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Background: Scientists have recently developed a technology that induces artificial taste through electronic stimulation. However, scattered reports have made it difficult to comprehensively understand the technology’s details and appreciate its potential applications in healthcare. To address these gaps, a meta-review was conducted. We re-viewed the current literatures on the technology behind artificial taste. Targeted original research papers were analyzed, with data extracted to address five key aspects: interface design, stimulation parameters, sensation verification results, applications to health problems, and potential side effects in human subjects. Results: A total of 19 relevant papers were identified. Eight studies focused on tongue-tip electrode interfaces, while others integrated technology into eating utensils. Eleven studies examined stimulation frequencies (50–1000 Hz), with five altering temperature and two changing water color to enhance taste perception. Only six studies reported verification results, showing that most participants perceived sour and salty tastes, mild bitter responses, and unreliable sweet evocation. Sixteen papers discussed applications in healthcare (dietary and weight management), entertainment (food and beverage sampling), and education. Side effects included reduced sensitivity after repeated trials and occasional discomfort from excessive stimulation, though no immediate tissue damage was reported. Conclusions: Artificial taste technology offers an innovative approach to managing food and beverage intake without compromising taste sensations. When applied on a large scale, it holds significant potential for regulating eating behaviors and providing novel strategies for addressing chronic health issues associated with diet. Full article

In the era of artificial intelligence (AI), economic efficiency has an obvious role to play, but “non-economic benefits” have gradually become the focus of corporate attention; thus, environmental, social, and governance (ESG) has become a mainstream investment strategy. This paper empirically examines the impact of corporate application of AI technology on corporate ESG performance using a sample of 4858 listed companies in China from 2007 to 2022. The study finds that: (1) corporate application of AI technology can significantly enhance corporate ESG performance, and this conclusion still holds after a series of endogeneity treatments and robustness tests; (2) mechanism analysis shows that the degree of corporate digitalization has a positive moderating effect in the process of AI technology affecting corporate ESG performance. The channel analysis shows that the application of AI technology can enhance environmental (E) performance by strengthening corporate green technology innovation, social (S) performance by improving corporate philanthropic responsibility, and overall ESG performance with the above two sub-items as the main aspects. However, AI technology also weakens the effectiveness of corporate internal control, which leads to a decline in corporate governance (G) performance; (3) Heterogeneity analysis shows that AI technology promotes ESG more significantly in more competitive industries and tech-nology-intensive firms, and more significantly in the eastern and central regions than in the western and northeastern regions, and that large- and medium-sized firms are similarly superior to small-sized firms, while medium-sized firms have more room for upward mobility than large-sized firms, which embody a higher promotion effect than large enterprises. This paper provides theoretical evidence that enterprises apply AI technology to improve ESG performance and empirical support around investing in ESG practices and promoting ESG development. Full article

The Gulf Cooperation Countries are rich in natural resources such as oil, yet they have serious environmental problems. These countries are also located in regions where there is abundance of sunshine, yet are not capitalizing on the use of solar energy—a clean source of fuel. They heavily rely on fossil fuels that are cheap and readily available in the region, causing serious environmental problems. This research investigates the role of trade, technology, and economic growth in improving environmental sustainability in this region; hence, covering the gap existing in the literature on how this region can address the problem of environmental sustainability. This research uses annual data of the Gulf Cooperation Countries for the period 1990 to 2022 and analyses it with the Methods of Moments Quantile Regression. The major findings presented in the research show the importance of technological innovations in ensuring the eradication of environmental deterioration. Technological innovation is observed to reduce environmental problems by 1.94 to 3.11 magnitude. The results also show that trade openness and natural resources rents fundamentally lower environmental deterioration in the long term by 0.02, and 0.05 to 0.09 magnitudes, respectively. However, the results show that economic growth, globalization, and financial development are harmful to environmental sustainability in this region. These factors tend to raise environmental damage by 0.14 to 0.24, 0.34 to 0.43, and 9.2 to 5.74 units on average, respectively. This research gives key policies towards advancing environmental sustainability through trade openness, natural resources rents, and technological innovation in the Gulf Cooperation Countries. Full article

Hydrogels are widely utilized in industrial and scientific applications owing to their ability to immobilize active molecules, cells, and nanoparticles. This capability has led to their growing use in various biomedical fields, including cell culture and transplantation, drug delivery, and tissue engineering. Among the available synthesis techniques, ionizing-radiation-induced fabrication stands out as an environmentally friendly method for hydrogel preparation. In alignment with the current requirements for cleaner technologies, developing hydrogels using gamma and electron beam irradiation technologies represents a promising and innovative approach for their biomedical applications. A key advantage of these methods is their ability to synthesize homogeneous three-dimensional networks in a single step, without the need for chemical initiators or catalysts. Additionally, the fabrication process is controllable by adjusting the radiation dose and dose rate. Full article

The widespread use of the internet, coupled with the increasing production of digital content, has caused significant challenges in information security and manipulation. Deepfake detection has become a critical research topic in both academic and practical domains, as it involves identifying forged elements in artificially generated videos using various deep learning and artificial intelligence techniques. In this dissertation, an innovative model was developed for detecting deepfake videos by combining the Quantum Transfer Learning (QTL) and Class-Attention Vision Transformer (CaiT) architectures. The Deepfake Detection Challenge (DFDC) dataset was used for training, and a system capable of detecting spatiotemporal inconsistencies was constructed by integrating QTL and CaiT technologies. In addition to existing preprocessing methods in the literature, a novel preprocessing function tailored to the requirements of deep learning models was developed for the dataset. The advantages of quantum computing offered by QTL were merged with the global feature extraction capabilities of the CaiT. The results demonstrated that the proposed method achieved a remarkable performance in detecting deepfake videos, with an accuracy of 90% and ROC AUC score of 0.94 achieved. The model’s performance was compared with other methods evaluated on the DFDC dataset, highlighting its efficiency in resource utilization and overall effectiveness. The findings reveal that the proposed QTL-CaiT-based system provides a strong foundation for deepfake detection and contributes significantly to the academic literature. Future research should focus on testing the model on real quantum devices and applying it to larger datasets to further enhance its applicability. Full article

Miniaturized solid-based approaches have added an eco-friendly dimension to analytical procedures, establishing themselves as promising strategies for a wide range of applications. Among these, microextraction by packed sorbent (MEPS) stands out due to its ability to facilitate efficient sample interaction with a densely packed sorb ent phase within the microextraction system. MEPS offers several advantages, including preconcentration capabilities and the use of minimal sample and solvent volumes, making it an appealing choice for modern analytical workflows. Since the extraction efficiency is largely dictated by the sorbent phase, recent advancements in sorbent design have garnered considerable attention in the field of sample preparation. Innovations in sorbent phases have not only enhanced the MEPS efficiency but also enabled the development of semi- and fully automated systems, paving the way for high-throughput methodologies. These advancements have elevated MEPS beyond traditional offline miniaturized sample preparation methods, offering new opportunities for streamlined and scalable analyses. Therefore, this study provides a comprehensive overview of novel sorbent phases used in MEPS, with a particular focus on both bio-based and synthetic materials. Furthermore, it explores the semi- and fully automated aspects of MEPS, highlighting current trends, technological advancements, and future directions in this rapidly evolving field. Full article

In the current tide of technological revolution and industrial transformation, digitalization and greening have surfaced as two prominent trends, serving as the inherent requisites and impelling forces of new productive forces. Augmenting carbon emission efficiency is a crucial pathway for attaining green development. Digital inclusive finance, as an innovative financial paradigm, is a significant determinant influencing carbon emission efficiency and the progression of green development. By harnessing panel data from 108 cities within the Yangtze River Economic Belt spanning from 2011 to 2021, this study deploys the super-efficiency SBM model to gauge carbon emission efficiency. Additionally, it employs fixed effects and mediating mechanism models to empirically scrutinize the impact of digital inclusive finance on carbon emission efficiency within urban agglomerations in the Yangtze River Economic Belt. The study further probes its spatial effects through a spatial Durbin model. The research findings disclose that digital inclusive finance can substantially augment carbon emission efficiency in regional cities along the Yangtze River Economic Belt, manifesting notable regional correlations. This enhancement is accomplished by propelling industrial structure upgrades and augmenting scientific and technological capabilities. To enhance carbon emission efficiency in the Yangtze River Economic Belt, efforts should be centered around advancing digital inclusive finance, expediting industrial structural transformation, and fortifying scientific and technological development. Full article

Artificial intelligence (AI) has transformed healthcare, yet patients’ acceptance of AI-driven medical services remains constrained. Despite its significant potential, patients exhibit reluctance towards this technology. A notable lack of comprehensive research exists that examines the variables driving patients’ resistance to AI. This study explores the variables influencing patients’ resistance to adopt AI technology in healthcare by applying an extended Ram and Sheth Model. More specifically, this research examines the roles of the need for personal contact (NPC), perceived technological dependence (PTD), and general skepticism toward AI (GSAI) in shaping patient resistance to AI integration. For this reason, a sequential mixed-method approach was employed, beginning with semi-structured interviews to identify adaptable factors in healthcare. It then followed with a survey to validate the qualitative findings through Structural Equation Modeling (SEM) via AMOS (version 24). The findings confirm that NPC, PTD, and GSAI significantly contribute to patient resistance to AI in healthcare. Precisely, patients who prefer personal interaction, feel dependent on AI, or are skeptical of AI’s promises are more likely to resist its adoption. The findings highlight the psychological factors driving patient reluctance toward AI in healthcare, offering valuable insights for healthcare administrators. Strategies to balance AI’s efficiency with human interaction, mitigate technological dependence, and foster trust are recommended for successful implementation of AI. This research adds to the theoretical understanding of Innovation Resistance Theory, providing both conceptual insights and practical implications for the effective incorporation of AI in healthcare. Full article

Information technology (IT) strategic planning plays a pivotal role in enhancing the performance of small and medium-sized enterprises (SMEs), improving operational efficiency and decision-making, and fostering innovation. This systematic review aims to synthesize the impacts of IT strategic planning on SME performance, focusing on key performance indicators such as operational efficiency, cost reduction, and customer satisfaction. A total of 80 studies were rigorously analyzed. Quantitative methods were used in 45% of the studies, while 25% applied thematic analysis. The adoption of cloud-based solutions (11.25%) and hybrid IT setups (17.5%) were also evaluated as critical enablers of flexibility and cost-efficiency. SMEs aligning their IT strategies with business objectives demonstrated up to a 20% reduction in operational costs and a 15% increase in customer satisfaction. Resource constraints were identified as a significant challenge in 60% of the studies. Nevertheless, effective IT planning contributed to long-term sustainability and competitive advantage in 60% of the reviewed studies. This review provides actionable insights and strategic frameworks to guide SMEs in optimizing their IT investments, overcoming resource limitations, and ensuring sustainable growth. Full article

Aquaculture is the fastest-growing food industry worldwide because it allows faster intensive production in a limited space and short time. However, the trade-off of this production scheme has led to infectious disease outbreaks that harm food production with economic impacts. Immunostimulants have entered the industry to fight against diseases by enhancing the immune system and conferring better protection against pathogens. In this regard, dietary immunostimulants have been tested at the farm level, such as carbohydrates and proteins known to enhance immunity and improve survival rates under experimental conditions. Despite the success of immunostimulant inclusion in experimental aquaculture, economic evaluation is an innovative avenue to be integrated when a novel immunostimulant is developed. The bioeconomic analysis permits the accurate demonstration of advantages or disadvantages regarding survival and yield performance upon immunostimulant application through mathematical and statistical estimates. An integrative bioeconomic model for testing a novel immunostimulant should contemplate technological, biological, and economic submodels at least; thus, financial variables, such as revenue, costs, and profitability, should also be considered for proper decision-making. Therefore, this perspective briefly describes the most relevant immunostimulants used in shrimp farms and offers bioeconomic elements that should be considered for affordable immunostimulant development and inclusion in shrimp aquaculture. Full article

The usage of digital twins (DTs) is growing across a wide range of businesses. The health sector is one area where DT use has recently increased. Ultimately, the concept of digital health twins holds the potential to enhance human existence by transforming disease prevention, health preservation, diagnosis, treatment, and management. Big data’s explosive expansion, combined with ongoing developments in data science (DS) and artificial intelligence (AI), might greatly speed up research and development by supplying crucial data, a strong cyber technical infrastructure, and scientific know-how. The field of healthcare applications is still in its infancy, despite the fact that there are several DT programs in the military and industry. This review’s aim is to present this cutting-edge technology, which focuses on neurology, as one of the most exciting new developments in the medical industry. Through innovative research and development in DT technology, we anticipate the formation of a global cooperative effort among stakeholders to improve health care and the standard of living for millions of people globally. Full article

The fourth agricultural revolution (or Agriculture 4.0) promises to lead the way to an agricultural sector that is smarter, more efficient, and more environmentally and socially responsible. Digital and data generating tools are seen as critical enablers for this transformation and are expected to make farming more planned, predictive, productive, and efficient. To make this vision a reality, agricultural producers will first adopt and use the technologies, but this is easier said than done. Barriers such as limited digital infrastructure, low (digital) literacy, low incomes, and socio-cultural norms are major factors causing sub-optimal access to and use of digital technologies among smallholder farmers. Beyond these use challenges of access and usage, limited evidence exists to support the notion that extant digital technologies add enough value to provide substantial benefits for targeted farmers. In this paper, we unravel insights from a six-year digital agriculture innovation project which was implemented to develop and deploy multi-modal digital tools for the control of a major banana disease. By reaching over 272,200 smallholder farmers in Rwanda through a smartphone app, unstructured supplementary service data, a chatbot, and other ancillary channels, we assessed various assumptions regarding intrinsic motivation, incentives, and skills retention among the target digital tool users. These insights suggest that embedding digital innovation requires intentional user-engagement, proper incentivization of next-users, and targeted communication to foster adoption. We present ten (10) salient, but non-exhaustive, lessons to showcase the realities of developing and delivering digital tools to farmers over an extended period, spanning from ideation, development, and testing to scaling stages. The lessons are relevant for a broad audience, including stakeholders across the digital innovation space who can utilize our experiential notes to guide the development and deployment of similar digital innovations for improved outcomes in smallholder farming systems. Full article

With improving economic conditions, consumer demand for fresh-cut produce is rising. The development of the fresh-cut industry has been hindered by pathogenic contamination and quality deterioration. Scientific communities have developed novel preservation technologies for fresh-cut produce. As an innovative non-thermal processing method, cold plasma effectively preserves the nutritional value and inactivates pathogens in fresh-cut produce. This review delineates the principles of cold-plasma generation and concludes with the primary factors influencing its efficacy. These factors include the specifications and parameters of the equipment utilized, the properties of the conductive gas utilized, the method of treatment, and the intrinsic properties of a sample subjected to treatment. Furthermore, this review delineates various scenarios for cold-plasma applications. This review focuses on its effects on enzymatic activities (including peroxidase, polyphenol oxidase, and pectin methylesterase), pathogenic microorganisms, and nutritional value. This review concludes with the potential application of cold-plasma technology in the processing of fresh-cut products. This study proposes advancing plasma technology in fresh-cut produce processing by (1) optimizing cold-plasma parameters for diverse fruit and vegetable varieties and (2) scaling up to facilitate industrial application. Full article

The Internet of Things (IoT) transforms traditional technology by introducing smart devices into almost every field, enabling real-time monitoring and automation. Despite the obvious benefits, the rapid deployment of IoT presents numerous security challenges, including vulnerabilities in network attacks and communication protocol weaknesses. While several surveys have addressed these aspects, there remains a lack of understanding of integrating all potential defense mechanisms, such as intrusion detection systems (IDSs), anomaly detection frameworks, and authentication protocols, into a comprehensive security framework. To overcome this, the following survey aims to critically review existing security mechanisms in IoT environments and significantly fill these gaps. In particular, this paper reviews state-of-the-art approaches for intrusion detection, key agreement protocols, and anomaly detection systems, pointing out their advantages and disadvantages and identifying the gaps in each field requiring more research. We identify innovative strategies by systematically analysing existing approaches and propose a roadmap for enhancing IoT security. This work contributes to the field by offering a fresh perspective on defense mechanisms and delivering actionable insights for researchers and practitioners securing IoT ecosystems. Full article