Affordable Technology Research Articles

Gold-Hydrogel Nanocomposites for High-Resolution Laser-Based 3D Printing of Scaffolds with SERS-Sensing Properties.

Although visible light-based stereolithography (SLA) represents an affordable technology for the rapid prototyping of 3D scaffolds for in vitro support of cells, its potential could be limited by the lack of functional photocurable biomaterials that can be SLA-structured at micrometric resolution. Even if innovative photocomposites showing biomimetic, bioactive, or biosensing properties have been engineered by loading inorganic particles into photopolymer matrices, main examples rely on UV-assisted extrusion-based low-resolution processes. Here, SLA-printable composites were obtained by mixing a polyethylene glycol diacrylate (PEGDA) hydrogel with multibranched gold nanoparticles (NPs). NPs were engineered to copolymerize with the PEGDA matrix by implementing a functionalization protocol involving covalent grafting of allylamine molecules that have C═C pendant moieties. The formulations of gold nanocomposites were tailored to achieve high-resolution fast prototyping of composite scaffolds via visible light-based SLA. Furthermore, it was demonstrated that, after mixing with a polymer and after laser structuring, gold NPs still retained their unique plasmonic properties and could be exploited for optical detection of analytes through surface-enhanced Raman spectroscopy (SERS). As a proof of concept, SERS-sensing performances of 3D printed plasmonic scaffolds were successfully demonstrated with a Raman probe molecule (e.g., 4-mercaptobenzoic acid) from the perspective of future extensions to real-time sensing of cell-specific markers released within cultures. Finally, biocompatibility tests preliminarily demonstrated that embedded NPs also played a key role by inducing physiological cell-cytoskeleton rearrangements, further confirming the potentialities of such hybrid nanocomposites as groundbreaking materials in laser-based bioprinting.

Novel dual‐resonance damped alternating current testing system for offline partial discharge measurement of power cables

AbstractTo accurately detect the early deterioration of electrical insulation in power cables, an energizing system is required for offline partial discharge (PD) measurements. The damped alternating current (DAC) testing system has emerged as an effective tool for inducing PD events. However, the existing systems often suffer from limitations such as signal interference, low sensitivity, and high costs. To address these issues, this study proposes a novel dual‐resonance DAC testing system that is simple in structure and cost‐effective. The prototype was built for testing 10‐kV distribution cables, and its effectiveness was validated through experimental tests on a cable sample. The results show that this approach significantly improves PD detection sensitivity and successfully completes PD localization. This research contributes to the development of more efficient and affordable DAC generation technology for power cable testing applications.

Development of a novel salt processing technology and its performance and economic evaluation: an experimental study

ABSTRACT This study aimed to develop a novel, sustainable, highly efficient, and affordable salt processing technology tailored to local salt producers. Novel technology converts raw solar sea salt into the finest dried salt, which is widely accepted by various industries. Experiments were conducted at a drying temperature of 80°C, with an air velocity of 30 m/s, and a feed rate of 125 kg per hour to evaluate the proposed novel salt processing technology. Performance evaluation was based on product quality parameters (e.g. wet moisture content, sodium chloride (NaCl) percentage, and whiteness) and specific energy consumption. The economic assessment relied on financial analysis and payback period parameters. The results indicated a reduction in salt sample moisture content from 10.37% ± 0.4% to 0.47% ± 0.02%, with NaCl percentage and whiteness of the salt produced at 98.5% ± 0.3% and 81 ± 0.7, respectively. The specific energy consumption for the novel salt processing technology was 0.119 ± 0.07 kWh/kg of the final salt product. Initial investment requirements totalled IDR 275,435,000, with a payback period of 1.66 years. This proposed novel salt processing technology has the potential to generate high-quality dried salt with a production efficiency of 89.5%. Consequently, it could enhance local producer’s businesses, seize opportunities in the national salt market, support rural industrialisation, and be best configured for Indonesia’s local salt producers.

HUMAN FOLLOWING CART

The development of a human-following robot utilizing Raspberry Pi and camera technology represents a significant advancement in autonomous robotics, offering practical solutions for various industries. This project integrates a Raspberry Pi microcomputer, a camera, and ultrasonic sensors to create a robot capable of tracking and following a human operator. The system employs computer vision algorithms, facilitated by a Haar Cascade Classifier, to detect faces in real-time video feeds. The video feed is processed to determine the position of the human within the frame, enabling the robot to navigate accordingly. Ultrasonic sensors are used to measure the distance between the robot and the human, ensuring that a safe and optimal following distance is maintained. The motors and motor drivers are controlled based on the visual and distance data, allowing the robot to move forward, backward, or turn as needed. This combination of technologies enhances worker safety by reducing physical strain and improves operational efficiency by automating the transportation of goods, tools, and supplies. The implementation of this system demonstrates the practical application of affordable and accessible technologies like the Raspberry Pi in creating intelligent, autonomous robots. The project highlights the potential for such robots to revolutionize workflows in warehouses, manufacturing plants, and hospitals, making advanced automation more attainable for a wide range of businesses. The integration of computer vision and sensor-based navigation in human-following robots marks a significant step forward in the evolution of intelligent workspaces and autonomous systems.

Teaching Tech by Rote: Socialization into Digital Literacies in a Ghanaian Classroom

ABSTRACT Building on decades of interdisciplinary language-centered research on literacies, this article is an exploration of the many ideologies about technology, literacy, and “good” learners, and the resulting tangle of contradictory practices, that converge in rural Ghanaian Information and Communication Technology (ICT) classrooms. In addition to tracing how Western ideologies of technological transformation were imported into the design of ICT policy and curricula via international development organizations, the article contrasts the enduring routines and practices of hierarchical knowledge transfer in Ghanaian classrooms with assumptions about exploratory users embedded in the design of technologies primarily produced in and for North American contexts. In doing so, the article highlights the regimes of participation (Flamenbaum & George 2023), or the interplay between these taken-for-granted ideologies, technological affordances, and available roles for participation in knowledge production, which dynamically structure participatory engagements with digital literacies. Such a lens highlights the ways in which persistent policy framings of digital literacies as universal, neutral universal encounters between individuals and particular hardware or software enable and reproduce longstanding processes of disciplining marginalized populations.

Building Three-dimensional Virtual Historic Fashion Museum Exhibitions: From the Perspective of Technology Affordances

Museums are currently undertaking the task of digital transformation. Transformational technology generates revitalization of the curatorship, cultural heritage presentation, management model, and traditional roles of museums. The creation of three-dimensional (3D) virtual museum exhibitions is important to fulfill the revolutionary operational requirements and projections of recent museums through digital transformation. The objectives of this project were to (1) create realistic 3D virtual museum exhibitions accessible from the web, focusing on historic fashions, and (2) provide an analysis of the process and resources for creating 3D virtual museum exhibitions featuring object-focused exhibits. As a theoretical background of this project, the theory of technology affordances and the affordance actualization process were applied in the creation of 3D virtual museum exhibitions. The results of this project provide cultural heritage museums and institutions with useful precedents for the development of 3D virtual historic fashion museum exhibitions.

Effect of a learning-based approach using the echo-signals obtained by a single-unit transducer on detection of breast tumors.

1566 Background: Breast cancer mortalities in the less developed countries are predicted to increase over the next decades mainly due to the low utilization rates of breast cancer screening programs. Additionally, studies have shown that the sensitivity and accuracy of breast self-examination in women are suboptimal. Therefore, it is important to develop a novel and affordable technology that can accurately detect small breast tumors in women. We have developed a deep learning-based echo- signal processing system that can detect breast tumors with high sensitivity and accuracy by merely obtaining ego-motion estimated echo-signals generated by a single-unit piezoelectric transducer system. Methods: We have prospectively collected echo-signals using a single-unit piezoelectric transducer system in 200 patients with breast tumors who underwent curative surgery at the Seoul National University Hospital and SMG-SNU Boramae Medical Center between Oct 2022 and Feb 2024. The data from the first 131 cases was used for the training and testing of the deep learning model with the ratio of 8:2, and the subsequent data from 69 cases was used for the external validation. We used ImageNet pre-trained ResNet50 model to train the deep learning model and adopted various data augmentation methods for model robustness. Five nested cross-validation was used to ensure the generalization performance. Results: The median age of the enrolled patients was 55 (IOR, 47-63) and 65 patients (32.5%) had non-palpable breast tumors. Nearly half of the patients (n=93, 46.5%) had tumors smaller than 2.0 cm in the largest dimension. Our deep learning algorithm showed outstanding performance with the area under the curve (AUC) of 0.914±0.022 and 0.964±0.011 for the image- and region-level, respectively, in the training and testing set (n=131). In the external validation set (n=69), the model demonstrated an AUC of 0.846±0.012 and 0.932±0.009 for the image- and region-level, respectively. As shown (Table), the accuracy, sensitivity, and specificity were substantially improved for the region-level analysis when compared with those of the image-level analysis. Conclusions: Using a prospectively collected data from 200 patients, we developed a highly accurate and robust deep learning model to detect breast tumors in women by processing echo-signals obtained by a single-unit piezoelectric transducer system. Our data indicate that deep learning approach based on low-volume echo signal can lead to a novel and affordable breast tumor screening strategy that can improve early breast cancer detection.[Table: see text]

ARcademy: Augmented Reality Adventures in Education

Abstract: Augmented reality (AR) technology holds enormous promise for transforming education by enabling interactive and immersive learning experiences. This research article provides an AR application built to highlight the different possibilities of AR in educational contexts. The program incorporates different interactive aspects, including a virtual dragon, as a showcase of the adaptability and potential of AR for boosting learning experiences. Users can connect with the virtual dragon and explore its interactions within the real-world setting, showing the seamless integration of digital material into physical spaces. Through a user-centered design approach, our team has built an easy and engaging AR experience geared at promoting curiosity, creativity, and critical thinking skills among learners. By exploiting the unique affordances of AR technology, educators can develop dynamic learning environments that cater to varied learning styles and interests. This study assesses the effectiveness of the AR application in encouraging active learning and boosting student engagement across diverse educational environments. It also investigates practical aspects such as usability, accessibility, and scalability to influence future innovations and implementations of AR-based teaching systems. By giving a real example of AR integration in education, our research contributes to the continuing discourse on the transformative potential of AR technology. It emphasizes the necessity of developing creative techniques to harness AR for interactive and personalized learning experiences in the digital age.

Sustainable Transport in the European Union: Exploring the Net-Zero Transition through Confirmatory Factor Analysis and Gaussian Graphical Modeling

The sustainability of the transport sector is targeted by various policies adopted by the European Union, and their impact must be constantly monitored in order to maximize the desired objective. This paper, through a two-stage investigation, aims to present a systemic approach of the sustainability dimensions in transport and to introduce an innovative technique to analyze the interdependencies between them. In the first stage, relevant indicators were selected from the Eurostat database for the content of four dimensions: economic, environmental, social and technological. The robustness of the developed dimensions was assessed and validated through a confirmatory factor analysis. In the second stage, a Gaussian graphical model was estimated as a technique integrating graphical and statistical modeling to identify complex structures of linkages between variables (as components of each dimension of sustainability). The structure of the network clearly highlights the dependence of transport on fossil fuel consumption as the main determinant of pollution in the sector (CO2 emissions). In addition, the central role of railways in decarbonizing transport is highlighted, in contrast to the limited, and isolated at one end of the network, role of electric vehicles. The findings support that affordability of this new technology plays an important role in its impact on zero-emission transition. Concentrating on the period 2013–2022, at EU27 level, the results are relevant in the context of decarbonization policies, offering useful insights both for future research and policy makers.

Quantum dot-enabled infrared hyperspectral imaging with single-pixel detection.

Near-infrared (NIR) hyperspectral imaging is a powerful technique that enables the capture of three-dimensional (3D) spectra-spatial information within the NIR spectral range, offering a wide array of applications. However, the high cost associated with InGaAs focal plane array (FPA) has impeded the widespread adoption of NIR hyperspectral imaging. Addressing this challenge, in this study, we adopt an alternative approach-single-pixel detection for NIR hyperspectral imaging. Our investigation reveals that single-pixel detection outperforms conventional FPA, delivering a superior signal-to-noise ratio (SNR) for both spectral and imaging reconstruction. To implement this strategy, we leverage self-assembled colloidal quantum dots (CQDs) and a digital micromirror device (DMD) for NIR spectral and spatial information multiplexing, complemented by single-pixel detection for simultaneous spectral and image reconstruction. Our experimental results demonstrate successful NIR hyperspectral imaging with a detection window about 600 nm and an average spectral resolution of 8.6 nm with a pixel resolution of 128 × 128. The resulting spectral and spatial data align well with reference instruments, which validates the effectiveness of our approach. By circumventing the need for expensive and bulky FPA and wavelength selection components, our solution shows promise in advancing affordable and accessible NIR hyperspectral imaging technologies, thereby expanding the range of potential applications.

The effects of augmented reality on prosocial behavior intentions in the disaster news context: The mediating role of physical presence and empathy

Despite the increasing adoption of augmented reality (AR) in journalism, there is limited scholarly attention devoted to understanding its effects compared to traditional modalities. This study investigates user engagement with AR-enabled disaster news through a between-subjects experiment ( N = 89), comparing AR, image, or text-only modalities. The results demonstrate that psychological responses to the technological affordances of AR (perceived vividness, interactivity, and novelty) did not mediate the effect of AR on physical presence. In addition, the positive indirect effect of AR on empathy was shown via physical presence. Furthermore, AR positively influenced intentions for news sharing through an increase in physical presence and empathy sequentially. These findings contribute to the growing body of research on immersive media in the journalism context, shedding light on the often-overlooked impact of AR compared to other leaner modalities, such as image or text.

Uses and Gratifications of Over-the-Top (OTT) Video Streaming Platforms in India: Predictors of User’s Affinity, Satisfaction and Cord-Cutting

Over-the-top (OTT) platforms have changed how people watch television due to technological affordance and interactivity. With the theoretical framework of the uses and gratifications theory ( N = 421), this study identified eight motivational factors for OTT viewing: convenient navigability, improved viewing experience, entertainment, relaxation, social interaction, companionship, voyeurism and information seeking. Some of the study’s prominent findings were: convenient navigability, improved viewing experience, entertainment and voyeurism were positive predictors of OTT affinity; Entertainment, voyeurism and information-seeking gratifications positively predicted satisfaction with the OTT, while convenient navigability negatively predicted satisfaction; Convenient navigability, improved viewing experience, entertainment and relaxation gratifications along with interactivity and viewing levels positively predicted the intention to cord-cut.

The psychology of sexual and gender diversity in the 21st century: Social technologies and stories of authenticity.

The 21st century has seen shifts in social and scientific understandings of gender and sexuality in the United States. From the legitimization of same-sex marriage to the heightened visibility of transgender identities, nonbinary gender, and forms of intimate diversity such as asexuality, kink, and polyamory, core cultural and scientific assumptions about gender and sexuality have been challenged. This article situates these changes in the historical context of 21st century social technologies, which challenge traditional sources of authority about information and provide enhanced opportunities for individuals to experience authenticity in gender and sexuality. We frame authenticity as a master cultural narrative in the United States characterized by feeling a heightened sense of self-authorship and alignment between inner experience and embodiment of gender and sexuality. Five narratives now circulate in the United States, four of which support sexual and gender diversity: (a) gender as self-constructed; (b) sexuality as plural, playful, flexible, and fluid; (c) sexuality and monogamy as cultural compulsions; and (d) intersectionality as central to the experience of sexuality and gender. A fifth narrative seeking to legitimize hierarchies (e.g., patriarchy) is hostile to sexual and gender diversity but remains anchored in a metanarrative of authenticity and has benefitted equally from the affordances of social technologies. This historical moment provides researchers and practitioners with the opportunity to more intentionally ground their work in lived experience, challenge normative thinking about sexuality and gender, practice affirmation, center the phenomenon of diversity over discrete identity categories in an ever-exclusionary acronym (lesbian, gay, bisexual, transgender, queer/questioning, and more identities [LGBTQ+]), and embrace fluid and nonlinear narratives of social change. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

The platformisation of illicit drug markets: How datafication, technological affordances, and platform-mediated labour practices shape illicit drug markets

Digital technologies go beyond merely facilitating illicit drug exchanges; they actively reconfigure and reorganise interactions in illicit drug markets. In this article we consider the ongoing evolution of illicit drug markets against the backdrop of platform capitalism in order to conceptualise the platformisation of illicit drug markets. The platformisation of illicit drug markets illustrates how drug markets are becoming contingent on the technological, economic and socio-cultural logics of digital platforms. We explore three key themes that are useful in framing the process of platformisation: (i) the datafication of drug markets, (ii) platform affordances and drug exchanges and (iii) platform-mediated labour practices. These themes unpack the transformations underway in illicit drug markets, but the paper also invites broader conversations on how criminology engages in discussions of crime in an era dominated by technology giants (e.g. Meta, Google and Amazon).

Co-phylogeographic structure in a disease-causing parasite and its oyster host.

With the increasing affordability of next-generation sequencing technologies, genotype-by-sequencing has become a cost-effective tool for ecologists and conservation biologists to describe a species' evolutionary history. For host–parasite interactions, genotype-by-sequencing can allow the simultaneous examination of host and parasite genomes and can yield insight into co-evolutionary processes. The eastern oyster, Crassostrea virginica, is among the most important aquacultured species in the United States. Natural and farmed oyster populations can be heavily impacted by ‘dermo’ disease caused by an alveolate protist, Perkinsus marinus. Here, we used restricted site-associated DNA sequencing (RADseq) to simultaneously examine spatial population genetic structure of host and parasite. We analysed 393 single-nucleotide polymorphisms (SNPs) for P. marinus and 52,100 SNPs for C. virginica from 36 individual oysters from the Gulf of Mexico (GOM) and mid-Atlantic coastline. All analyses revealed statistically significant genetic differentiation between the GOM and mid-Atlantic coast populations for both C. virginica and P. marinus, and genetic divergence between Chesapeake Bay and the outer coast of Virginia for C. virginica, but not for P. marinus. A co-phylogenetic analysis confirmed significant coupled evolutionary change between host and parasite across large spatial scales. The strong genetic divergence between marine basins raises the possibility that oysters from either basin would not be well adapted to parasite genotypes and phenotypes from the other, which would argue for caution with regard to both oyster and parasite transfers between the Atlantic and GOM regions. More broadly, our results demonstrate the potential of RADseq to describe spatial patterns of genetic divergence consistent with coupled evolution.

Environmentally benign preparation of Ag nanoparticles & Ag-rGO nanocomposite and evaluation of their photocatalytic, sensing, antioxidant and antimicrobial activities

Environmental pollution and fossil fuel depletion are becoming major issues on a worldwide scale, posing serious threats to both the environment and human health. Finding effective and affordable pollution cleanup technologies as well as the alternate source of energy is very important. The present study is concerned with the synthesis of Ag nanoparticles and Ag-rGO composite employing environment affable and cost-effective green combustion method. The fuel used for the preparation of NPs was the Malus domastica juice. The synthesized materials were subjected for the characterization techniques like XRD, TEM, SEM, Raman and UV-Visible spectral studies. The synthesized nanocomposite was analyzed for photocatalytic dye degradation, electrochemical nitrate sensing, antibacterial as well as antioxidant activities. Ag-rGO degraded methylene blue dye completely by 70 min. Further, the material was subjected for recyclability test and it was efficient and stable upto 5th cycle. Effect of various parameters such as catalytic load, dye concentration and pH on efficiency of dye degradation was analyzed. Nitrite sensing studies revealed that the LOD was found to be 19.8 µg. Further, Ag-rGO exhibited antibacterial activity on Pseudomonas aeroginosa bacterial strain to a greater extent compared to all the other bacterial strains tested. The Ag-rGO nanocomposite was found to be the potent antioxidant with IC50 value of 1489 µg/mL. Therefore, this work exemplifies the easy and eco-friendly green synthetic route for the large-scale industrial production of versatile Ag-rGO nanocomposite.

The mundane governance of education through time: the case of national testing in Norway

ABSTRACT This article explores national testing in Norway by analyzing technical and bureaucratic documents steering the process of data production. By examining documents through sociological perspectives on time, as well as attuning to the form and genre of the documents, we identify bureaucratic, sociotechnical, and genre-specific ways in which data production is structured to ensure a smooth process of testing. We find that national tests govern (through) time and by ordering time: their time rules produce simultaneity and synchronicity that in turn gently nudge schools and municipalities into alignment. Thus, time rules and routines enable forms of mundane governance that mirror how contemporary education policy happens through short but more prescriptive (and increasingly digital) policy texts. This is how national authorities may make themselves less detectable, but ever more present and productive of national unity. While recent conversations on time and temporality focus on the emergence of complex, non-linear (e.g. networked) time enabled by the digital transformation of society and education, our article attests to the persistence and significance of linear temporalities in and for education governance, and shows how quantification, assessment, bureaucracy and the affordances of digital technologies together play pivotal roles in upholding a linear time order.

What drives digital innovation cycles? Evidence from manufacturing enterprises in China

This paper examined the determinant factors of digital innovation cycles using the data of 356 listed manufacturing enterprises in China from 2013 to 2021. The digital innovation cycles were measured using Data Envelopment Analysis (DEA). Various influencing factors, including digital technologies, organisations, users, and the environment, were analysed based on the Technology Affordance Theory (TAT). The results indicated that digital innovation efficiency in the Chinese manufacturing industry exhibited a fluctuating development trend and had considerable potential for future development. Digital innovation varied across sub-sectors, and the high-knowledge-intensive industries were subject to the greatest weaknesses. Digital innovation also changed significantly across regions in China. Furthermore, digital strategic orientation, executive education level, digital infrastructure, and regional digitalisation level negatively affected digital innovation. However, customer concentration positively affected digital innovation efficiency. Comprehensive guidance and implications for multiple perspectives are presented to enhance digital innovation by manufacturing enterprises.

A smartphone-based fluorescent biosensor with metal-organic framework biocomposites and cotton swabs for the rapid determination of tetrodotoxin in seafood

BackgroundTetrodotoxin (TTX) is a potent neurovirulent marine biotoxin that is present in puffer fish and certain marine animals. It is capable of causing severe neurotoxic symptoms and even death when consumed through contaminated seafood. Due to its high toxicity, developing an effective assay for TTX determination in seafood has significant benefits for food safety and human health. Currently, it remains challenging to achieve on-site determination of TTX in seafood. To facilitate mass on-site assays, more affordable technologies utilizing accessible equipment that require no skilled personnel are needed. ResultsA smartphone-based portable fluorescent biosensor is proposed for TTX determination by using metal-organic framework (MOF) biocomposites and cotton swabs. Oriented antibody (Ab)-decorated and fluorescent quantum dot (QD)-loaded MOF biocomposites (QD@MOF*Ab) are rapidly synthesized for binding targets and fluorescent responses by utilizing the tunability of zinc-based MOF. Moreover, facile Ab-immobilized household cotton swabs are utilized as TTX capture tools. TTX forms sandwich immune complexes with QD@MOF*Ab probes, achieving signal amplification. These probes are excited by a portable device to generate bright fluorescent signals, which can be detected by the naked eye, and TTX quantitative results are obtained using a smartphone. When observed with the naked eye, the limit of detection (LOD) is 0.4 ng/mL, while intelligent quantitation presents an LOD of 0.13 ng/mL at logarithmic concentrations of 0.2–400 ng/mL. SignificanceThis biosensor is convenient to use, and an easy-to-operate analysis is completed within 15 min, thus demonstrating excellent performance in terms of detection speed and portability. Furthermore, it successfully determines TTX contents in puffer fish and clam samples, demonstrating its potential for monitoring seafood. Herein, this work provides a favorable rapid sensing platform that is easily portable.

Microbial nanomaterials: Role in sustainable agricultural practices

The increased use of chemical fertilizers, pesticides, soil-based heavy metals to improve productivity in agriculture results into higher pollution level in agroecosystem. It has become a major issue on a global scale that seriously jeopardizes people’s health and welfare as well as affects society and overall economy. In view of this, there is an urgent need to detect pollutants in the agroecosystem so that remediation practices can be implemented in time. The evolution of more responsive, affordable and precise technology is needed to create nano-sensors or nanodevices that can be used to monitor agricultural pollution, and the processes involved in pollution control. Major focused ones are those that can detect pollutants at very low concentration levels, as well as point-to-point sensing, in situ, and uninterrupted monitoring devices that offer synchronized data. These sensors are readily available in the market for the detection of organic pollutants, gases, volatile organic molecules, heavy metal ions, hazardous metal ions, etc. but they consume a lot of power and lack sophisticated technologies for improved selectivity and sensitivity. Their precision, sensitivity, response speed and environmental stability under actual operating conditions can all be improved with the aid of nanotechnology. In this study an attempt was made to describe how microbial biosensors can be used to detect toxic materials in agroecosystems. Additionally, an application of nanomaterials as pesticides and antimicrobial agent has also been discussed.