methods. Dicer, Drosha which are RNA enzymes, along with protein complexes, RISC and Argonaute, institute at the epicenter of this technology. These explicit RNA binding proteins and ribonucleases regulate the synthesis and production of tiny regulating RNAs. Several latent usages for this ground-breaking process in agriculture have been identified for improving crops, such as the construction of disease-resistant, biotic or abiotic, high-yielding, stress-tolerant and exclusive assortments; enhancement of nutritional quality; removal of allergens and toxins; and postponing the ripening of fruits and vegetables for extended storage periods. This ground-breaking procedure has the latent to be further utilized to pave the way for the creation of environmentally friendly biotech methods for crop protection and enhancement. Improving research and development activities in this auspicious field is imperative to ensure the efficient appropriate and safe application of these instruments as enduring remedies for agricultural enhancement.

Research trends of computational toxicology: a bibliometric analysis.

Computational toxicology utilizes computer models and simulations to predict the toxicity of chemicals. Bibliometric studies evaluate the impact of scientific research in a specific field. A bibliometric analysis of the computational methods used in toxicity assessment was conducted on the Web of Science between 1977 and 2024 February 12. Findings of this study showed that computational toxicology has evolved considerably over the years, moving towards more advanced computational methods, including machine learning, molecular docking, and deep learning. Artificial intelligence significantly enhances computational toxicology research by improving the accuracy and efficiency of toxicity predictions. Generally, the study highlighted a significant rise in research output in computational toxicology, with a growing interest in advanced methods and a notable focus on refining predictive models to optimize drug properties using tools like pkCSM for more precise predictions.

Spatial lung imaging in clinical and translational settings.

For many severe lung diseases, non-invasive biomarkers from imaging could improve early detection of lung injury or disease onset, establish a diagnosis, or help follow-up disease progression and treatment strategies. Imaging of the thorax and lung is challenging due to its size, respiration movement, transferred cardiac pulsation, vast density range and gravitation sensitivity. However, there is extensive ongoing research in this fast-evolving field. Recent improvements in spatial imaging have allowed us to study the three-dimensional structure of the lung, providing both spatial architecture and transcriptomic information at single-cell resolution. This fast progression, however, comes with several challenges, including significant image file storage and network capacity issues, increased costs, data processing and analysis, the role of artificial intelligence and machine learning, and mechanisms to combine several modalities. In this review, we provide an overview of advances and current issues in the field of spatial lung imaging.

GBKPA and AuxShield: Addressing adversarial robustness and transferability in android malware detection

Android stands as the predominant operating system within the mobile ecosystem. Users can download applications from official sources like Google Play Store and other third-party platforms. However, malicious actors can attempt to compromise user device integrity through malicious applications. Traditionally, signatures, rules, and other methods have been employed to detect malware attacks and protect device integrity. However, the growing number and complexity of malicious applications have prompted the exploration of newer techniques like machine learning (ML) and deep learning (DL). Many recent studies have demonstrated promising results in detecting malicious applications using ML and DL solutions. However, research in other fields, such as computer vision, has shown that ML and DL solutions are vulnerable to targeted adversarial attacks. Malicious actors can develop malicious adversarial applications that can bypass ML and DL based anti-viruses. The study of adversarial techniques related to malware detection has now captured the security community’s attention. In this work, we utilise android permissions and intents to construct 28 distinct malware detection models using 14 classification algorithms. Later, we introduce a novel targeted false-negative evasion attack, Gradient Based K Perturbation Attack (GBKPA), designed for grey-box knowledge scenarios to assess the robustness of these models. The GBKPA attempts to craft malicious adversarial samples by making minimal perturbations without violating the syntactic and functional structure of the application. GBKPA achieved an average fooling rate (FR) of 77 % with only five perturbations across the 28 detection models. Additionally, we identified the most vulnerable android permissions and intents that malicious actors can exploit for evasion attacks. Furthermore, we analyse the transferability of adversarial samples across different classes of models and provide explanations for the same. Finally, we proposed AuxShield defence mechanism to develop robust detection models. AuxShield reduced the average FR to 3.25 % against 28 detection models. Our findings underscore the need to understand the causation of adversarial samples, their transferability, and robust defence strategies before deploying ML and DL solutions in the real world.

Research Progress of Breath Sound Analysis for Common Respiratory Diseases in Children

Breath sounds can reflect the physiological and pathological conditions of the lungs and airways.Due to the differences in acoustic characteristics of breath sounds between healthy children and those with different respiratory diseases,analyzing breath sounds may provide important information for the diagnosis and treatment of respiratory diseases in children.With the development of digital auscultation,children's breath sounds have gradully become a research focus.This article summarizes the recent research progress in breath sound analysis for the diagnosis and treatment of common respiratory diseases in children,offering reference for the research in related fields.

Nanopore ultra-long sequencing and adaptive sampling spur plant complete telomere-to-telomere genome assembly

The pursuit of complete telomere-to-telomere (T2T) genome assembly in plants, challenged by genomic complexity, has been advanced by Oxford Nanopore Technologies (ONT), which offers ultra-long, real-time sequencing. Despite its promise, sequencing length and gap filling remain significant challenges. This study optimized DNA extraction and library preparation, achieving DNA lengths exceeding 485 kb; average N50 read lengths of 80.57 kb, reaching up to 440 kb; and maximum reads of 5.83 Mb. Importantly, we demonstrated that combining ultra-long sequencing and adaptive sampling can effectively fill gaps during assembly, evidenced by successfully filling the remaining gaps of a near-complete Arabidopsis genome assembly and resolving the sequence of an unknown telomeric region in watermelon genome. Collectively, our strategies improve the feasibility of complete T2T genomic assemblies across various plant species, enhancing genome-based research in diverse fields.

Two-stage estimation of hourly diffuse solar radiation across China using end-to-end gradient boosting with sequentially boosted features

Diffuse solar radiation (DR) constitutes a vital component of solar energy reaching the surface of the Earth. The demand for extensive temporal and spatial coverage of DR data has intensified in the realms of solar energy harvesting, agriculture, and climate change. However, until now, long-term DR observations have only been available from 17 stations across mainland China. Consequently, there is a pressing need to estimate spatially continuous, high-temporal-resolution DR for large-scale regions in China. The current hindrance to DR estimations stems from the scarcity of stations equipped with DR observations. This study proposes a two-stage strategy to efficiently estimate seamless DR in 2019 at a national scale, leveraging both DR and total solar radiation (TR) observations from numerous stations. In the first stage, the approach generates virtual DR at TR stations by establishing a learned relationship between DR and TR observations. Subsequently, in the second stage, these virtual DR data, in conjunction with satellite and reanalysis datasets, are utilized to estimate national-scale DR. Additionally, a novel model, End-to-end Gradient Boosting with Shortcuts and Feature selection (EGB-SF), is introduced to estimate DR over China. One advantage of this model is its consideration of the impact of sequentially boosted features and their interactions. Embedded shortcut connections fully exploit the influence of existing features on newly introduced ones during the learning process. Beyond enhancing the accuracy of DR estimation, the EGB-SF algorithm can also elucidate the relative importance levels of input features to the model. Moreover, the two-stage strategy outperforms the method of estimating national DR using only DR observations, as evidenced by its superior spatial generalization abilities. Statistical evaluation, collaborative analysis with influencing factors, and comparisons with related products confirm the accuracy and spatial continuity of the DR estimations in this study. These results furnish reliable DR data across China for research in agriculture, climate, solar radiation, and related fields.

Membrane Permeability and Drug Targeting Potential of Phospholipid‐Based Nanocarriers in Lung Cancer Therapy

AbstractLung cancer has become the leading cause of cancer‐related deaths, surpassing all other forms of cancer. Among lung cancers, non‐small cell lung cancer (NSCLC) accounts for approximately 85% of cases. The use of tobacco, genetic traits, and radiation exposure are amongst the major reasons of lung cancer. The ongoing research in the medical field has considered the efficacy of nanocarriers in targeting various cancer cells. Among several biomaterials, lipid‐based nanocarriers have gained special attention due to their excellent compatibility, improved targeting efficacy, and encapsulation ability of diverse therapeutic agents. Phospholipids are naturally occurring amphiphilic moieties found in all living creatures. The presence of phospholipids in biomembrane aids the permeability of phospholipid‐based drug carrier. It can also facilitate targeting of therapeutic agents to cancer microenvironment without degrading the encapsulated drug. Phospholipids can be employed to develop conjugated nanocarriers and vesicular nanoformulation that can result in prolonged circulatory half‐life and controlled release of drugs. Phospholipids are also suitable biomaterials to attach a ligand for tissue‐specific targeting. Recent researches have reported effective targeting of chemotherapeutic agents, genes, and vaccines through phospholipid‐based nanocarriers to lung cancer cells. This review focuses on the rationality and applications of phospholipid‐based nanocarriers in lung cancer therapy.

Evolving Memristive Reservoir.

In light of the dynamic plasticity, nanosize, and energy efficiency of memristors, memristive reservoirs have attracted increasing attention in diverse fields of research recently. However, limited by deterministic hardware implementation, hardware reservoir adaptation is hard to realize. Existing evolutionary algorithms for evolving reservoirs are not designed for hardware implementation. They often ignore the circuit scalability and feasibility of the memristive reservoirs. In this work, based on the reconfigurable memristive units (RMUs), we first propose an evolvable memristive reservoir circuit that is capable of adaptive evolution for varying tasks, where the configuration signals of memristor are evolved directly avoiding the device variance of the memristors. Second, considering the feasibility and scalability of memristive circuits, we propose a scalable algorithm for evolving the proposed reconfigurable memristive reservoir circuit, where the reservoir circuit will not only be valid according to the circuit laws but also has the sparse topology, alleviating the scalability issue and ensuring the circuit feasibility during the evolution. Finally, we apply our proposed scalable algorithm to evolve the reconfigurable memristive reservoir circuits for a wave generation task, six prediction tasks, and one classification task. Through experiments, the feasibility and superiority of our proposed evolvable memristive reservoir circuit are demonstrated.

The Influence of Digital Marketing and Service Quality on Customer Loyalty among Gojek Users (Case Study of FISIP Students at Riau University)

This research aims to identify and analyze the influence of digital marketing and service quality on customer loyalty among Gojek users, with a focus on students at the Faculty of Social and Political Sciences (FISIP) at Riau University. The research method used was a survey using a questionnaire distributed to respondents who were Gojek users among FISIP students at Riau University. The data analysis technique used is multiple linear regression. The results of this research show that digital marketing has a significant influence on customer loyalty among Gojek users among FISIP students at Riau University. Apart from that, service quality also has a significant influence on customer loyalty among Gojek users among FISIP students at Riau University. Thus, it can be concluded that both digital marketing and service quality have an important role in forming customer loyalty on the Gojek platform among FISIP students at Riau University. It is hoped that the findings from this research can contribute to the development of digital marketing strategies and improve service quality for Gojek and other similar companies in increasing customer loyalty, especially among FISIP students at Riau University and can also be a reference for further research in the same field.

HERITAGE TOURISM: A BIBLIOMETRIC ANALYSIS OVER THREE DECADES (1994-2023)

This qualitative study explores the relationship between tourism and places recognized by UNESCO as World Heritage Sites, whether tangible (WHS) or intangible (ICH). In the last two decades there has been a growth in the number of resources with UNESCO recognition. It aims to fill the research gap in the analysis of heritage tourism using bibliometric techniques. Data were collected from 886 documents in the period 1994-2023 (December) from the Web of Science database. Using the VOSviewer software, scientific maps were created showing the current and future line of research in this scientific field. The results show evidence of related research on Tourism sustainability at UNESCO sites in China and Tourism sustainability of cultural heritage for the whole period. In addition, two new research topics from 2016 are identified: Motivation and satisfaction of heritage tourists and Authenticity of intangible heritage. The results help to visualise the structure and trends of heritage tourism research, which can help researchers, policy makers and destination marketing organisations (DMOs) to gain knowledge and understanding of existing studies and current research topics.

The Procedure of an International Student Studying Abroad: A Case Study

As it is examined and concluded by many researchers, studying abroad has been common when students are trying to receive higher quality education. Cross-cultural adjustment is also regarded as a compulsory term to consider, and the way to get involved in the host culture has also been deeply investigated in this procedure. Therefore, this paper aims at identifying the factors that cause cultural barriers, as well as finding solutions to cope with them. In this study, a case study research method is employed and the result will be beneficial to support future research in similar fields.

Methodology of legal research in the security field

The relevance of the study lies in the fact that in the context of armed aggression against Ukraine, the most scientifically relevant issues are those related to the security and defense sector, and the development of effective practical recommendations in this area is impossible without proper theoretical substantiation. The purpose of the study was to determine certain aspects of the use of methodological tools in conducting legal research in this area. To achieve its purpose and objectives, the author used general scientific and special research methods. The main results of the study are the argumentation of the position that at the present stage, the most reliable and objective legal knowledge should be considered that which involves the use of special methods, techniques and compliance with the principles of knowledge acquisition. Today, the system of legal sciences is gradually developing its own methodology based on the general scientific principles of knowledge; legal science forms it in close connection with and in accordance with the subject matter of research, reflecting the peculiarities of the object of study and its specifics. The security and defense sector, in turn, also requires a separate scientific approach and research tools, since the activities of the State in this sector, which are its exclusive prerogative, involve ensuring the sovereignty of the State, its independence in the international arena, and protection of the population on its territory. The conclusions of the study are that the system of legal sciences in Ukraine is gradually developing its own methodology in accordance with the peculiarities of the object under study and the area in which it realizes its tasks. The research is devoted to the study of an issue which is of topical importance both for the practical activities of state bodies performing functions in the security and defense sector and for further scientific research.

Innovative Trends in Modified Membranes: A Mini Review of Applications and Challenges in the Food Sector.

Membrane technologies play a pivotal role in various industrial sectors, including food processing. Membranes act as barriers, selectively allowing the passage of one or other types of species. The separation processes that involve them offer advantages such as continuity, energy efficiency, compactness of devices, operational simplicity, and minimal consumption of chemical reagents. The efficiency of membrane separation depends on various factors, such as morphology, composition, and process parameters. Fouling, a significant limitation in membrane processes, leads to a decline in performance over time. Anti-fouling strategies involve adjustments to process parameters or direct modifications to the membrane, aiming to enhance efficiency. Recent research has focused on mitigating fouling, particularly in the food industry, where complex organic streams pose challenges. Membrane processes address consumer demands for natural and healthy products, contributing to new formulations with antioxidant properties. These trends align with environmental concerns, emphasizing sustainable practices. Despite numerous works on membrane modification, a research gap exists, especially with regard to the application of modified membranes in the food industry. This review aims to systematize information on modified membranes, providing insights into their practical application. This comprehensive overview covers membrane modification methods, fouling mechanisms, and distinct applications in the food sector. This study highlights the potential of modified membranes for specific tasks in the food industry and encourages further research in this promising field.

Research on the Influence of Human Language on the Formation and Development of Thinking

The SapirWhorf Hypothesis has aroused great interest among anthropologists, linguists, and psychologists since its proposal. This article delves into the important role of human language in the formation, development, and application of thinking through the literature review and questionnaire survey. The main target of the study is the 0-50 year-old population whose native language is Chinese. An electronic questionnaire survey was conducted to reveal the close relationship between language and thinking. Research has found that language not only serves as a carrier of thinking but also plays a crucial role in shaping and driving the development of thinking. In this context, this article aims to systematically analyze the impact of language on thinking, in order to provide new perspectives and thoughts for research in related fields.

Use of information technologies in lean management: the case of Gazi University Research Center in Turkey

Purpose Sustainability and accessibility of education are the main purposes of educational institutions. Higher education institutions (HEIs) have been addressing these concerns through their distance education departments for years. Especially during and after the COVID-19 pandemic, HEIs encountered challenges related to productivity, escalating costs and decreasing user satisfaction with distance education. This study proposes the integration of new and suitable information technologies (ITs) into the steps of lean management (LM) implementation. It suggests that this approach will be highly effective and beneficial, providing solutions to the problems above in higher education (HE) field. The study aims to highlight the effectiveness and benefits of incorporating new and suitable ITs into the application stages of LM principles. Sample applications in HE will be provided to enhance understanding. Design/methodology/approach A model is introduced for researching new ITs and incorporating appropriate ones in the application steps of LM. This model has been applied and analyzed in two case studies at Gazi University for a more comprehensive understanding. Findings When examining periodic surveys and usage statistics from case studies, it becomes evident that implementing LM with the support of ITs reduces waste and enhances the quality of existing work. The success observed in the case studies was notably influenced by managers’ proficiency in business processes, experience in ITs, managerial skills and support from senior management. Practical implications This case study provides a roadmap and step-by-step implementation of LM with IT support for HEIs. The implementation process and results will also be guiding for other sectors. Originality/value There is a notable absence of significant studies on integrating ITs, which have become crucial in today’s context in the stages of LM implementation. This study is envisioned as a pioneering endeavor to address this gap in the literature. Notably, challenges exist in applying LM principles outside production sectors, and limited research has been conducted. This study aims to pave the way for further research in diverse fields by conducting a comprehensive case study in the realm of HE.