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The purpose of this study is to develop a molecular imprinting electrochemical sensor for the specific detection of the anticancer drug amsacrine. The sensor used a composite of bacterial cellulose (BC) and silver nanoparticles (AgNPs) as a platform for the immobilization of a molecularly imprinted polymer (MIP) film. The main objective was to enhance the electrochemical properties of the sensor and achieve a high level of selectivity and sensitivity toward amsacrine molecules in complex biological samples.

The composite of BC-AgNPs was synthesized and characterized using FTIR, XRD and SEM techniques. The MIP film was molecularly imprinted to selectively bind amsacrine molecules. Electrochemical characterization, including cyclic voltammetry and electrochemical impedance spectroscopy, was performed to evaluate the modified electrode’s conductivity and electron transfer compared to the bare glassy carbon electrode (GCE). Differential pulse voltammetry was used for quantitative detection of amsacrine in the concentration range of 30–110 µM.

The developed molecular imprinting electrochemical sensor demonstrated significant improvements in conductivity and electron transfer compared to the bare GCE. The sensor exhibited a linear response to amsacrine concentrations between 30 and 110 µM, with a low limit of detection of 1.51 µM. The electrochemical response of the sensor showed remarkable changes before and after amsacrine binding, indicating the successful imprinting of amsacrine in the MIP film. The sensor displayed excellent selectivity for amsacrine in the presence of interfering substances, and it exhibited good stability and reproducibility.

This study presents a novel molecular imprinting electrochemical sensor design using a composite of BC and AgNPs as a platform for MIP film immobilization. The incorporation of BC-AgNPs improved the sensor’s electrochemical properties, leading to enhanced sensitivity and selectivity for amsacrine detection. The successful imprinting of amsacrine in the MIP film contributes to the sensor's specificity. The sensor's ability to detect amsacrine in a concentration range relevant to anticancer therapy and its excellent performance in complex sample matrices add significant value to the field of electrochemical sensing for pharmaceutical analysis.

The purpose of this paper is to give an overview of artificial intelligence (AI) and other AI-enabled technologies and to describe how COVID-19 affects various industries such as health care, manufacturing, retail, food services, education, media and entertainment, banking and insurance, travel and tourism. Furthermore, the authors discuss the tactics in which information technology is used to implement business strategies to transform businesses and to incentivise the implementation of these technologies in current or future emergency situations.

The review provides the rapidly growing literature on the use of smart technology during the current COVID-19 pandemic.

The 127 empirical articles the authors have identified suggest that 39 forms of smart technologies have been used, ranging from artificial intelligence to computer vision technology. Eight different industries have been identified that are using these technologies, primarily food services and manufacturing. Further, the authors list 40 generalised types of activities that are involved including providing health services, data analysis and communication. To prevent the spread of illness, robots with artificial intelligence are being used to examine patients and give drugs to them. The online execution of teaching practices and simulators have replaced the classroom mode of teaching due to the epidemic. The AI-based Blue-dot algorithm aids in the detection of early warning indications. The AI model detects a patient in respiratory distress based on face detection, face recognition, facial action unit detection, expression recognition, posture, extremity movement analysis, visitation frequency detection, sound pressure detection and light level detection. The above and various other applications are listed throughout the paper.

Research is largely delimited to the area of COVID-19-related studies. Also, bias of selective assessment may be present. In Indian context, advanced technology is yet to be harnessed to its full extent. Also, educational system is yet to be upgraded to add these technologies potential benefits on wider basis.

First, leveraging of insights across various industry sectors to battle the global threat, and smart technology is one of the key takeaways in this field. Second, an integrated framework is recommended for policy making in this area. Lastly, the authors recommend that an internet-based repository should be developed, keeping all the ideas, databases, best practices, dashboard and real-time statistical data.

As the COVID-19 is a relatively recent phenomenon, such a comprehensive review does not exist in the extant literature to the best of the authors’ knowledge. The review is rapidly emerging literature on smart technology use during the current COVID-19 pandemic.

This paper aims to present a literature review of remote monitoring systems for water infrastructure in the Global South.

Following initial scoping searches, further examination was made of key remote monitoring technologies for water infrastructure in the Global South. A standard literature search methodology was adopted to examine these monitoring technologies and their respective deployments. This hierarchical approach prioritised “peer-reviewed” articles, followed by “scholarly” publications, then “credible” information sources and, finally, “other” relevant materials. The first two search phases were conducted using academic search services (e.g. Scopus and Google Scholar). In the third and fourth phases, Web searches were carried out on various stakeholders, including manufacturers, governmental agencies and non-governmental organisations/charities associated with Water, Sanitation and Hygiene (WASH) in the Global South.

This exercise expands the number of monitoring technologies considered in comparison to earlier review publications. Similarly, preceding reviews have largely focused upon monitoring applications in sub-Saharan Africa (SSA). This paper explores opportunities in other geographical regions and highlights India as a significant potential market for these tools.

This review predominantly focuses upon information/data currently available in the public domain.

Remote monitoring technologies enable the rapid detection of broken water pumps. Broken water infrastructure significantly impacts many vulnerable communities, often leading to the use of less protected water sources and increased exposure to water-related diseases. Further to these public health impacts, there are additional economic disadvantages for these user communities.

This literature review has sought to address some key technological omissions and to widen the geographical scope associated with previous investigations.

The primary objective of this paper is to show a systematic and methodological approach for the digitalization of critical clinical pathways (CPs) within the healthcare domain.

The methodology entails the integration of service design (SD) and action research (AR) methodologies, characterized by iterative phases that systematically alternate between action and reflective processes, fostering cycles of change and learning. Within this framework, stakeholders are engaged through semi-structured interviews, while the existing and envisioned processes are delineated and represented using BPMN 2.0. These methodological steps emphasize the development of an autonomous, patient-centric web application alongside the implementation of an adaptable and patient-oriented scheduling system. Also, business processes simulation is employed to measure key performance indicators of processes and test for potential improvements. This method is implemented in the context of the CP addressing transient loss of consciousness (TLOC), within a publicly funded hospital setting.

The methodology integrating SD and AR enables the detection of pivotal bottlenecks within diagnostic CPs and proposes optimal corrective measures to ensure uninterrupted patient care, all the while advancing the digitalization of diagnostic CP management. This study contributes to theoretical discussions by emphasizing the criticality of process optimization, the transformative potential of digitalization in healthcare and the paramount importance of user-centric design principles, and offers valuable insights into healthcare management implications.

The study’s relevance lies in its ability to enhance healthcare practices without necessitating disruptive and resource-intensive process overhauls. This pragmatic approach aligns with the imperative for healthcare organizations to improve their operations efficiently and cost-effectively, making the study’s findings relevant.

This article takes into account object identification, enhanced visual feature optimization, cost effectiveness and speed selection in response to terrain conditions. Neither supervised machine learning nor manual engineering are used in this work. Instead, the OTV educates itself without instruction from humans or labeling. Beyond its link to stopping distance and lateral mobility, choosing the right speed is crucial. One of the biggest problems with autonomous operations is accurate perception. Obstacle avoidance is typically the focus of perceptive technology. The vehicle's shock is nonetheless controlled by the terrain's roughness at high speeds. The precision needed to recognize difficult terrain is far higher than the accuracy needed to avoid obstacles.

Robots that can drive unattended in an unfamiliar environment should be used for the Orbital Transfer Vehicle (OTV) for the clearance of space debris. In recent years, OTV research has attracted more attention and revealed several insights for robot systems in various applications. Improvements to advanced assistance systems like lane departure warning and intelligent speed adaptation systems are eagerly sought after by the industry, particularly space enterprises. OTV serves as a research basis for advancements in machine learning, computer vision, sensor data fusion, path planning, decision making and intelligent autonomous behavior from a computer science perspective. In the framework of autonomous OTV, this study offers a few perceptual technologies for autonomous driving in this study.

One of the most important steps in the functioning of autonomous OTVs and aid systems is the recognition of barriers, such as other satellites. Using sensors to perceive its surroundings, an autonomous car decides how to operate on its own. Driver-assistance systems like adaptive cruise control and stop-and-go must be able to distinguish between stationary and moving objects surrounding the OTV.

One of the most important steps in the functioning of autonomous OTVs and aid systems is the recognition of barriers, such as other satellites. Using sensors to perceive its surroundings, an autonomous car decides how to operate on its own. Driver-assistance systems like adaptive cruise control and stop-and-go must be able to distinguish between stationary and moving objects surrounding the OTV.

The purpose of this paper is to construct an event-triggered finite-time fault-tolerant formation tracking controller, which can achieve a time-varying formation control for multiple unmanned aerial vehicles (UAVs) during actuator failures and external perturbations.

First, this study developed the formation tracking protocol for each follower using UAV formation members, defining the tracking inaccuracy of the UAV followers’ location. Subsequently, this study designed the multilayer event-triggered controller based on the backstepping method framework within finite time. Then, considering the actuator failures, and added self-adaptive thought for fault-tolerant control within finite time, the event-triggered closed-loop system is subsequently shown to be a finite-time stable system. Furthermore, the Zeno behavior is analyzed to prevent infinite triggering instances within a finite time. Finally, simulations are conducted with external disturbances and actuator failure conditions to demonstrate formation tracking controller performance.

It achieves improved performance in the presence of external disturbances and system failures. Combining limited-time adaptive control and event triggering improves system stability, increase robustness to disturbances and calculation efficiency. In addition, the designed formation tracking controller can effectively control the time-varying formation of the leader and followers to complete the task, and by adding a fixed-time observer, it can effectively compensate for external disturbances and improve formation control accuracy.

A formation-following controller is designed, which can handle both external disturbances and internal actuator failures during formation flight, and the proposed method can be applied to a variety of formation control scenarios and does not rely on a specific type of UAV or communication network.

Several high street retail banks are extending their brands into digital banking through fully digital, app-only neobanks, which have been described as traditionally-driven neobanks (TDNBs). These TDNBs are considered a form of brand extension, representing the increased complexity of branding banks and financial institutions. This study explicitly addresses the branding strategies employed by TDNBs.

This study has adopted a case study research design, using a multi-stage data collection strategy. Initially, interviews were conducted with bank managers, followed by interviews with customers. Later, user-generated content was extracted through verified reviews from the app store. Subsequently, these three strands of data were thematically analysed and triangulated, in order to gain a holistic understanding of the branding strategies used by TDNBs.

Three key themes emerged regarding the branding strategies of the TDNBs: aligning with the parent brand, reinforcing the digital experience, and enhancing the brand image.

This study contributed to the growing body of research on marketing, branding, and digital transformation of bank services. As more traditional banks are exploring opportunities to pivot and explore other fintech options, this study offers significant insights that will help in managing brand experience and promotion across customer journeys in the banking sector.

This study contributes to the growing body of research on marketing, branding, and digital transformation of bank services. Even as more traditional banks explore opportunities to pivot as well as other fintech options, this study offers significant insights to help manage brand experience and promotion across customer journeys in the banking sector.

While previous studies on banking and financial services have concentrated on traditional retail and high street banks, there is a need for a greater understanding of the brand positioning of digital banks, especially those created by traditional banks.

This paper aims to concentrate on recent innovations in flexible wearable sensor technology tailored for monitoring vital signals within the contexts of wearable sensors and systems developed specifically for monitoring health and fitness metrics.

In recent decades, wearable sensors for monitoring vital signals in sports and health have advanced greatly. Vital signals include electrocardiogram, electroencephalogram, electromyography, inertial data, body motions, cardiac rate and bodily fluids like blood and sweating, making them a good choice for sensing devices.

This report reviewed reputable journal articles on wearable sensors for vital signal monitoring, focusing on multimode and integrated multi-dimensional capabilities like structure, accuracy and nature of the devices, which may offer a more versatile and comprehensive solution.

The paper provides essential information on the present obstacles and challenges in this domain and provide a glimpse into the future directions of wearable sensors for the detection of these crucial signals. Importantly, it is evident that the integration of modern fabricating techniques, stretchable electronic devices, the Internet of Things and the application of artificial intelligence algorithms has significantly improved the capacity to efficiently monitor and leverage these signals for human health monitoring, including disease prediction.

The purpose of this paper is to enrich the knowledge about blockchain (BC) technology implementation in the agri-food industry by providing an interpretive framework of the key marketing opportunities and challenges, related to the adoption of BC for Geographical Indication (GI) products.

The study adopts an explorative qualitative research design through the cognitive mapping technique applied to the cognition of different market players involved in agri-food BC projects: farmers, distributors, companies and consultancies.

This study presents a comprehensive examination of the marketing impacts of BC across various marketing objectives, including product enhancement, brand positioning, consumer relationships, market access and supply chain relationships. It highlights the capability of BC to facilitate data-enabled ecosystems within the agri-food sector, involving supply chain actors and control agencies. Additionally, the study sheds light on the challenges (technological, collaborative, political, financial and organizational) associated with the implementation of BC in the marketing of agri-food products.

This work provides a comprehensive examination of the relevance of BC in the marketing activities of firms, particularly in the context of quality food products. It highlights the main areas of impact and effects and emphasizes the complexity of the phenomenon, which extends beyond its technical issues. Furthermore, it offers a systematic exploration of the challenges associated with the adoption of BC in marketing activities, thus contributing to a broader understanding of the implications of BC adoption in companies' marketing strategies.

The practical implications for this work addresses both GI companies and policy makers. Implications for companies relate to the market benefits associated with the implementation of BC, which allow further strengthening of market positioning, relationships of trust within the supply chain and integration between physical and digital market channels. The study also systematizes the challenges underlying the implementation of BC projects. The implications for policy makers regard the role they have to play in BC projects at regulatory, financial and policy levels.

Studies focusing on BC applications in marketing are still limited and characterized by a very narrow perspective (especially in the food industry). This study contributes to the conceptual design of the marketing applications of BC in the agri-food sector. The value of the study also lies in having framed the marketing impacts of BC in a holistic perspective, along with the technological and non-technological challenges that are related to the integration of BC in marketing strategy and operations.

Nanosensors have a wide range of applications because of their high sensitivity, selectivity and specificity. In the past decade, extensive and pervasive research related to nanosensors has led to significant progress in diverse fields, such as biomedicine, environmental monitoring and industrial process control. This led to better and more efficient detection and monitoring of physical and chemical properties at better resolution, opening new horizons in the development of novel technologies and applications for improved human health, environment protection, enhanced industrial processes, etc.

In this paper, the authors discuss the application of citation network analysis in the field of nanosensor research and development. Cluster analysis was carried out using papers published in the field of nanomaterial-based sensor research, and an in-depth analysis was carried out to identify significant clusters. The purpose of this study is to provide researchers to identify a pathway to the emerging areas in the field of nanosensor research. The authors have illustrated the knowledge base, knowledge domain and knowledge progression of nanosensor research using the citation analysis based on 3,636 Science Citation Index papers published during the period 2011 to 2021.

Among these papers, the bibliographic study identified 809 significant research publications, 11 clusters, 556 research sector keywords, 1,296 main authors, 139 referenced authors, 63 nations, 206 organizations and 42 journals. The authors have identified single quantum dot (QD)-based nanosensor for biological applications, carbon dot-based nanosensors, self-powered triboelectric nanogenerator-based nanosensor and genetically encoded nanosensor as the significant research hotspots that came to the fore in recent years. The future trend in nanosensor research might focus on the development of efficient and cost-effective designs for the detection of numerous environmental pollutants and biological molecules using mesostructured materials and QDs. It is also possible to optimize the detection methods using theoretical models, and generalized gradient approximation has great scope in sensor development.

The future trend in nanosensor research might focus on the development of efficient and cost-effective designs for the detection of numerous environmental pollutants and biological molecules using mesostructured materials and QDs. It is also possible to optimize the detection methods using theoretical models, and generalized gradient approximation has great scope in sensor development.

This is a novel bibliometric analysis in the area of “nanomaterial based sensor,” which is carried out in CiteSpace software.