New Field Of Study Research Articles

Transitive reasoning: A high-performance computing model for significant pattern discovery in cognitive IoT sensor network

Current research on the Internet of Things (IoT) has given rise to a new field of study called cognitive IoT (CIoT), which aims to incorporate cognition into the designs of IoT systems. Consequently, the CIoT inherits specific attributes and challenges from IoT. The CIoT applications generate vast, diverse, constantly changing, and time-dependent data due to the billions of devices involved. The efficient operation of these CIoT systems requires the extraction of valuable insights from vast data sources in a computationally efficient manner. Therefore, this study proposes transitive reasoning to glean significant concepts and patterns from a 21.25-year environmental dataset. To reduce the effects of missing entries, the proposed methodology includes a grouping of data using probabilistic clustering and applying total variance regularization in the alternate direction method of multipliers (ADMM) to regularize the sensory data. As a result, noisy entries will be less conspicuous. Afterward, it calculates the transitional plausibility value for each cluster using the transited value and then turns it into binary data to create concept lattices. In addition, each concept that is formed is assigned a weight, and the concept with the largest transitive strength value is chosen, followed by calculating the mean value. Therefore, this pattern is seen as significant. Experimental results on 21.25-year environmental data show an accuracy of over 99.5%, outperforming competing methods, as shown by cross-validation using multiple metrics.

Generative artificial intelligence: a proactive and creative tool to achieve hyper-segmentation and hyper-personalization in the tourism industry

Purpose The purpose of this paper is to explore how GenAI can help companies achieve a higher level of hyper-segmentation and hyper-personalization in the tourism industry, as well as show the importance of this disruptive tool for tourism marketing. Design/methodology/approach This paper used the Web of Science and Google Scholar databases to provide updated studies and expert authors to explore GenAI in the tourism industry. Analysing hyper-segmentation and hyper-personalization modalities through GenAI and their new challenges for tourists, tourism cities and companies. Findings Findings reveal that GenAI technology exponentially improves consumers’ segmentation and personalization of products and services, allowing tourism cities and organizations to create tailored content in real-time. That is why the concept of hyper-segmentation is substantially focused on the customer (understood as a segment of one) and his or her preferences, needs, personal motivations and purchase antecedents, and it encourages companies to design tailored products and services with a high level of individual scalability and performance called hyper-personalization, never before seen in the tourism industry. Indeed, contextualizing the experience through GenAI is an important way to enhance personalization. Originality/value This paper also contributes to enhancing and bootstrapping the literature on GenAI in the tourism industry because it is a new field of study, and its functional operability is in an incubation stage. Moreover, this viewpoint can facilitate researchers and companies to successfully integrate GenAI into different tourism and travel activities without expecting utopian results. Recently, there have been no studies that tackle hyper-segmentation and hyper-personalization methodologies through GenAI in the tourism industry.

Manifestation of polystyrene microplastic accumulation in brain with emphasis on morphometric and histopathological changes in limbic areas of Swiss albino mice

The widespread problem of microplastic (MP) contamination is becoming a major threat to the globe. Although most of the research to date has concentrated on the physiological impacts of MPs exposure, a relatively new field of study is beginning to examine its effects on the behaviour and limbic regions of the brain. In this study, exposure to polystyrene MPs (PS-MPs) for acute and sub-chronic durations negatively affected cognition and induced anxiety-like behaviour in mice. PS-MPs were detected in vital organs of mice, including the brain, which induced neurobehavioural and pathological changes in the limbic system. Furthermore, morphometric analysis revealed a significant decrease in the total cell count in the Dentate Gyrus (DG) and Cornu Ammonis (CA) regions of the hippocampus. Signs of neuronal injury and dystrophic changes were observed in the cortex, amygdala, and hypothalamus, potentially affecting anxiety and fear responses. Our study thus provides insight into the effect of PS-MPs on the neurobiology of the brain’s limbic system and related behavioural alterations.

Nattokinase as an adjuvant therapeutic strategy for non-communicable diseases: a review of fibrinolytic, antithrombotic, anti-inflammatory, and antioxidant effects.

Nattokinase (NK) is the primary ingredient of natto, a traditional Asian food made from fermented soybean by Bacillus subtilis natto. Studies have shown that natto reduces the risk of cardiovascular disease (CVD) mortality due to its fibrinolytic and antithrombotic properties. A new field of studies also demonstrates that NK can mitigate molecular pathways related to inflammation and oxidative stress and can be considered an adjuvant strategy for use in many non-communicable diseases (NCDs). This paper is a narrative review of the literature. A search was conducted in PubMed and ScienceDirect up to July 2024. This review discusses the possible effects of NK on mitigating the common complications of NCDs, such as inflammation and oxidative stress. In addition, it provides an update on the most addressed areas related to NK's fibrinolytic and antithrombotic activities. Due to the fibrinolytic and antithrombotic activity of nattokinase, and more recently added to the anti-inflammatory and antioxidant effects, this enzyme can be used as a new adjuvant therapeutic strategy to mitigate inflammation and oxidative stress in NCDs, including CVD.

The Potential Use of Targeted Proteomics and Metabolomics for the Identification and Monitoring of Diabetic Kidney Disease.

Diabetic kidney disease (DKD) is a prevalent microvascular complication of diabetes mellitus and is associated with a significantly worse prognosis compared to diabetic patients without kidney involvement, other microvascular complications, or non-diabetic chronic kidney disease, due to its higher risk of cardiovascular events, faster progression to end-stage kidney disease, and increased mortality. In clinical practice, diagnosis is based on estimated glomerular filtration rate (eGFR) and albuminuria. However, given the limitations of these diagnostic markers, novel biomarkers must be identified. Omics is a new field of study involving the comprehensive analysis of various types of biological data at the molecular level. In different fields, they have shown promising results in (early) detection of diseases, personalized medicine, therapeutic monitoring, and understanding pathogenesis. DKD is primarily utilized in scientific research and has not yet been implemented in routine clinical practice. The aim of this review is to provide an overview of currently available data on targeted omics. After an extensive literature search, 25 different (panels of) omics were withheld and analyzed. Both serum/plasma and urine proteomics and metabolomics have been described with varying degrees of evidence. For all omics, there is still a relative paucity of data from large, prospective, longitudinal cohorts, presumably because of the heterogeneity of DKD and the lack of patient selection in studies, the complexity of omics technologies, and various practical and ethical considerations (e.g., limited accessibility, cost, and privacy concerns).

Evaluating the Impact of Social Media on Consumers’ Online Shopping Behavior: A Mediated-Moderation Model

Social commerce has rapidly become a new field of study for both professionals and academics, indicating the possible influence of social media in shaping online commercial avenues. People spend a significant amount of time on social media, presenting online businesses with the chance to gain a comprehensive understanding of their customers' shopping behaviors. Consequently, it is essential to explore the factors that affect consumers' online shopping behavior. This research, conducted in Indonesia, seeks to identify the factors influencing consumer online shopping behavior. Analyzing data from 375 customers, the study employs Smart PLS to explore the relationships within the proposed model. The results indicated that live streaming, promotional tools, celebrity endorsements and perceived credibility are factors that impact consumer online shopping behavior in social commerce. The study verified the mediating role of promotional tools. However, perceived credibility did not moderate the association amid promotional tools and consumer online shopping behavior. The findings offer clearer insights into the factors affecting consumer online shopping behavior, aiding entrepreneurs in developing more effective strategies. This research brings fresh perspectives on consumer online shopping behavior by examining it empirically within the Indonesian context. This is significant due to the previous lack of studies focused on consumer behavior in social commerce and the scarcity of empirical evidence in this area.

Content Analysis of Textbooks via Natural Language Processing

Purpose: Advanced methods from the field of data science have the potential to shed fresh light on basic concerns in the field of educational research. Natural language processing tools, such as lexicons, word embeddings, and topic models, are used in 15 United States history textbooks that were extensively used in Texas between the years 2015 and 2017. Material and Methods: This study aims to analyze these textbooks for their portrayal of historically oppressed populations. Latinx individuals are rarely mentioned, but renowned white men are almost always mentioned. People of African descent are characterized as behaving in ways that imply helplessness and lack of control, according to lexical methods. Women are most often addressed in the contexts of the home and the workplace, according to the word embeddings. Issues of a political rather than a social nature are highlighted by subject modeling. Findings: We also found that textbooks with a smaller representation of women and people of African heritage are more often purchased by conservative nations. Implications to Theory, Practice and Policy: Our computational toolkit has a rich history of textbook analysis and has recently been distributed as part of our efforts to support new fields of study.

Elevated levels of oxLDL and LOX-1: Implications for schizophrenia pathophysiology

Inflammation and oxidative stress are both considered to be factors in the etiopathogenesis of schizophrenia. LOX-1 (lectin-like oxidized low-density lipoprotein receptor-1) and ox-LDL (oxidized low-density lipoprotein) have been reported to be active in neuroinflammation pathways in which they are involved in oxidative stress and inflammation. However, its relationship with schizophrenia is unclear. This study aimed to assess the potential connection between serum ox-LDL and LOX-1 levels in schizophrenia patients, their unaffected first-degree relatives, and healthy controls. The study comprised 63 schizophrenia patients, 57 first-degree relatives, and 63 healthy controls who were age, gender, and BMI-matched. Serum ox-LDL and LOX-1 levels were measured. PANSS was used to assess the severity of the disease. Levels of both ox-LDL and LOX-1 were markedly elevated in individuals diagnosed with schizophrenia when compared to both their relatives and a control group. While ox-LDL levels were significantly higher in relatives of patients compared to controls, there was no significant difference between relatives of patients and control groups for LOX-1 levels. Significant correlations were observed between PANNS general and total and ox-LDL levels and PANNS negative and LOX-1 levels. The relationship between ox-LDL and LOX-1 and schizophrenia is quite limited in the literature and is a new field of study. Future studies are needed to evaluate their role in etiopathogenesis.

WHAT COGNITIVE NEUROSCIENCE SAY ABOUT AESTHETIC EXPERIENCE?

Today, researchers can observe the neural responses to an aesthetic image in the human brain and examine the physiological reactions of viewers to an art object. Neuroaesthetics is a new field of study that characterizes the evolutionary history of the creation and evaluation of art by examining these responses. Neuroscientists, who have managed to map the neural pathways of the visual processing processes that occur in a person's brain while watching artworks, have been focusing on how the visual cortex processes information and reaches aesthetic judgment in recent years. The focus of this research is how a work of art is perceived, how the visual cortex processes information when reaching aesthetic judgments, color perception, synesthesia, and finally, the effects of brain damage on artists. In the study, firstly, the visual-spatial processes, which are the basic processes of visual perception, were discussed. In this way, object perception and the visual processes occurring in the brain during the perception of the art object were examined. In the next section, which draws attention to the perception of color as well as shape and spatial location, synesthesia, which has been the subject of many studies by neuroscientists in recent years and is known as the perception of one sense together with another sense, is discussed. Finally, studies on brain-damaged artists, one of the experimental methods most preferred by neuroscientists in research on aesthetic perception, and the data obtained from these studies are presented.

A review of 2.45 GHz microstrip patch antennas for wireless applications

Recently, microstrip patch antennas have become popular. Due to their ubiquity, these antennas have more uses every day. In this research paper, a 2.45 GHz microstrip patch antenna has been reviewed and analyzed. Different substrate materials have been used to make these antennas, and their thickness is different. Various antennas are designed based on the application, such as rectangular, square, triangle, ring, donut, and dipole. Other types of software were used to design the antenna, including CST, HFSS, MATLAB, ADS, and FEKO. Microstrip patch antenna design is a relatively new field of study for wireless applications. Several devices are linked to send or receive radio waves using a single antenna. Antennas designed for 2.45 GHz are used in various wireless communication systems, including television broadcasts, microwave ovens, mobile phones, wireless local area network (WLAN), Bluetooth, global positioning system (GPS), and two-way radios. This article looks at the geometric structures of antennas, including their many parameters and materials and the many different shapes they can take. In addition, the substrate materials, the loss tangent, the thickness, the return loss, the bandwidth, the voltage standing wave ratio (VSWR), the gain, and the directivity of previous articles will also be discussed.

The Impact of Digital Advancements and Their Influence on Marketing, Value Chains, and Business Models

Although good mastery of digital innovations can be highly advantageous in today's environment, as business models and industries are changing rapidly due to digital innovations, there are significant gaps in the literature on digital innovations. By defining terms and examining the particulars of this new field of study, we add to the body of literature. The impact of digital innovation on marketing, value chain, and business models is then covered, with particular attention paid to conflicts and marketing difficulties, value chain dynamics, and business model evolutions. We offer recommendations for more research in our conclusion.

Bioinformatics Identification and Experimental Validation of a Prognostic Model for the Survival of Lung Squamous Cell Carcinoma Patients.

Lung squamous cell carcinoma (LUSC) kills more than four million people yearly. Creating more trustworthy tumor molecular markers for LUSC early detection, diagnosis, prognosis, and customized treatment is essential. Cuproptosis, a novel form of cell death, opened up a new field of study for searching for trustworthy tumor indicators. Our goal was to build a risk model to assess drug sensitivity, monitor immune function, and predict prognosis in LUSC patients. The 19 cuproptosis-related genes were found in the literature, and patient genomic and clinical information was collected using the Cancer Genomic Atlas (TCGA) database. The LUSC patients were grouped using unsupervised clustering techniques, and 7626 differentially expressed genes were identified. Using univariate COX analysis, LASSO regression analysis, and multivariate COX analysis, a prognostic model for LUSC patients was developed. The tumor immune escape was evaluated using the Tumor Immune Dysfunction and Exclusion (TIDE) method. The R packages 'pRRophetic,' 'ggpubr,' and 'ggplot2' were utilized to examine drug sensitivity. For modeling, a 6-cuproptosis-based gene signature was found. Patients with high-risk LUSC had significantly worse survival rates than those with low-risk conditions. The possibility of tumor immunological escape was increased in patients with higher risk scores due to more immune cell inactivation. For patients with high-risk LUSC, we discovered seven potent potential drugs (AZD6482, CHIR.99021, CMK, Embelin, FTI.277, Imatinib, and Pazopanib). In conclusion, the cuproptosis-based genes predictive risk model can be utilized to predict outcomes, track immune function, and evaluate medication sensitivity in LUSC patients.

Strategic Enterprise Artificial Intelligence (The Conceptual Hierarchical Framework)

This paper discusses three statements: Enterprise AI strategy must be linked with the existing business strategy of the organization, Enterprise AI must be a virtual strategist of the organization, and Enterprise AI must be a virtual strategy manager for organizational performance. Based on the research on these statements, this paper will introduce the conceptual hierarchical framework titled Strategic Enterprise Artificial Intelligence (SEAI) consisting of four levels: Disconnected Enterprise AI, Linked Enterprise AI, Strategist Enterprise AI, and Integrative Enterprise AI. Disconnected Enterprise AI represents the lowest level, while Integrative Enterprise AI is the highest. This framework, with its title, can be introduced as a new field of study. If the corporate sector uses this framework tactfully, it will help the organizations to strategize Enterprise AI to achieve business results.

Modulation of the Immune System Mechanisms using Probiotic Bacteria in Allergic Diseases: Focus on Allergic Retinitis and Food Allergies.

Allergic illnesses occur when an organism's immune system is excessively responsive to certain antigens, such as those that are presented in the environment. Some people suffer from a wide range of immune system-related illnesses including allergic rhinitis, asthma, food allergies, hay fever, and even anaphylaxis. Immunotherapy and medications are frequently used to treat allergic disorders. The use of probiotics in bacteriotherapy has lately gained interest. Probiotics are essential to human health by modulating the gut microbiota in some ways. Due to probiotics' immunomodulatory properties present in the gut microbiota of all animals, including humans, these bacterial strains can prevent a wide variety of allergic disorders. Probiotic treatment helps allergy patients by decreasing inflammatory cytokines and enhancing intestinal permeability, which is important in the battle against allergy. By altering the balance of Th1 and Th2 immune responses in the intestinal mucosa, probiotics can heal allergic disorders. Numerous studies have shown a correlation between probiotics and a reduced risk of allergy disorders. A wide range of allergic disorders, including atopic dermatitis, asthma, allergic retinitis and food allergies has been proven to benefit from probiotic bacteria. Therefore, the use of probiotics in the treatment of allergic diseases offers a promising perspective. Considering that probiotic intervention in the treatment of diseases is a relatively new field of study, more studies in this regard seem necessary.

Presenting a meta-heuristic solution for optimal resource allocation in fog computing

Given that cloud computing is a relatively new field of study, there is an urgent need for comprehensive approaches to resource provisioning and the allocation of Internet of Things (IoT) services across cloud infrastructure. Other challenging aspects of cloud computing include IoT resource virtualization and disseminating IoT services among available cloud resources. To meet deadlines, optimize application execution times, efficiently use cloud resources, and identify the optimal service location, service placement plays a crucial role in installing services on existing virtual resources within a cloud-based environment. To achieve load balance in the fog computing infrastructure and ensure optimal resource allocation, this work proposes a meta-heuristic approach based on the cat swarm optimization method. For more clarity in the difference between the work presented in this research and other similar works, we named the proposed technique MH-CSO. The algorithm incorporates a resource check parameter to determine the accessibility and suitability of resources in different situations. This conclusion was drawn after evaluating the proposed solution in the ifogsim environment and comparing it with particle swarm and ant colony optimization techniques. The findings demonstrate that the proposed solution successfully optimizes key parameters, including runtime and energy usage.

Hydrothermal zeolitization: Towards a paradigm shift for producing stronger and more sustainable construction materials

The construction sector provides 14.8 million jobs in the European Union. However, it also accounts for 36% of greenhouse gas emissions and 35% of total waste. High-temperature ceramic manufacturing consumes substantial energy, yielding basic structural products. The alternatives presented, such as geopolymers, still do not replace traditional materials and are not as sustainable as believed. This innovative study combines hydrothermal zeolitization with kaolin-based ceramics fired at both conventional (900°C) and much lower temperatures (600°C), exploring varied conditions, including the use of microplastic wastes as pore-forming agents. Significant zeolite crystallization (15–74%) and mechanical strength increase (2–37-fold compared to untreated materials) is demonstrated in granular specimens, especially when adding microplastics. Geopolymerization appears as a secondary process during treatment. This innovative method offers energy-efficient lower temperatures, transforming fired specimens into zeolite-enriched, robust materials, adaptable to current technology. This study paves the way for further research, opening up a new field of study on hydrothermally manufactured Zeolitic Construction Materials.

Research on SQL Injection Attacks using Word Embedding Techniques and Machine Learning

Most of the damage done by web application attacks comes from SQL injection attacks, in which the attacker(s) can change, remove, and read data from the database servers. All three tenets of security— confidentiality, integrity, and availability—are vulnerable to a SQL injection attack. Database management systems receive their queries in the form of SQL (structured query language). It is not a new field of study, but it is still important to detect and prevent SQL injection attacks. A method of SQL injection detection based on machine learning is proposed. Feature extraction, followed by implementing various word embedding techniques like count vectorizer, TFIDF vectorizer to process the text data which can effectively represent the SQLI features is performed. Classification algorithms like Logistic Regression, SVM and Ensemble techniques like XGBoost is employed. Our goal in doing this systematic review is to find a better machine learning model to detect SQL injection attacks via implementing different word embedding techniques. The accuracy and F1-score of machine learning algorithms in terms of predicting the SQLI query has been calculated and reported in this research paper.

Behavioral Finance: Understanding Investment Decisions Among Individual Investors

In the early 1990s, India started to open up to the outside world. Steep GDP growth has been facilitated by privatization, liberalization, and globalization together. An important aspect in this was the investors. As a result, the administration thought of enticing more investors. Sophisticated investors from all over the world started to pay more attention to the Indian capital markets, especially after 2003. In this instance, it is vital to examine the How, Why, When, Where, and Amount of the Investors’ Investments. A further tool for comprehending the decision-making process of investors is behavioral finance, a relatively new field of study. Emotions and psychology play a part in the way investors make financial decisions. It says that people are not foolish or illogical. They are common individuals with diverse prejudices. Numerous elements, such as personality and demography, can affect how risk and return on investment are evaluated. They can also have an impact on investor psychology and attitudes, investment selection, and decision-making processes. In this study, we look at how Bengaluru’s individual investors’ choice of investment instruments is influenced by their personalities and demographics. Frequency analysis along with other statistical methods were used to describe the variables. Only respondents who have invested in any form of financial instrument at least once are selected for the study.

A Metapragmatic Analysis of Iraqi and American Political Legal Discourse

Metapragmatics is a relatively new field of study that attracts the attention of many scholars in linguistics; it refers to the use of language about language use. In trials of political figures, such as Saddam Hussein and William Clinton, Iraqi and American legal discourses have not been addressed that much, if ever, metapragmatically; thus, the study aims to analyze these discourses metapragmatically. This paper attempts to answer central questions about identifying the metapragmatic expressions, explaining their functions, and describing the layers of metapragmatic monitoring of the detected metapragmatic expressions in the Iraqi and American legal discourse. Accordingly, the objectives are to identify the metapragmatic expressions detected by specific indicators and investigate their functions and role in monitoring the Iraqi and American broadcast political court discourses. Some extracts of the two figures mentioned above are analyzed according to a developed model encompassing Caffi’s (2016) model, Hubler and Bublitz’s (2007) metapragmatic parameters, and Culpuper and Haugh’s (2014) metapragmatic awareness indicators, and forms. The current study is hoped to be helpful for those researchers interested in the fields of pragmatics, politics, and applied linguistics. Since metapragmatics deals with the pragmatic meaning of language, this study highlights the importance of metapragmatic expressions in promoting productive interaction and organizing communication within the court, regardless of the language used. Further investigation of metapragmatics is recommended while analyzing political, literary, religious, social, and media discourse to understand the functions of the metapragmatic utterances used in different settings.

Biofilm Formation in Mycobacterial Genus; Mechanism of Biofilm Formation and Anti-Mycobacterial Biofilm Agents.

Mycobacterium tuberculosis, Mycobacterium leprae, and non-tuberculous mycobacteria (NTM) are among the most significant human pathogens within the Mycobacterium genus. These pathogens can infect people who come into contact with biomaterials or have chronic illnesses. A characteristic pathogenic trait of mycobacteria is the development of biofilms, which involves several molecules, such as the GroEL1 chaperone, glycopeptidolipids, and shorter-chain mycolic acids. Bacterial behavior is influenced by nutrients, ions, and carbon sources, which also play a regulatory role in biofilm development. Compared to their planktonic phase, mycobacterial biofilms are more resilient to environmental stresses and disinfectants. Mycobacteria that produce biofilms have been found in several environmental studies, particularly in water systems. NTM can cause respiratory problems in individuals with underlying illnesses such as cystic fibrosis, bronchiectasis, and old tuberculosis scars. Mycobacteria that grow slowly, like those in the Mycobacterium avium complex (MAC), or rapidly, like Mycobacterium abscessus, can be pathogens. Infections related to biomaterials represent a significant category of biofilm-associated infections, with rapidly growing mycobacteria being the most frequently identified organisms. A biofilm produced by M. tuberculosis can contribute to caseous necrosis and cavity formation in lung tissue. Additionally, M. tuberculosis forms biofilms on clinical biomaterials. Biofilm formation is a major contributor to antimicrobial resistance, providing defense against drugs that would typically be effective against these bacteria in their planktonic state. The antibiotic resistance of biofilm-forming microbes may render therapy ineffective, necessitating the physical removal of biofilms to cure the infection. Recently, new approaches have been developed with potential anti-biofilm compounds to increase treatment effectiveness. Understanding biofilms is crucial for the appropriate treatment of various NTM diseases, and the recent discovery of M. tuberculosis biofilms has opened up a new field of study. This review focuses on the biofilm formation of the Mycobacterial genus, the mechanisms of biofilm formation, and anti-mycobacterial biofilm agents.