We present an updated design process for adapting and integrating existing cyber risk assessment approaches for impact assessment for the risk from IoT to the digital economy. The new design process includes a set of changes to the original standards (e.g. NIST) that are adapted for the IoT cyber risk in this paper. This paper also presents a new framework for impact assessment of IoT cyber risk, specific for the digital economy.

The aim of this study is to describe a research protocol of a multi-country randomized controlled trial to investigate the effect of a smartphone CBT stress management program on improving depression and other health- and work-related outcomes among hospital nurses in Vietnam and Thailand during the COVID-19 epidemic as a part of the COCONATS project. The study is a two-arm, parallel randomized control trial. Hospital nurses (N = 1,500) will be recruited in Vietnam and Thailand, and those who meet the criteria will be randomly allocated to the intervention or control (treatment as usual) group. A seven-week, seven-module smartphone-based stress management program will be developed to teach CBT skills. The intervention group will participate in the program for 10 weeks. Depression as the primary outcome will be measured using the DASS21 at baseline and in 3- and 6-month follow-up surveys. A mixed model repeated measures analysis will be used to test the intervention effect in the total combined sample, on an intention-to-treat basis. This is the first study to investigate the effectiveness of a self-guided smartphone CBT program on improving depression among hospital nurses using a RCT design in South-East Asian middle-income countries during the COVID-19 pandemic.

This article delves into the complex landscape of Bitcoin halving events, analyzing the historical context and implications of these pivotal occurrences within the cryptocurrency ecosystem and on its sustainability within the landscape of financial technologies. Through an examination of past halving events in 2012, 2016, and 2020, this study meticulously scrutinizes the conditions and prices of Bitcoin before and after each halving. By synthesizing data and trends from previous events, this article aims to uncover patterns and insights that illuminate the impact of Bitcoin halving on market dynamics and sustainability, movement of the price level, reached peaks and price troughs. Furthermore, this research presents a comparative analysis of past halving events, drawing parallels and distinctions to elucidate the evolving nature of Bitcoin's price movements and market sentiment surrounding these milestone events. Looking towards the future, this study estimates predictions and expectations for the upcoming Bitcoin halving. By unraveling the intricate relationship between Bitcoin halving events and market behavior, this article seeks to provide a comprehensive understanding of the broader implications for Bitcoin's trajectory and the evolving landscape of the cryptocurrency market and its sustainability.

A critical context is an essential aspect of practice-based research; however, a lack of structure exists to obtain and evaluate criticism from peers. This paper presents a case study of how the ‘silent student’ critique method used in Higher Education settings in the UK (Elkins, 2014) was adapted for a holographic arts research study. A ‘silent researcher’ critique session with nine experts was held in Aveiro, Portugal, June 2018 to evaluate the author’s digital holographic artwork, on display at the City Museum. The experts asked the author critical questions about the artwork while the author remained silent. The session was filmed, transcribed and processed using a general inductive approach for analysing qualitative evaluation data (Thomas, 2006). This paper outlines the benefits and drawbacks of using this new critique method for research. The benefits included; participant’s careful response to the artwork avoiding engagement of egos of critic and researcher, the drawbacks included the difficulty of evaluating against a pre-determined research question when the discussion could not be steered. This paper evaluates the artwork critiqued describing how the work contributes to the aesthetic development of the medium of holography; which used the Z-axis of holographic space to depict a chronological narrative.

This research delves into the integration of green roofs with Building Information Modeling (BIM), a pivotal advancement in sustainable urban construction. Aligning with the United Nations Sustainable Development Goals, particularly Goal 11, the study explores how this integration can address global challenges like climate change and resource depletion. Using the Dynamo Visual Programming Language within Autodesk Revit, the research develops a computational modeling approach for green roofs, focusing on their thermal and structural characteristics under varied environmental conditions. Key findings demonstrate the significant influence of substrate and drainage material combinations on green roofs’ thermal performance, highlighting the need for tailored designs based on climatic conditions. The study also emphasizes the importance of considering structural performance in both dry and saturated conditions for overall building integrity. The research identifies gaps in current practices, such as limited focus on specific green roof materials and reliance on certain software tools, suggesting the need for broader material selection and software adaptability. Future research directions include expanding material selections, exploring diverse environmental conditions, and integrating green roofs with various BIM software platforms. The study's implications extend to stakeholders in the construction industry, offering a framework for architects, urban planners, and policymakers to design and implement green roofs aligned with environmental goals. This work contributes to the field by proposing a novel approach to sustainable construction, integrating ecological design with digital technology, and setting a new benchmark in the integration of green roofs with BIM. By addressing these aspects, the research paves the way for future developments in sustainable urban construction, enhancing the efficiency, sustainability, and resilience of urban communities in line with global sustainability objectives.

The increased number of buildings in urban areas limits the creation of vegetated areas, leading to the search for alternatives to create spaces to promote contact with nature. In this context, green roofs have been increasingly studied. These structures have specific microclimatic condi-tions requiring an accurate study of the most appropriate vegetation to use. This study aims to analyze the long-term viability of vegetation installed on an experimental green roof open-air lab. This analysis was done through images obtained from photographic records and later in-serted into the ImageJ program, to identify species and evaluate the area covered by vegetation. Only a few of the species that were planted in the test beds over the years have persisted to the present, while other species have spontaneously appeared. Also, surveys were used to learn about people's preferences for the vegetation on these test beds. These showed that people favor recognizable plants with plenty of vibrantly colored blossoms. It was feasible to choose the best plants for green roofs in the studied conditions as a result of the analysis, taking into account the ground cover percentage by vegetation, its persistence, and the preferences of the respondents.

For most professionals to be successful in the current job market, they need some entrepreneurial skills (ES). This study aimed to describe and systematize these skills, considering the current globalization and digital transformation phenomena. The documental analysis and the critical reflection on the collected data allowed us to identify the socio-economic and socio-cultural reasons for the relevance of this problem. Consequently, to elaborate a frame of reference that is intended to be adequate to the needs of the professionals of the current global and digital era. The results pointed to a tripartite ES model - to be open to novelty, to create solutions to emerging problems, and to communicate effectively - which integrates the following skills: creativity and innovation, the spirit of initiative, self-efficacy and resilience, strategic planning, and evaluation, resolution of problems and decision-making, transformational leadership, clear and visual communication, teamwork and networking, and digital communication. In the continuation of this study, an ES scale will be created and validated according to this model, which will make it possible to measure the degree of development of these competencies.

In the field of business environments, the integration of novel artificial intelligence (AI) techniques has been identified in the literature and theoretical discourse as an essential catalyst for enhancing the decision-making processes. In the contemporary landscape of digital transformation, the application of these techniques becomes essential, despite encountering various hurdles that impede their seamless integration into the rational decision-making process within e-government, which constitutes a critical component of digital government initiatives. This study explores whether similar advancements can be observed within the e-government sector and investigates the impact of using machine learning (ML) as a technique of artificial intelligence on rational decision-making (RDM). Employing an empirical research approach, the study utilized a quantitative methodology, relying on an electronically structured questionnaire survey administered to 163 employees in the e-government sector in Jordan through purposive random sampling. Data analysis was conducted using the SPSS v25 program, complemented by a media-tion analysis using AMOS v23 software. The research findings revealed a significant contribution of using machine learning to enhance rational decision-making and trust levels, with trust positively impacting RDM. Trust was identified as a beneficial mediator in the relationship between machine learning and rational decision-making. Despite certain limitations, this study's outcomes offer substantial insights for researchers and government policy-makers alike, contributing to the advancement of sustainable practices in the e-government domain.

In the past decades, the world is actively working towards the global goal of net-zero emission. To decrease emissions, there is a notable trend of electrification in transportation, which is a transition from traditional fuel-based systems to electrical power systems onboard different transportation platforms. For this transition, it is important to study the electrical structure, specifically the onboard microgrid, powered by various energy sources. In this paper, traditional energy management strategies for onboard microgrid systems are discussed, which usually require complicated optimization algorithms and high computation capabilities. Driven by the recent advancements in information technologies, artificial intelligence and digital twin have gained much interest within the transportation sector. These technologies can effectively utilize data to achieve intelligent decision-making, optimize resource utilization, and save energy consumption. This paper presents an overview of the usage of these emerging information technologies in energy management strategies, providing an overall summary and classification of the practical applications. In addition, after examining the potential challenges associated with artificial intelligence and digital twin, this paper also discusses future trends in this field.

Abstract: The widespread and popular use of TADs for orthodontic anchoring has become a daily routine in clinical orthodontic treatment. However, as there have been many accidents over the past decade, safety action is needed to help reduce these accidents. We have advocated using the surgical guide and developed a procedure that can benefit patients and orthodontists. The first part of this paper is about the rationale for making the surgical guide for various implant placements that were observed. Due to their anatomical structure, some placements may require particular attention, which is focused on and discussed in length. The second part deals with fabricating the surgical guide in the laboratory procedure. The data from the intraoral SLT acquisition was extracted, and with the DICOM data from CBCT and in a 3-Shapes software, the guidance was designed. The detailed and step-by-step laboratory procedure, CAD/CAM, and 3D printers to make the surgical guide for TADs are explained. The procedure is performed in an easy-to-understand manner to make using the surgical guide possible for the daily practice of orthodontics (Pubmed).

This study presents an advanced Simulated Shearer Machine Cutting Experiment System enhanced with digital twin technology. Central to this system is a simulated shearer drum, designed based on similarity theory to mirror the operational dynamics of actual mining cutters accurately. The setup incorporates a modified machining center equipped with sophisticated sensors that monitor various parameters such as cutting states, forces, torque, vibration, temperature and sound. These sensors are crucial for precisely simulating the shearer cutting actions. The integration of digital twin technology is pivotal, featuring a real-time data management layer, a dynamic simulation mechanism model layer, and an application service layer that facilitates virtual experiments and algorithm refinement. This multifaceted approach allows for in-depth analysis of simulated coal cutting, utilizing sensor data to comprehensively evaluate the shearer's performance. The study also includes tests on simulated coal samples. The system effectively conducts experiments and captures cutting condition signals via the sensors. Through time-domain analysis of these signals, gathered while cutting materials of varying strengths, it is determined that the cutting force signal characteristics are particularly distinct. By isolating the cutting force signal as a key feature, the system can effectively distinguish between different cutting modes. This capability provides a robust experimental basis for coal-rock identification research, offering significant insights into the nuances of shearer operation.

First came the digital banks without offices, and then the “fintech” companies that combined technology and finance to achieve greater efficiency and new business models. Later was the turn of transport and logistics, understood as the sector whose economic activities derived from the transport of people and goods, while on the one hand, it has had a new spring thanks to factors such as online sales. Then, perhaps catalyzed by the pandemic scenario, the turn has reached education, where years ago was only a complement of traditional education, now is a central part with multiple modern methodologies. Numerous studies exist about using or implementing these e-learning procedures, but technical analysis is barely found in references. This work aims to analyze the digital transformation of the main sectors of our society, including finances, transport, and education, together with several examples of how technology was helping to fight the pandemic scenario.

The transferability of structure-property relationships for laser-pretreated metal adhesive joints to laser-pretreated metal – carbon fiber reinforced plastic (CFRP) bonds is investigated. Single-lap shear tests were performed on hybrid AW 6082-T6 – CFRP specimens pretreated with the same pulsed laser surface parameter sets on the metal surface as previously tested AW 6082-T6 – E320 metal adhesive joints. The fracture surfaces were characterized to determine the type of failure and elucidate differences and commonalities in the link between surface structures and single-lap shear strengths. Digital image analyses of the hybrid specimens fractured surfaces were used to quantify remaining CFRP fragments on the metallic joint side. The results indicate that high surface enlargements and the presence of undercut structures leads to single-lap shear strengths exceeding 40 MPa and 35 MPa for unaged and aged hybrid specimens respectively. While for the metal-polymer joints the trend from high strength to weakly bonded specimens was largely continuous with the degree of surface structuring, hybrid metal – CFRP joints exhibit a drastic drop in joint performance after aging if the laser-generated surface structures are less pronounced with low surface enlargements and crater depths. Surface features and hydrothermal aging determine whether the specimens fail cohesively or adhesively.

Recent advances in mathematical modelling and artificial intelligence have challenged the use of traditional regression analysis in biomedical research. This study examined artificial and cancer research data using binomial and multinomial logistic regression and compared its performance with other machine learning models such as random forests, support vector machines, Bayesian classifiers, k-nearest neighbours and repeated incremental clipping (RIPPER). The alternative models often outperformed regression in accurately classifying new cases. Logistic regression had a structural problem similar to early single-layer neural networks, which limited its ability to identify variables with high statistical significance for reliable class assignment. Therefore, regression is not always the best model for class prediction in biomedical datasets. The study emphasises the importance of validating selected models and suggests that a mixture of experts approach may be a more advanced and effective strategy for analysing biomedical datasets.

Digital technologies play a key role in reviving the world economy. The EU has pledged to combine recovery support with resilient digital transformation. The COVID-19 pandemic highlighted the lack of digitization in Slovakia and the shortcomings of digital skills in citizens and communication with institutions. Digital skills are important and should form part of educational policy. ICT skills can help people succeed in the labour market and improve communication with public administration. Digitization and globalization increase the importance to communicate through the Internet, applications and other e-based gadgets. Digital skills are one of the essential parts of e-Government, so people can use e-Government services in communication with public administration. The current crisis citizens' use of online services. In-dices concerning the digital economy are analysed, such as the digital economy and society index DESI and e-government digital skills (EGDI) from 2018 to 2021 revealed a stagnant state in 2018 and 2019 and 2020, there was a decrease in basic digital skills". The next index is E-Government Digital Index It focuses on human capital and digital skills in these indices. The paper analyses and identifies the digital skills of citizens in the context of e-Government development and describes the use of e-Government services by EU citizens with a focus on the Slovak republic. The data were collected through a questionnaire survey with citizens in Slovak republic's digital skills according to selected categories, the use of e-Government services as well as awareness of e-Government services. Solutions that improve e-government in the Slovak Republic are gradually being implemented. Improving digital skills according to National Coalition for Digital Skills and professions in the Slovak republic and is one of the priorities of The Ministry of Education, Science, Research and Sport of the Slovak Republic which has adopted an action plan for 2019 – 2022 to improve the results in the DESI index by 2025 and focus on the digital skills required by employers. The survey revealed that in Slovakia, the majority of schools offer only weak support for digital education (about the EU-27 average of 68% and 45%, respectively). The research revealed also decreased level of digital literacy among young people. These competencies are very important to gain a position in the labour market in the digital society. The projects aim to support the development of digital skills of primary and secondary school students, and the integration of new technologies into teaching.

This article sets out to examine how digital twins have been used in a multi-national corporation, what technologies have been used, what benefits delivered and the significance of people and process related issues in achieving successful implementation. A qualitative, inductive research method is used, based on interviews provided by key personnel involved in three digital twin projects. The article concludes that digital twin projects are likely to involve incremental rather than disruptive change, and that successful implementation is usually underpinned by ensuring technology, people and process change factors are progressed in a balanced and integrated fashion. Building upon existing frameworks, three “properties” are identified as being of particular value in digital twin projects - workforce adaptability, technology manageability and process agility – and a related set of steps and actions is put forward as a template and point of reference for future digital twin implementations. The findings are a contribution to the developing theory around digital twins and digitalization in general, and are also of relevance to professionals embarking on DT projects.

This paper presents the design and implementation of a digital control system for modular multilevel converters (MMC) and its use in a 5-kW small scale prototype. To achieve higher system control reliability and multi-functionality, the proposed architecture has been built with an effective split of the control tasks between a master controller and six slave controllers, one for each of the six arms of the converter. The MMC prototype have been used for testing both converter and system level controls in a reduced scale laboratory set up of a Multi-Terminal DC transmission network (MTDC). The whole control has been tested in order to validate the proposed control strategies. The tests performed at system level allowed to explore the advantages of using an MMC in a MTDC system.

This research proposes an algorithm to sign messages using the ElGamal asymmetric cryptosystem, called: Digital signature algorithm based on ElGamal, Diffie-Hellman protocol and the number π (DSAπ). This proposal has a high level of security like the DSA standard, in addition, execution times are reduced in relation to it. The Diffie-Hellman protocol and the number π were used in the construction of the digital signature algorithm in conjunction with the Hash-Sha-512 function. Some experiments are presented to provide evidence that the bits on the right side of the decimal point of π appear randomly, such as: a color image was constructed of a string of consecutive bits chosen at random, of the number π. Subsequently, parameters such as: entropy, correlation, discrete Fourier transform, goodness-of-fit test χ2 were evaluated. It is mentioned that an S-box 8×8 is involved in the signature. The sensitivity of the signature was measured, that is, when small changes are made to the sender’s private key, or small changes to the message. Finally, an image was constructed using the signatures of random texts, and subsequently the randomness of its pixels was obtained, to verify that there is no relationship between the different signatures.

The new SARS-CoV-2 coronavirus has brought with it an increase in the use of digital platforms and an exponential increase in the number of scientific papers worldwide. The purpose of this study is to show a global overview of the digital transformation from 1975 to the present (2021). The main collection of the Web of Science database was used to retrieve global scientific production on digital transformation. Bibliometric indicators of production, visibility, impact, and collaboration were analyzed to assess research progress on the topic. The results show that digital transformation is a construct of recent development, increasingly relevant and transdisciplinary, with a clear growth after the declaration of the global COVID-19 pandemic.

The national-scale evaluation and modelling of the impact of agricultural management and cli-mate change on soils, crop growth, and the environment require soil information at a spatial res-olution addressing individual agricultural fields. This manuscript presents a data science ap-proach which agglomerates the soil parameter space into a limited number of functional soil pro-cess units (SPUs) which may be used to run agricultural process models. In fact, two unsupervised classification methods were developed to generate a multivariate 3D data product consisting of SPUs, each being defined by a multivariate parameter distribution along the depth profile from 0 to 100 cm. The two methods account for differences in variable types and distributions and in-volve genetic algorithm optimization to identify those SPUs with the lowest internal variability and maximum inter-unit difference with regards to both, their soil characteristics and landscape setting. The high potential of the methods was demonstrated by applying them to the agricultural German soil landscape. The resulting data product consists of twenty SPUs. It has a 100 m raster resolution in the 2D mapping space, and its resolution along the depth profile is 1 cm. It includes the soil properties texture, stone content, bulk density, hydromorphic properties, total organic carbon content, and pH.

The stability assessment of aged tunnel linings were mainly evaluated based on the visual inspection, and the Tunnel-lining Crack Index (TCI) is one of the most widely used tunnel lining health assessment indexes in Japan. However, the intersection and distribution of cracks, which can influence the stability of tunnel lining greatly, were not considered in the TCI. A new method was proposed for the health assessment of tunnel lining, which evaluate the lining states according to the fractal dimension of cracks. Based on the machine vision-based method, the crack image can be extracted efficiently. The fractal dimension of lining cracks in one span can be obtained in a few minutes. A series of comparative tests and field tests were conducted to evaluate the validity of this new method. The comparative tests confirmed that fractal dimension can characterize the density, width, and distribution of cracks. The results also certificated that the influence of crack width is larger than the crack density. The intersection of cracks, which will increase the risk of lining collapse, can also increase the fractal dimension, whereas the TCI keep constant. The fractal dimensions of tunnel lining cracks were obtained according to the digital inspection test of Hidake Tunnel in Japan for all the 65 spans. Moreover, the TCI was obtained through statistical methods. The correlation between fractal dimension and TCI of tunnel lining was studied. The significance of the new evaluation index is that it can identify some unusual spans of tunnel lining and provide a basis for further internal testing. As a complement to the conventional visual inspection method, the fractal dimension of the cracks is a promising health assessment index.

The digital orthophoto is an image with geometric accuracy and no distortion. It is acquired through a top view of the scene and finds widespread applications in map creation, planning, and related fields.This paper classifies the algorithms for digital orthophoto generation into two groups: explicit methods and implicit methods. Explicit methods rely on traditional geometric methods, obtaining geometric structure presented by explicit parameters with Multi-View Stereo (MVS) theories, as seen in our proposed Top view constrained Dense Matching (TDM). Implicit methods rely on neural rendering, obtaining implicit neural representation of scenes through the training of neural networks, as exemplified by Neural Radiance Fields (NeRF). Both of them obtain digital orthophoto by rendering from a top view perspective. In addition, this paper conducts an in-depth comparative study between explicit and implicit methods. The experiments demonstrate that both algorithms meet the measurement accuracy requirements and exhibit a similar level of quality in terms of generated results. Importantly, the explicit method shows a significant advantage in terms of efficiency, with a time consumption reduction of two orders of magnitude under our latest CUDA version TDM algorithm. Although explicit and implicit methods differ significantly in their representation forms, they share commonalities in the implementation across algorithmic stages. These findings highlight the potential advantages of explicit methods in orthophoto generation, while also providing beneficial references and practical guidance for the fast digital orthophoto generation using implicit methods.

The implementation of neural networks (NN) on edge devices enables local processing of wireless data but faces challenges such as high computational complexity and memory requirements when deep neural networks (DNN) are used. Shallow neural networks customized for specific problems are more efficient, requiring fewer resources, and resulting in a lower latency solution. An additional benefit of the smaller network size is that it is suitable for real-time processing on edge devices. The main concern with shallow neural networks is their accuracy performance compared to DNNs. In this paper, we demonstrate that a customized adaptive activation function (AAF) can meet the accuracy of a DNN. We designed an efficient FPGA implementation for a customized segmented spline curve neural network (SSCNN) structure to replace the traditional fixed activation function with an AAF. We compared our SSCNN with different neural network structures such as real-valued time delay neural network (RVTDNN), augmented real-valued time delay neural network (ARVTDNN), and deep neural networks with different parameters. Our proposed SSCNN implementation uses 40% fewer hardware resources and no Block RAMS compared to the DNN with similar accuracy. We experimentally validate this computationally efficient and memory-saving FPGA implementation of SSCNN for digital predistortion of RF power amplifiers using the AMD/Xilinx RFSoC ZCU111. The implemented solution uses less than 3% of the available resources. The solution also enables an increase of the clock frequency to 221.12 MHz, allowing the transmission of wide bandwidth signals.

Although our emotional connection with the physical urban setting is often valued, it is rarely recognised or used as a resource to understand future actions in city planning. Yet, despite the importance of emotion, citizens’ emotions are typically seen as difficult to quantify and individualistic, even though knowledge about people’s response to space could help planners understand people’s behaviours and learn about how citizens use and live in the city. The study explores the relationship between the physical space and emotions through identifying the links between stress levels, and specific features of the urban environment. This study aims to show the potential of integrating the use of galvanic skin response (GSR) within urban spatial analysis and city planning, in order to address the relationship between emotions and urban spaces. This method involved participants using a (GSR) device linked to location data to measure participant’s emotional responses along a walking route in a city centre environment. Findings show correlations between characteristics of environment and stress levels, as well as how specific features of the city spaces such as road crossing create stress ‘hotspots’. We suggest that the data obtained could contribute to citizens creating their own information layer - an emotional layer- that could inform urban planning decision-making. The implications of this application of this method as an approach to public participation in urban planning are also discussed.

This paper empirically analyzes the relationship between digital inclusive finance and rural income, and demonstrates that digital inclusive finance plays a significant role in promoting rural income, based on the 2012-2018 panel data of 17 cities in Henan Province of China. Further dimensional research unveils that all of its breadth of coverage, depth of use and degree of digitization present significant positive correlation with rural income, and a robustness test was conducted through the sub-sample method. In addition, according to regression analysis on the influencing factors of digital inclusive finance through the Tobit model, the level of economic development, the Internet popularity rate and the urbanization rate have a positive effect on the development of digital inclusive finance in Henan, while the income gap between urban and rural areas and the degree of opening up have a negative effect. Finally, predicated on the analysis of the restrictive factors of Henan’s digital inclusive finance in increasing rural income, the paper puts forward specific policy proposals based on the native state quo.

The potential of digital twin technology is yet to be fully realised due to its diversity and untapped potential. Digital twins enable systems’ analysis, design, optimisation, and evolution to be performed digitally or in conjunction with a cyber-physical approach to improve speed, accuracy, and efficiency over traditional engineering methods. Industry 4.0, factories of the future, and digital twins continue to benefit from the technology and provide enhanced efficiency within existing systems. Due to the lack of information and security standards associated with the transition to cyber digitisation, cybercriminals have been able to take advantage of the situation. Access to a digital twin of a product or service is equivalent to threatening the entire collection. There is a robust interaction between digital twins and artificial intelligence tools, which leads to strong interaction between these technologies, so it can be used to improve the cybersecurity of these digital platforms based on their integration with these technologies. This study aims to investigate the role of artificial intelligence in providing cybersecurity for digital twin versions of various industries, as well as the risks associated with these versions. In addition, this research serves as a road map for researchers and others interested in cybersecurity and digital security.

Eco-agricultural technology is crucial to alleviating agricultural resource scarcity and environ-mental pressures. However, financial constraint affects its successful promotion. Digital finance has a significant impact on farmers, but existing research lacks an exploration of the impact of digital finance on farmers' adoption of eco-agricultural technology. This study focuses on Rice–Crayfish Co-cultivation Technology as an example. It utilizes survey data from 1,063 households in China. An Endogenous Switching Probit model is employed to solve self-selection bias. The results reveal several key findings. First, the average treatment effect on the treated is 51.5%. This indicates that if farmers who use digital finance were to stop using it, the probability of adopting rice–crayfish co-cultivation technology would decrease by 51.5%. Therefore, digital finance is beneficial for farmers in adopting this technology. Second, heterogeneity analysis reveals that digital finance has a greater promoting effect on older farmers, those with lower education levels, and higher proportions of agricultural income. This suggests a greater reliance on digital financial services among vulnerable groups. Third, digital finance promotes farmers' adoption of rice–crayfish co-cultivation technology by alleviating financial constraints, expanding information channels, and increasing social capital accumulation. Overall, the findings offer valuable insights for for-mulating supportive policies.

This article explores the concept of sustainable leadership in the digital era and the role of technology in promoting environmental sustainability. As the world becomes increasingly interconnected through digital advancements, leaders are facing new challenges and opportunities to address environmental concerns. This article examines the key characteristics of sustainable leadership and discusses how technology can be utilized to promote environmental sustainability. It highlights various technological innovations and strategies that leaders can employ to foster a sustainable organizational culture. Moreover, the article discusses potential barriers and limitations of technology in achieving sustainability goals. Overall, it emphasizes the significance of sustainable leadership and technology integration in addressing environmental challenges in the digital era.

Coastal dunes worldwide are increasingly under pressure from the adverse effects of human activities. Therefore, more and more restoration measures are being taken to create conditions that help disturbed coastal dune ecosystems regenerate or recover naturally. However, many projects lack (open-access) monitoring observations needed to signal whether further actions are needed, and hence to learn by doing. This submission presents an open access data set of 37 high-resolution digital elevation models and 24 orthomosaics collected before and after the excavation of five artificial foredune trough blowouts ("notches") in winter 2012/2013 in the Dutch Zuid-Kennemerland National Park, one of the largest coastal dune restoration projects in northwest Europe. These high-resolution data provide a valuable resource for improving understanding of the biogeomorphic processes that determine the evolution of restored dune systems, as well as developing guidelines to better design future restoration efforts with foredune notching.

With technological transformations such as big data, blockchain, artificial intelligence, and cloud computing, digital techniques are penetrating the field of finance. Digital finance is a resource-saving and environmentally friendly innovative financial service. It shows great green attributes and can drive the flow of financial resources towards environmentally friendly enterprises, thereby promoting green and low-carbon development. This paper investigates the effects of digital finance on green and low-carbon cyclic development and the mechanism. First, the level of green and low carbon cyclic development in China is estimated from multiple aspects based on the panel data of 31 provinces by using the spatio-temporal range entropy weight method. Then, the working mechanism of digital finance on green and low carbon cyclic development is revealed by performing empirical tests based on panel regression models, mediating effect models, and threshold models. Finally, the effects of digital finance and conventional variables on green and low-carbon cyclic development are investigated by using a random forest model and a CatBoost model in based on the machine learning. The results show that digital finance has significant positive effects on green and low-carbon cyclic development, and technological innovation plays a key role in the effects of digital finance on green and low-carbon cyclic development; meanwhile, the driving effect of digital finance on green and low carbon cyclic development shows nonlinear features with increasing “marginal effect”; besides, both digital finance and conventional factors have significant impacts on green and low carbon cyclic development. This study provides an empirical basis and path reference for digital finance to achieve “carbon peak, carbon neutralization” in China.

The rapid market changes and strong product individualization create the need for great flexibility of manufacturing management on new foundations, such as the Industry 4.0 model. Digital manufacturing is the basis for Industry 4.0, that have the following dimensions: (i) digital manufacturing based on advanced digital-oriented technologies, (ii) smart products (advanced manufacturing mode and new characteristics), and (iii) smart supply - chain (procurement of raw materials and delivery of finished products). Bidirectional exchange of information in collaborative manufacturing, using it exchange also for digital platforms of design of the innovative products. In this paper we are showing developed model of one Serbian digital factory model for Quality 4.0 (Q 4.0) , especially in workshop as a part of ERP/MES model.

Using digital media has become the most popular leisure activity for children and adolescents. The effects of digital media use on the developing brain and cognitive processes of children are subject to debate. Here, we examine the effect of digital media use on attention subdomains in children aged 6 to 10 years. In total, 77 children participated in the study. Selective and divided attention as well as switching between attentional demands were quantified by the SwAD task. Parents were asked to assess the screen time of their children (TV, smartphone, laptop/PC, game console, tablet). Results show no main or interaction effects of screen time on any of the attention conditions investigated. Based on the present findings, as well as previous studies, we suggest a possible non-linear relationship between the amount of screen time and attention function. Furthermore, we emphasize the relevance of considering the socio-economic background of children and a need for longitudinal studies.

The world is growing very rapidly concerning technology. In the next-generation Internet, the existing architecture requires to be upgraded from Host-Centric Networking paradigm to Information-centric networking architecture. The unique aspect of information-centric networking is in-network cashing. Due to the system augmentation and In-network cashing technique, this novel system needs extremely high content security to ensure system integrity and maintenance. 5G network may be supported by the Information-Centric Network due to its high data transmission rate. In order to handle the serious security issues such as attack on confidentiality, authentication and integrity of the content, a Digital Signature based Access Control Mechanism in Information-Centric Network (DSAC) scheme is proposed to enhance security of ICN. Briefly, this new scheme uses Digital Signature, hash function, Trusted Third Party (TTP) and Proxy TTP. The client request for content, after receiving a request, the content provider generates and encrypts content with the digital signature and random value ‘k’ hash function and send it to TTP. After the signing process, the TTP sends the encryption hash key to Proxy TTP. In this proposed scheme authentication, confidentiality, the integrity aspects of the content security are improved.

As technology evolves, our digital footprint keeps increasing. Now, everything we do is largely related to us being online, connected and logged. Therefore, if someone’s online data is exposed, then their life will be compromised. This is called identity theft and in this era of technology, it has become one of the most serious forms of crime. When someone’s data is compromised, there is a huge chance of harming the person financially, morally and socially. New technology and the knowledge gap it creates when it first comes out is perfect for identity thieves to exploit. If we are not cautious, our future will be very different than what we dream of due to the very technology created to make it better. Hence, we need to understand the technology, identify the loopholes and educate ourselves to avoid being held captive by our digital footprint.

In this paper, a technique of image watermarking using multiple images as watermarks is presented. The technique is based on transform domain functions including discrete wavelet transform (DWT), discrete cosine transform (DCT) and singular value decomposition (SVD) with an image as the host signal i.e. the watermarks will be used as proofs of the authenticity of the host image. The technique is executed by performing multilevel DWT followed by applying DCT and SVD to both the host and watermark. Multiple watermarks are used for the insurance of better security level. The scheme is immune to common image processing operations & some attacks and exhibits PSNR of 108.3781dB, normalized cross correlation (NCC) over 0.99 and normalized correlation (NC) over 0.99.

Gardens play a key role in the definition of the cultural landscape since they reflect the culture, identity and history of a people. They also contribute to the ecological balance of the city. Despite gardens have an historic and social value, they are not protected as much as the rest of the existing heritage, like architecture and archaeological sites. While methods of built-heritage mapping and monitoring are increasing and constantly improving to reduce built-heritage loss and the severe impact of natural disasters, the documentation and survey techniques for gardens are often antiquated, inventories are typically made by non-updated/updatable reports, and rarely they are on digital format and in 3D. This paper presents the preliminary results of a study on latest technology for gardens laser scanning. We compared static Terrestrial Laser Scanning and Mobile Laser Scanning point clouds, to evaluate their quality for documentation and the estimation of the tree attributes. The evaluation is based on visual observation and graphic comparison of the two point clouds acquired in different instances. Both methods produced useful outcomes for the research scope within their limitations. Terrestrial Laser Scanning is still the method that offers more accurate point clouds with a higher point density and less noise level. However, the more recent Mobile Laser Scanning is able to survey in less time, significantly reducing the costs for site activities, data post-production and registration. Both methods have their own restrictions that are amplified by site features, mainly the lack of plans for the geometric alignment of scans and for the Simultaneous Location and Mapping (SLAM) process. We also offer the results of a comparison of the functional range of the two machines, as well as for a comparison of their terrain information extraction capabilities.

This study examines the activities conducted at the archaeological site of Aptera in Crete, Greece. The research was part of the DIACHRONIC LANDSCAPES International Design Workshop, organized by the CAM (Center for Mediterranean Architecture), TUC (Technological University of Crete School of Architecture), and UNIFE (University of Ferrara Department of Architecture). This article outlines the methods used for data acquisition and processing on a territorial scale, which generated digital outputs necessary for the analysis and design phases of the workshop, as well as for further examination of the results. The collected data, obtained through low-cost aerial photogrammetric surveying and GNSS terrestrial coordinate detection, were integrated in a Structure from Motion workflow that led to the creation and exportation of various digital outputs, such as point clouds, DTM, DSM, orthophotos, and contour lines. An accuracy analysis was performed to evaluate the effectiveness and efficiency of the digital models compared to the implemented surveying strategies, including the Ground Control Point and Quality Check Point marker positioning strategy. The resulting digital models proved to be valuable assets for analysis and design within the workshop and provided insightful prospects for future research and territorial-scale projects.

The prognostic abilities of artificial intelligence and neuroscience in forensics and the criminal justice system stand as a reformatory paradigm for understanding any criminal conduct. While the use of artificial intelligence has been labeled transformational data analytical capabilities, neural predictive approaches also enable an intricate understanding of culpability and criminal propensities. The literature on the complex nature of neuroprediction and artificial intelligence, its ethical deliberations and its usability in curving recidivism are analyzed. This theoretical review elucidates the complex interplay, nuptial relationships and convergence of these relationships in the quest for justice. The consequences of not protecting individual rights in the criminal justice system are surveyed using grounded theory. The degree of acceptability and dependability of AI-generated evidence in legal proceedings are also reviewed. All these topics are yet to be contemplated under one roof to offer an argumentative view. The author expects to prompt readers and new commers to embrace more sociolegal and technological research before incorporating such research in the Indian Judiciary. The review focuses on the question of whether to blame such technology inclusion wholly or rather to prioritize the acquisition of bias-free pretrained datasets and processing models.

The adoption of Industry 4.0 technology is essential for achieving energy efficiency, a critical aspect of Sustainable Development Goal (SDG) no. 12 aimed at addressing climate change. Understanding the impact of Sustainable Attitudes, Digital Trust, and Uncertainty Avoidance is crucial in the decision-making process regarding the implementation of Industry 4.0 technology. The slow adoption of Industry 4.0 technology is attributed to non-technological factors or people, while the need to achieve energy efficiency targets necessitates examining the influence of Sustainable Attitudes and Digital Trust as supporting variables, along with Uncertainty Avoidance, on technology adoption. The study employed a quantitative explanatory research approach to investigate the relationships and impacts of variables. It centered on employees of Schneider Electric Indonesia, a global Industry 4.0 technology provider, with a sample of 189 employees selected through random sampling, incorporating a 5% margin error from Slovin formula. The analysis involved the use of Structural Equation Modeling (SEM) with AMOS version 26. Industry 4.0 technology is essential for fostering innovation and business expansion, leading to a sustainable environment by offering principles, guidance, and energy-efficient technologies for companies. The involvement of Sustainable Attitude, moderated by Uncertainty Avoidance, is vital in reaching energy efficiency goals through Industry 4.0 implementation.

: The agriculture sector is one of the backbones of many countries’ economies and its processes have been changing in order to enable technological adoption to increase productivity, quality, and sustainable development. In this research, we present a theoretical reflection through a scientific mapping of the adoption of precision techniques and breakthrough technologies in agriculture, the so-called Precision Agriculture (PA) and Agriculture 4.0 (A4.0). To do this, we used 4,694 documents from the Web of Science database to perform a Bibliometric Performance and Network Analysis (BPNA) of the literature with the support of the PICOC protocol and the SciMAT software. Our findings present 22 strategic themes related to Digital Agriculture (DA) such as Internet of Things (IoT) and Climate-smart Agriculture (CSA) among others, and the thematic network structures of the motor themes and the thematic evolution structure of the field of the study over time. In addition, our results discuss the main challenges and opportunities of DA. Our findings have the potential to provide insights for practitioners and researchers in decision-making and pave the way for future works.

This research assess the effects of training program based on the usage of the digital learning objects in teaching practice at the Northern Borders University staff. E Assessment through the tablets and smart phones and the teachers’ attitudes towards such way of evaluation is the major objective of this study as the researcher expects that the assessment mechanism in the university through utilization of tablets and smart phones and its application will inevitably bring in a systematic improvement in the assessment and evaluation process of the curricula. Moreover, making use of the e learning objects in training will make a significant change in e training program of the university. Hence, the researcher has chosen voluntary random samples from the university teaching staff (men\women) from various different faculties (medicine, medical sciences, science, education and arts, business administration, home economics, and science and literature). These samples included 300 members of the teaching staff. In a group of 20 to 25 members, a personal training was conducted regarding the usage of tablets and smart phones and its applications in the assessment process. Each group participated by producing a complete e-assessment for their students in the Northern Borders University and by the e learning system i.e. Blackboard and Question Mark. The research also depends on the semi-experimental design of multiple groups and on testing the groups’ pre and post achievement tests. In addition, the research identifies the level of the university teaching staff in using the tablets and the smartphones and its applications in the assessment process by the note card that the individuals have during the test.

This article explores how digitalisation is impacting the hospitality industry and assesses the evolving role of Information Technology (IT) strategy in the digitalisation process. The research approach is qualitative and inductive, based on six in-depth interviews with senior IT professionals in the hospitality industry. Findings indicate significant differences in the role of IT strategy in guiding digitalisation in the companies studied. The depth of information provided by the interviewees supports the development and application of a model that profiles the companies regarding their degree of digitalisation and technology integration. Analysis of interview material allows the identification of key properties for successful digitalization: process agility, workforce adaptability, and technology manageability, along with a clear data culture and ensured cybersecurity. However, disparate systems and technologies, and a lack of data integrity, are key issues that leave hospitality companies with difficult choices in progressing digitalisation initiatives. The applied model and identification of key properties for successful digitalisation contribute to the development of related theory and can also be used as a reference point for senior IT professionals working in the industry.

This paper exposes the initial part of a research consisting in a need analysis carried out by the Romanian partner in the Erasmus+ "Media Education for Aware Adults" project, regarding digital competences and media education of adult educators or trainers. After a short introduction on the subject, in the paper are presented the main findings of the desk research, and two focus group sessions, first one for identifying the necessary digital competences of adult educators, and second one for identifying the elements that educators need in order to adequately support adults in their learning process, especially in relation to the digital environment. The results of the initial research will lead to the development of the main intellectual outputs, namely the digital competences framework, handbook, online platform and training material on digital and media education. In their development will be taken into account, on the one hand, the needs identified in the initial research, and, on the other hand, the need for a sustainable approach to all activities, resources and outputs produced, as well as education itself, this goal being assumed through the project.

The emergence of digital twins (DTs) represents a recent advancement in technological processes that support the planning, construction, and oversight of constructed assets. A DT is essentially a digital model that facilitates simulations and two-way information exchange with its real-world counterpart (a physical twin), creating opportunities for data-driven decision-making. Despite the promising prospects of DTs, both the technology and the methodologies for developing them, as well as their potential applications, remain not fully understood in both academic and industrial contexts. This research explores the applications of DTs for the management of existing assets within the AEC/FM industry. The study presents the results of a comprehensive literature review that explores existing knowledge in this domain. The findings reveal that procedures for creating DTs are still in their early stages, emphasizing potential applications in asset management throughout their lifespan, facilitating sustainability upgrades, and supporting the maintenance and restoration of heritage assets. The review concludes by providing recommendations for future research in this evolving field.

Short-form video has taken over social media and attracted attention from advertisers. As brands shift their advertising spending to short-form video social platforms, doubts remain about the advertising efficacy on these platforms, especially given the skyrocketing advertising costs in recent years. In a large-scale randomized experiment on ByteDance in collaboration with an automobile brand, we show a significant effect of the advertising campaign on ByteDance, compared with effects reported in other studies. Exposed users are eight times more likely to convert from outside than from within ByteDance, which raises the importance of information sharing between the platform and brands. When considering conversions outside ByteDance, the average cost per conversion, which brands commonly use to evaluate the cost of campaigns, shrinks by 5 or 25 times, depending on the methods used to calculate it. Information sharing can also affect a brand’s targeting strategy. While commonly used demographic variables by the automobile brand are effective for target marketing with only platform data, they are not when considering conversions outside ByteDance. Instead, a behavioral variable proposed herein (prior brand home page visits) effectively moderates the advertising effect but has no effect when including only platform data in the analysis.

Dynamic simulation of district heating and cooling networks has an increased importance in the transition towards renewable energy sources and lower temperature district heating grids, as both temporal and spatial behavior need to be considered. Even though a lot and research and development has been performed in the field, there are several pitfalls and challenges towards dynamic district heating and cooling simulation for everyday use. This article presents the experiences from working with district heating and cooling projects, along with relevant research, corresponding research gaps and proposed research directions.

Achieving effective control over microbial contamination necessitates the precise and concurrent identification of numerous pathogens. In this research, we have devised a remarkably sensitive duplex droplet digital PCR (dddPCR) reaction system to simultaneously detect Pseudomonas aeruginosa (P. aeruginosa) and Pseudomonas fragi (P. fragi). Employing comparative genomics, we identified four genes of P. fragi. By specific analysis, RS22680 gene was selected as the detection target of P. fragi and LasR gene was chosed as P. aeruginosa, which were applied to construct a dddPCR reaction. In terms of specificity, sensitivity and anti-interference ability, the constructed dddPCR detection system was verified and analyzed. The assay showed excellent sensitivity and applicability, as evidenced by a limit of detection of 100 CFU/mL. When the concentration of natural background bacteria in milk or fresh meat was 100 times that of the target detection bacteria, the method was still capable of completing the absolute quantification. In the simulation of actual sample contamination, P. aeruginosa could be detected after 3 h of enrichment culture, and P. fragi could be detected after 6 h. The established ddPCR detection system exhibits exceptional performance, serving as a foundation for the simultaneous detection of various pathogenic bacteria in food products.

The growth of social media has changed the face of many aspects of marketing such as online, digital, etc. It also has changed the way modern human communicates and connects with others. Moreover, the behavior on this platform could not and should not be justified with strategies of other marketing channels and media. Due to the nature of social media, they are rich in precise and lean data, but processing these data and extracting knowledge and insights from them are problematic. Evaluating the effectiveness of a marketing endeavor is also a task related to these data. The current research attempts to assess the effectiveness of an advertising campaign on Instagram via advertising cost and sentiment classification of audience opinion regarding the campaign. The methodology used in this research is the standard process of data mining, i.e., CRISP-DM. Furthermore, multiple machine learning models and approaches were studied to train a prediction model based on data. In order to find the most accurate algorithm, grid search was used among the trained models and different algorithms with different combinations of hyper-parameters. The obtained results revealed that although the number of not profitable advertising media was higher than the profitable media, the overall status of the campaign was profitable, both in the cost-effectiveness approach and sentiment analysis approach. The other valued outcome of this research was important general and specific insights which can be used to shape a better-performing and effective advertising campaign on Instagram.

The flourishing landscape of agritourism in Albania has witnessed a steady increase in destinations over the years. Recognizing their pivotal role in driving economic development in rural areas, considerable attention is directed towards the promotion and expansion of these agricultural tourism spots. To enhance interactivity with visitors, these agritourism destinations actively leverage social networks and various digital platforms. However, the wealth of information pertaining to these destinations is currently scattered across different platforms, posing a challenge to accessibility. To address this issue, these points are strategically placed on Google Maps, along with essential details collected from users, such as websites, contact numbers, visitor ratings, and comments. Nevertheless, other valuable data remains dispersed on various social networks. In response to this fragmentation, this study proposes the development of algorithms and scripts to systematically collect and analyze this dispersed information. By doing so, the goal is to centralize and streamline the data, enabling a comprehensive understanding of the agritourism landscape in Albania. This approach not only facilitates efficient access to information for potential visitors but also provides valuable insights for stakeholders involved in the development and management of these agritourism destinations. The study aims to contribute to the sustainable growth of agritourism in Albania by harnessing the power of digital platforms to create a unified and organized database. Through this integration, the research seeks to unveil patterns, trends, and opportunities that can further guide policy-making, marketing strategies, and overall decision-making processes in the realm of agritourism development.

Abandoned, lost, or otherwise discarded fishing gear (ALDFG) is a primary contributor to the entanglement of numerous marine species. Utilizing digital media platforms like Google, Facebook, and Instagram we conducted an assessment of the detrimental effects of ALDFG and plastic litter, on the biodiversity of Italy's marine ecosystem. Our investigation revealed that plastic litter has adverse consequences on various forms of marine life, including reptiles, mammals, birds, fish, crustaceans, and mollusks, along different Italian geographical sub-areas. Several records of interaction between plastic and endangered and vulnerable marine species have been described. Our reports even highlight the impact on marine turtles, mainly on Caretta caretta. This is the first report of entangled with fishing nets in Cetorhinus maximus, Oblada melanura, Serranus scriba, Homarus gammarus, Octopus vulgaris, and Phoenicopterus roseus. Furthermore, we identified that ghost nets have repercussions for endangered and vulnerable marine species. This update sheds light on the ongoing adverse effects of ghost nets on the Italian marine ecosystem, yet it is crucial to acknowledge that the true extent of the problem remains underestimated.

Engineering the supply chain requires a design that possesses the flexibility of a complex adaptive system, consisting of interlinking architecture, with external dimensions and system germane internal elements. The complexity of the subject, the multiple environments, dimensions, elements and concepts, require a research that does not set any limits to the conceptual, analytical or empirical nature of the existing approaches present in practice. This present the rational for applying a taxonomy approach to investigate the integration engineering of supply chain architecture, design and engineering, and building a framework for integrating the existing supply chain approaches. The objectives of this paper are to critically analyse the key supply chain concepts and approaches, to assess the fit between the research literature and the practical issues of supply chain architecture, design and engineering, and to develop a methodology that could be used by practitioners when integrating supply chain architecture and design with strategy engineering. Taxonomy approach is applied to consider criteria for strategy architecture, hierarchical strategy design, strategy engineering, and integration of supply chain architecture, design and engineering as a conceptual system. The results from this paper derived with the findings that the relationship between supply chain architecture, design and engineering is weak and challenges remain in the process of adapting and aligning operations. This paper also derived with a novel approach for addressing these obstacles, based on a new methodology. The novelty that derives from this paper is a methodology for integrating supply chain architecture, design and engineering, with criteria that enable decomposing and building a digital (new and non-existent) supply chain as a system. The paper revealed a number of tools and mechanism which enabled the development of a new methodology for integrating the architecture, design and engineering of a supply chain. The review derived with improvements to current and existing theories for analysing interdependencies within and between their individual contexts. This issue is addressed with a hierarchical method for network design, applied for building and combining the integration criteria.

INT-FFT algorithm presented in this work uses an interpolation methodology to densify 3D-GPR datasets to sharpen images obtained in GPR surveys obtained in an archaeological context. It allows the reconstruction of missing data from the combined use of mathematical transforms (e.g., the Fourier and Curvelet transform) and predictive filters. This technique makes it possible to calculate the missing signal simply by meeting two requirements: the data in the frequency domain must be limited in a range of values and must be able to be represented by a distribution of Fourier coefficients (verified conditions). The INT-FFT algorithm uses an open-access routine (Suinterp, Seismic Unix) to interpolate the GPR profiles based on seismic trace interpolation. This process uses automatic event identification routines by calculating spatial derivatives to identify discontinuities in space by detecting very subtle changes in the signal, thus allowing for more efficient interpolation without artifacts or signal deterioration. We successfully tested the approach using GPR datasets from the Roman Villa of Horta da Torre (Fronteira, Portugal). The results show an increase in the geometric sharpness of the GPR reflectors and have not produced any numerical artifacts. The tests performed to apply the methodology to GPR-3D data allowed for assessing the interpolation efficiency, the level of recovery of missing data, and the level of information lost when one chooses to increase the distance between profiles in the acquisition stage of the data.

Structure from Motion with Multi-View Stereo photogrammetry (SfM) is increasingly utilised in geoscience investigations as a cost-effective method of acquiring high resolution (sub-meter) topographic data, but has not been thoroughly tested in gullied savanna systems. The aim of this study was to test the accuracy of topographic models derived from aerial (via an Unmanned Aerial Vehicle, ‘UAV’) and ground-based (via a handheld digital camera, ‘Ground’) SfM in modelling a hillslope gully system in dry-tropical savanna, and to assess the strengths and limitations of the approach at different scales. A UAV survey covered an entire hillslope gully system (0.715 km²), whereas a Ground survey covered a single gully within the broader system (650 m²). SfM topographic models, including Digital Surface Models (DSM) and dense point clouds, were compared against RTK-GPS point data and a pre-existing airborne LiDAR Digital Elevation Model (DEM). Results indicate UAV SfM can deliver topographic models with a resolution and accuracy suitable to define gully systems at a hillslope scale (e.g., 0.1 m resolution with ~ 0.5 – 1.3 m elevation error), while ground-based SfM is more capable of quantifying gully morphology (e.g., 0.01 m resolution with ~ 0.1 m elevation error). Key strengths of SfM for these applications include: the production of high resolution 3D topographic models and ortho-photo mosaics, low survey instrument costs (< $AUD 3,000); and rapid survey time (4 and 2 hours for UAV and Ground survey respectively). Current limitations of SfM include: difficulties in reconstructing vegetated surfaces; uncertainty as to optimal survey and processing designs; and high computational demands. Overall, this study has demonstrated great potential for SfM to be used as a cost-effective tool to aid in the mapping, modelling and management of hillslope gully systems at different scales, in tropical savanna landscapes and elsewhere.

Sustainability is the core concern of every business; The exploration of avenues to maintain sustainability while staying competitive with high level of productivity remains a vital endeavor. Production flexibility is a key area that can enhance the sustainability of manufacturing industries as it can ensure product availability, scalability, agility/fault tolerance as well as disaster recovery potentials. Technological advancements have provided avenues where companies can enhance virtually all aspects of their operations for efficiency, effectiveness, and productivity. This paper uses both quantitative and qualitative research approach to identify the capability requirements for smart and effective production management and subsequent analysis is done using Multi-Criteria Decision-Making methodology to identify and rank various industry 4.0 technologies and concepts that can provide these smart capabilities in in manufacturing industries to aid the businesses to achieve sustainability with production flexibility. The paper identifies over 12 smart capabilities and 9 Industry 4.0 Technologies which are applicable to production management. It also compares results from the analytics of historical I4.0 implementation as discussed in literatures with the current state as deduces from survey feedbacks from various manufacturing industries.

Histologically poor differentiation is associated with lymph node metastasis. Thus, pathological evaluation of biopsy specimens is crucial when treating stomach cancers. Deep learning of WSIs is challenging because the images are enormous. Given the computing limitations, patch-level supervised learning methods have been proposed. However, valuable information is lost when dividing WSIs into smaller patches. Another drawback is the need for pixel-level annotation by a pathologist. It is acceptable to differentiate, i.e., grade, gastric cancer at the holistic tissue level (i.e., under low magnification). We developed a weakly supervised learning technique for tissue-level gastric adenocarcinoma histological differentiation (well-to-moderately or poorly differentiated) and applied global reasoning to tissue-level features. The tissue-level AUROCs of the histological differentiation classifiers were 0.953, 0.969, and 0.943, respectively when data from five hospitals were subjected to threefold cross-validation. Comparison of the Grad-CAM heatmaps of the trained classifier and the pathologists’ annotations confirmed that our weakly supervised model exhibited performed well.

Climate change and food security are the most relevant issues to be considered in sustainable agricultural development. The FAO’s initiative of climate-smart agriculture has attracted international attention. Since then, the smart agriculture (SA) has been recognized as the most influential trends in contributing to agricultural development. Therefore, encouraging farmers to adopt digital technologies and mobile devices into farming practices becomes a policy priority worldwide. However, there is limited literature available on psychologic factors that drive farmers’ intentions to adopt SA technologies. The purpose of this study is to investigate how farmer’s knowledge and attitude toward SA affects their adoption of smart technologies in Taiwan. A total of 321 farmers participated in the project’s survey in 2017 and 2018, from which the data was used to perform an OLS regression model of SA adoption. This study contributes to a preliminary understanding of relationship between innovation and adoption of SA technologies in a small-scale farming economic context. The findings suggest that the policy makers and R&D institutes need to concentrate on improving market access for well-known and high important SA technologies.

The main purpose of this study was to design a workplace in the conditions of a digital factory. The goal of this study is to compile a proposal for improving the layout solution in the selected enterprise to reduce material flows between individual workplaces. In addition, the workplace research study uses methods of material flow analysis with the application of visTABLE software support, which serves as a tool for designing production processes. The main result of the study was the reduction of the production time of the beam by 10 minutes and the creation of proposals for solutions for the company. The study helped with the visualization of processes within the digital factory to simplify and clarify processes at the workplace.

Background: Industry revolution 4.0 (IR.4.0) paradigm, nurses were required to have adequate competencies to carry out their professional duties. Digital information should be mastered by the nursing student. Purpose: This study aims to explain digital literacy competencies on nursing students in the era of IR 4.0 in the Indonesian context. Methode: A literature review was conducted in this study using Rayyan Systematic Reviews Software. Results: There was 14 literature analyzed describing Student’s Information literacy competency and Internet of Thing. Conclusion: Digital literacy for nursing students today is an inevitability, and nursing students who have digital literacy competencies have the potential to be able to increase nursing knowledge and skills as ontological competencies in their learning process.

During the COVID-19 pandemic, online media were the most widely used source of scientific information. Often, they are also the only ones on science-related topics. Research has shown that much of the information available on the Internet about the health crisis lacked scientific rigor and that misinformation about health issues can pose a threat to public health. In turn, millions of Catholics were found to be demonstrating against vaccination against COVID-19 based on "false" and misleading religious arguments. This research analyses publications about the vaccine in Catholic online media with the aim of understanding the presence of information (and misinformation) in this community. An algorithm designed for each media outlet collected COVID-19 vaccine-related publications from 109 Catholic media outlets in five languages. In total, 970 publications were analysed for journalistic genres, types of headlines and sources of information. The results show that most publications are informative and most of their headlines are neutral. However, opinion articles have mostly negative headlines. Also, a higher percentage of the opinion authors come from the religious sphere and most of the sources cited are religious. Finally, 35% of the publications relate the vaccine to the framing issue of abortion.

Usually, towed hydrophone arrays are instrumented with a set of compasses. Data from these sensors are utilized while beamforming the acoustic signal for target bearing estimation. However, elements of the hydrophone array mounted in the neighborhood of a compass can affect the Earth’s magnetic field detection. The effects depend upon the kind of elements present in the platform hosting the compass. If the disturbances are constant in time, they can be compensated for by means of a magnetic calibration. This process is commonly known as soft and hard iron compensation. In this paper, a solution is presented to carry out the magnetic calibration of a COTS (Commercial Off The Shelf) digital compass without unattainable sensor motion. This approach is particularly suited in applications where a physical rotation of the platform that hosts the sensor is unfeasible. In our case, the platform consists in an assembled and operational towed hydrophone array. A standard calibration process relies on physical rotation of the platform and thus on the use of the geomagnetic field as a reference during the compensation. As a variation on this approach, we provide to the sensor an artificial reference magnetic field to simulate the unfeasible physical rotation. We obtain this by using a tri-axial Helmholtz coil, which enables programmability of the reference magnetic field and assures the required field uniformity. In our work, the simulated geomagnetic field is characterized in terms of its uncertainty. The analysis indicates that our method and experimental set-up represent a suitably accurate approach for the soft and hard iron compensation of the compasses equipped in the hydrophone array under test.

Scanning underwater areas, using magnetometers, in search of unexploded ordnance is a difficult challenge, where machine learning methods can find a significant application. However, this requires the creation of a set enabling the training of prediction models. Such a task is difficult and costly due to the limited availability of relevant data. To meet this challenge in the article, we propose the use of numerical modeling to solve this task. The conducted experiments allow us to conclude that it is possible to obtain high compliance of the numerical model with the results of physical tests. In addition, the paper discusses the methodology of simplifying the computational model, allowing for almost three times reduction of the calculation time. In addition, in the work we present the methodology of creating an appropriate data set, enabling the generation of any number of training samples.

Various therapeutic approaches have been developed for neglect. Many studies have demonstrated the effect of Digital therapeutics(DTx) on neglect. By contrast, only a few studies have reported on the effects of DTx on egocentric and allocentric neglect. In this article, seven studies on DTx of egocentric and allocentric neglect were reviewed. DTx, which was employed in these studies, could be classified as follows: 1) software adaptation in traditional treatment, 2) VR game using the head-mount display as treatment, and 3) development of new digital program like ReMoVES. In addition, more studies and effective results were reported on egocentric neglect than allocentric neglect. In future studies, each effect on egocentric and allocentric neglect should be identified in detail through the appropriate use of differential evaluation and long-term application of independent digital therapeutics.

Today, the digital economy has pursued the required social and economic development, and enterprises can achieve long-term sustainability by relying on the digital platform ecosystem. However, the development of the digital economy and the rapid growth of platform ecosystems have also generated some problems. To study effective digital platform ecosystem governance, this study used the tripartite evolutionary game method and analyzed the changes and effects of platform regulation under different development stages from the perspectives of government, platforms, and enterprises. The results indicate that in the early stages, digital platforms primarily relied on the government’s obligation to regulate. With the digital platform ecosystem’s evolution, the platform organization and settled enterprises’ governance effects gradually appeared, establishing the three common constraints of governance mode. Finally, when the digital platform ecosystem is in its self-renewal period, the government effect is reduced, with the platform itself and settled enterprises taking primary supervisory roles. This study provides reasonable methods for effective platform governance at different stages and enriches the theoretical basis and management practices of platform ecosystems.

This paper delves into the application of digital twin monitoring techniques for enhancing offshore floating wind turbine performance, with a detailed case study. We explore the practical implementation of digital twins and their efficacy in optimizing operations and predictive maintenance. Our findings emphasize digital twins' potential as a valuable tool for renewable energy, driving efficiency and sustainability in offshore floating wind installations.

The Coronavirus (COVID-19) pandemic has created big challenges and opportunities in Higher Education (HE). In this situation, several universities worldwide have responded with digital methods and hybrid classes in a short period of time. The aim of this paper is to show how the universities have adapted teaching methods to digital platforms in the academic year 2020–21. This case study is based on the experience of 37 postgraduate communication students in the course Business and Communication from a Communication Programme. The objective of this course was to promote the 17 sustainable development goals (SDGs) in business and following the Principles for Responsible Management Education (PRME) of the United Nations. To do this, the students provided different solutions related to the SDGs and developed a communication strategy to inform and engage the stakeholders in the companies analyzed in a hybrid class. The results show that using this methodology and working in digital platforms, students have learned the importance of SDGs through implementing specific solutions linked to the corporate social responsibility (CSR) strategy. Based on this analysis, they also developed a communication strategy showing how companies can improve society with specific actions through the lens of the SDG perspective.

Multiple valued logic (MVL) has proven to be a better alternative and solution to the challenges of traditional binary logic because of its fast computation, fewer interconnects, and small die. It is a potential candidate for future digital design because it allows energy-efficient, low-complex, and high-speed circuits. This paper introduces a new resistive-load two-dimensional field effect transistor-based ternary logic gates, wherein the active resistive-load is replaced with memristor to reduce chip area and power consumption. A memristor-based standard ternary inverter (STI) is designed using GNRFET, MoS2 FET, WSe2 FET, and FinFET, and their performance metric such as delay, power, and energy delay product (EDP) are analyzed. The results show that the proposed design achieves 50% reduction in circuit area, the average power dissipation is reduced by 11.7X, 6.8X, and 3.2X for GNRFET, MoS2 FET, and WSe2 FET, respectively, as compared to FinFET-based ternary inverter. Moreso, other logic gates such as OR, NOR, AND and NAND were simulated in T-SPICE EDA tool, and the results and truth table are in good agreement.

COVID-19 pandemic instigated a digital revolution in academia and higher education. Social distancing, months-long quarantine, as economic shutdown will help the majority of people working in academia and higher education not only to complete their personal transition to the fully functional and operational online tuition, but also to understand that online defences, online entrance and final exams, as well as online academic jobs are as effective and meaningful as those conducted “in real life”. Due to the crisis induced by the coronavirus epidemic, innovations in academia and higher education that would have normally taken several years due to the various contradictory administrative regulations are now introduced promptly in a matter of days. This is a clear example of the Schumpeterian ‘creative destruction’ in making that will forever change the status quo in academia and higher education.

In response to the issues of sensor noise and accumulated motion errors that lead to low positioning accuracy and insufficient robustness during large maneuvers or continuous flight of small unmanned aerial vehicles (UAVs) in complex environments, this paper proposes a multi-source and multimodal data fusion method. Initially, it employs a multimodal data fusion of various sensors including GPS (Global Positioning System), IMU (Inertial Measurement Unit), and visual sensors to complement the strengths and weaknesses of each hardware component, thereby eliminating motion errors to enhance accuracy. To mitigate the impact of sudden changes in sensor data, the method introduces a digital twin UAV data source. By utilizing the Extended Kalman Filter algorithm, it fuses data from both the real UAV and its digital twin, and the filtered positional information is fed back into the control system of the real UAV. This enables real-time correction of UAV positional deviations caused by sensor noise and environmental disturbances. The multi-source multimodal fusion Kalman filter method proposed in this paper significantly improves the positioning accuracy of UAVs in complex scenarios and the overall stability of the system. This method holds significant value in maintaining high-precision positioning in variable environments and has important practical implications for enhancing UAV navigation and application efficiency.

Quantitative phase imaging by digital holographic microscopy (DHM) is a nondestructive and label-free technique, that has been playing an indispensable role in the field of science, technology, and biomedical imaging. The technique is competent for the imaging and analysis of label-free living cells and the investigation of reflective surfaces. Herein, we introduce a new configuration of a wide field-of-view single-shot common-path off-axis reflective DHM for the quantitative phase imaging of biological cells that leverages with several advantages including less-vibration sensitive to external perturbations due to common-path configuration, compact in size, simple in optical design, highly stable, and cost-effective. A detailed description of the proposed DHM system, including its optical design, working principle, and capability of phase imaging, is presented. The applications of the proposed system are demonstrated by quantitative phase imaging results obtained from the reflective surface (USAF resolution test target) as well as transparent samples (microlens array and living plant cells). The proposed system could find its applications in the investigations of several biological specimens and optical metrology of micro-surfaces.

We present a case of Capnocytophaga canimorsus septic shock after a dog bite in an immunocompetent individual, where real-time nanopore metagenomic sequencing characterized the microbial agent within 19 hours, with subsequent confirmation using droplet digital PCR. Oral swabs from the dog demonstrated a nearly-identical C. canimorsus isolate by sequencing.

The ageing of the population is growing significantly and will challenge healthcare systems. Chronic diseases in the older population require a change in service delivery, and new technologies can be a key element in ensuring the viability and sustainability of these systems. However, the generation gap and the physical and cognitive decline commonly associated with the older generation are barriers to the transition to these models of care. Despite this, there has been a trend towards digital healthcare, which has many potential benefits for the older population. Numerous studies have assessed the acceptability of new technologies for older people in health care. These studies highlight the importance of perceived usefulness, compatibility, ease of use and personalisation of the technology. Personalisation is necessary to ensure that the system is useful for users, and different characteristics such as country of origin, gender, age or comfort with the technology should be taken into account. A person-centred approach in the development of new health technology systems is essential to ensure that applications can be better tailored to the needs of different ageing populations. Many organisations have dedicated time and resources to ensure a person-centred approach in the development of new health technology systems, and putting the individual first is the best way forward in digital health. This article presents the work carried out in this regard in the framework of the European TeNDER project together with an analysis of the results obtained in terms of satisfaction, usefulness and usability by end users.

One of the most critical aspects in introral impression is the detection of the finish line, in particular in case of subgingival preparations. The aim of these in vitro study was to evaluate the accuracy among four different IntraOral Scanners (IOSs) in scanning a subgingival vertical margins preparation (VP). A reference maxillary typodont (MT) was fabricated with a VP for full crown on #16 and #21. The MT was scanned with a laboratory scanner (Aadva lab scanner, GC, Tokyo, Japan) to obtain a digital MT (dMT) in .stl format file. A group of 40 digital casts (dIOC) were obtained by scanning the MT 10 times with four different IOSs (Trios 3, 3Shape A/S), ( I700, Medit), (Vivascan, Ivoclar), (Experimental IOS, GC). All the obtained dIOCs were imported into an inspection software program (Geomagic Control X; 3D SYSTEMS) to be superimposed to the dMT, to calculate trueness. Therefore, in order to calculate precision all the scans of the same scanner group were superimposed onto the cast that obtained the best result of trueness. Results were collected as root mean square value (RMS) on #16 and #21 abutment surfaces and on a marginal area positioned 1 mm above and below the gingival margin. A nonparametric analysis Kruskal-Wallis test was performed to compare the RMS values obtained in the different iOS groups for trueness and precision. Statistically significance was set at 0.05. The trueness on #16 abutment, did not statistically differ in between the IOS, while on #21 abutment, Vivascan (56.0 ±12.1) and Experimental IOS, GC (59.2±2.7) performed statistically better than the others. Regarding precision Experimental IOS, GC and Trios 3 were significantly better than I700 and Vivascan both in the #16 (10.7±2,1; 15.8 ± 2,7) and in the #21 area (16.9±13.8 ; 18.0±2.7). At marginal level for both #16 and #21 all the IOS reported reduced accuracy compared to clinical acceptance.

The management of a cultural change in higher education is becoming necessary and unavoidable: changes in teaching, changes in research and changes in governance. Digital transformation is an essential part of many countries’ modernisation agendas. The aim of this non-experimental, descriptive, survey-based study was to explore the perceptions of university students toward the digital transformation that took place in university teaching as a consequence of COVID-19. The specific objectives proposed were to: a) analyse the perceptions of students toward digital transformation in university teaching; b) determine the valuation of students about the digital transformation that occurred in university teaching as a result of COVID-19; and c) explore the resources (hardware-software), professional collaboration, digital pedagogy and student empowerment (motivation) with respect to digital education and the recent changes in university teaching due to the pandemic. The results show that a large number of items are positively correlated. In conclusion, further research should delve into motivation, collaboration, reflective experience sharing, self-learning and initiatives that promote the development of competences in future teachers.

In this paper, we study the effect of decreasing aperture diameter on signal transmission from the scintillator to the PMT. The apertures have been inserted directly between the scintillator and the photomultiplier. Three different aperture diameters have been used over a wide energy range.A newly developed fast digital spectrometer has been utilised for experimental measurement in the radial channel of the VR-1 research reactor. The detector signals with and without inserted apertures have been measured and evaluated. The aim of our research was to determine the effect of the apertures on the spectral quality, energy range and the evaluated physical quantities.

In recent years, Chinese manufacturing enterprises compete to chase the wave of "digital revolution", digital empowerment has become an important strategic path of technological reform for many manufacturing enterprises. Based on the micro data of listed companies, this paper investigates the impact of digital transformation of Chinese listed companies on the quality of their export products. It is found that digital transformation can significantly improve the quality of enterprises' export products. After a series of robustness tests, this conclusion is still valid, and there are two ways to improve innovation performance and total factor productivity. The export product quality enhancement effect of enterprise digital transformation also has the heterogeneity of ownership, region and industry. In the further study, this paper also examines the impact of digital transformation on the internal salary gap of enterprises, and finds that digital transformation may increase the internal salary gap of enterprises, and form a "masking effect" on the quality of export products. To a certain extent, this paper deepens the understanding of the study of enterprise digital transformation on the quality of export products and its differences, and provides certain guidance for enterprises to implement the strategy of digital transformation.

The structure of self-reinforced composites (SRCs) based on ultra-high molecular weight 21 polyethylene (UHMWPE) was studied by means of Wide-Angle X-Ray Scattering (WAXS), X-Ray 22 tomography, Raman spectroscopy, Scanning Electron Microscopy (SEM) and in situ tensile testing 23 in combination with advanced processing tools like Avizo, ImageJ, and Ncorr to determine the cor-24 relation between the processing conditions, on the one hand, and the molecular structure and 25 mechanical properties, on the other. SRCs were fabricated by hot compaction of UHMWPE fibers at 26 different pressure and temperature combinations without addition of polymer matrix or softener. 27 It was found by WAXS that higher compaction temperatures led to more extensive melting of 28 fibers with the corresponding reduction of the Herman’s factor reflecting the degree of molecular 29 orientation, while the increase of hot compaction pressure suppressed the melting of fibers within 30 SRCs at a given temperature. X-Ray tomography proved the absence of porosity while polarized 31 light Raman spectroscopy measurements for both longitudinal and perpendicular fiber orienta-32 tions showed qualitatively the anisotropy of SRC samples. SEM revealed that the matrix was 33 formed by interlayers of molten polymer entrapped between fibers in SRCs. Moreover, in situ 34 tensile tests demonstrated the increase of Young’s modulus and tensile strength with increasing 35 temperature.

The textile and clothing (T&C) industry is not usually viewed as an exemplar of sustainable de-velopment and the circular economy, as the industry has hitherto made its products in linear fashion, with relatively little recycling of the finished goods. This article examines the industry’s approach to the core sustainability concept and the circular economy in particular, through a re-view of the available academic literature, evidence from corporate sustainability reports and websites, and feedback from an online survey of industry professionals. The role of digital technology deployment in engendering sustainability and the circular economy in the industry is also explored. The study finds that whilst sustainability is now firmly embedded at the strategic level in the vast majority of companies studied, attitudes towards the circular economy remain fickle. The use of digital technologies in support of sustainability objectives is also limited at present, but the article concludes that the need to meet compliance requirements and new cus-tomer perceptions of sustainability will speed the transition to circular economy activities, facili-tated by greater exploitation of digital technologies. Building upon the research findings, existing models and an initial conceptual framework, a simple operational model for initiating such a transition for small-to-medium sized enterprises in the T&C industry is put forward.

As digital technologies rapidly integrate into Health Professions Education (HPE), gaining a comprehensive understanding of cyberethics becomes crucial. This scoping review aimed to explore the pedagogy of cyberethics within HPE, with an emphasis on its definitions, conceptualizations, theoretical foundations, and interventions. Drawing from 37 documents spanning 2012-2022, primarily originating from the U.S. and encompassing both peer-reviewed and grey literature, the study highlighted a significant gap in the explicit definition and conceptualization of cyberethics. Additionally, the evident lack of specific theoretical frameworks in the majority of these documents could hamper the progression and replicability of research. Among the reviewed articles, only four introduced cyberethics educational interventions, indicating a substantial avenue for future research. While the study utilized comprehensive search methods, limitations such as language biases and the potential omission of pertinent documents were present. Future investigations should broaden the cyberethics discourse to encompass emerging technologies and their ethical implications within HPE. Crafting comprehensive, culturally sensitive, and inclusive guidelines is pivotal in nurturing ethical digital practices in the health care community.

In the field of modeling social systems, the use of agent-based models (AM) has become a powerful tool for understanding processes occurring in society, in particular, for studying the spread of infections among the population. The agent model is based on a synthetic population consisting of agents, their interactions and sometimes the territory in which the interaction occurs. The choice of an appropriate method for creating such artificial populations and the selection of parameters becomes a key issue affecting the realism of the model and its ability to reflect real-world scenarios. This article delves into the interplay between agent-based modeling, synthetic population construction, and parameter selection, offering our insight into the complex process of modeling infectious disease dynamics. The review concludes with an exploration of extending the Covasim model [1] to experiments in computational epidemiology. Covasim, a dynamic transmission modeling tool, is known for its ability to adapt to different scenarios and offers predictive information critical for managing epidemiological situations. The Covasim model could include improvements to better simulate real-world epidemic conditions, including a revised transmission strategy to account for accumulation through daily contacts. In addition, we propose to add a module for intercity travel and a visualization package that will significantly expand the functionality of Covasim. These improvements make Covasim a more versatile and efficient tool for modeling and analyzing epidemic processes.

Digital literacy is the ability to use digital technologies to find, evaluate, create, and communicate information. People with disabilities benefit from having these skills because they allow them to access various opportunities in the digital world. To ensure that they can fully participate in the digital realm, digital literacy efforts should prioritize inclusive design principles. People with disabilities often rely on assistive technologies such as screen readers, alternative input devices, voice recognition software, or specialized hardware to navigate digital platforms. Digital literacy programs should not only focus on consuming content but also on creating and sharing it through documents, multimedia, and online platforms. Peer support and collaboration are important for enhancing their learning experience. Additionally, digital literacy programs address cybersecurity or online safety considerations specific to such people and provide them training and support for using assistive technologies effectively while educating them about potential risks, privacy settings, and safe online practices. This narrative review highights the meaning and levels of digital literacy, digital divide, history, before expanding on the quantative metrics in the available research on the theme of people with disabilities. Retrieved data from freely accessible internet search engines revealed 196 publications, including books, chapters in books, original research articles, proceedings of seminars, and reviews, which were classified into harvest plots to be analyzed by their format, timelines, topics, or themes, respectively. While results indicate an upward curve in the quantity of publications, especially in the post-millennium era, the topics addressed are unevenly distributed, leaving scope for the future to focus empirical and evidence based research on themes related to measurement as well as training on digital literacies for both teachers and students with disabilities. By promoting digital literacy in people with disabilities, we can bridge the digital divide and empower them to participate fully in today's increasingly digital society.

This review article conducts an in-depth analysis of the role of next-generation technologies in soilless vegetable production, highlighting their groundbreaking potential to revolutionize yield, efficiency, and sustainability. These technologies, such as AI-driven monitoring systems and precision farming methods, offer unparalleled accuracy in monitoring critical variables like nutrient concentrations and pH levels. However, the paper also addresses the multifaceted challenges that hinder the widespread adoption of these technologies. The high initial investment costs pose a significant barrier, particularly for small and medium-scale farmers, thereby risking the creation of a technological divide in the industry. Additionally, the technical complexity of these systems demands specialized expertise, potentially exacerbating knowledge gaps among farmers. Ethical considerations are scrutinized, including data privacy concerns and potential job displacement due to automation. Regulatory challenges, such as international trade regulations and policy frameworks, are discussed as they may need revision to accommodate these new technologies. The paper concludes by emphasizing that while these sustainable technologies offer transformative benefits, their potential for broad adoption is constrained by a complex interplay of financial, technical, ethical, regulatory, and social factors. Comprehensive, multi-faceted solutions are therefore essential for their ethical and equitable implementation.

This research examines the impact of social equity on energy consumption. We constructed a digital twin for residential energy consumption by enriching the synthetic population with real-world surveys and feeding them with other environmental and appliance data to the energy modeling framework. We analyzed household hourly energy consumption data from Albemarle County and Charlottesville City in Virginia, USA, for the year 2019. We used clustering analysis to identify patterns in social equity and energy consumption. The results demonstrated the impact of different residential attributes on energy poverty. Statistical analyses, including ANOVA and Chi-Squared tests, were conducted to test for significant differences between racial groups in quantitative and categorical variables. The study found that race is significant in determining the location and quality of housing. People of color often live in areas with higher pollution and less access to green spaces. Additionally, income levels and the age of the house are influential factors in determining energy efficiency. Future work should focus on collecting and analyzing data at the country level and using qualitative data collection methods to gain a more comprehensive understanding of social equity issues concerning energy consumption. Overall, this study provides valuable insights into the relationship between different residential attributes and energy consumption, which can inform policy development to promote more equitable and sustainable communities.

Studies show that executive functions and motor development are associated among each other and with learning ability. A more technological lifestyle, related with digital culture, should be considered an important component to stimulate children. In addition, digital games constitute an element of the digital culture in which children are inserted. The aim of this study is to present a systematic mapping of the literature involving executive functions, motor development and the use of digital games in intervention programs for elementary school children, from 6 to 11 years old. Four databases were searched: PubMed, Scielo, Science Direct and SCOPUS, including publications between 2012 and March 2021. The initial results indicated 4881 works. After the selection process, 15 investigations that presented the central theme of the study were selected. The main results indicate that intervention strategies are quite heterogeneous. Most of the studies demonstrated significant positive effects after intervention protocols and were conducted in Europe and 46% of the studies were conducted in a school environment. No researches were identified that involved technological solutions involving executive functions, motor development and digital games in an integrated manner, constituting a field of future scientific research.

The efficacy of the product development process is measured by the ability to launch a project with product and production process specifications that could guarantee that the manufacturing can produce it with the least impact. If a problem is detected late, they bring consequences beyond the high cost of the solution, if related to physical ergonomics, which will influence the well-being of operators, productivity, and quality. Virtual Reality (VR) and Digital Human Modeling (DHM) are ones of the enabling technologies of Industry 4.0 and has already been applied on a large scale in industries such as automotive, construction, and aeronautics. However, even though the huge applications, these technologies are not yet applied by these industries for the analysis of physical ergonomics during product development phases. This study aims to characterize the state of the art and technology about the application of Virtual Reality and Digital Human Modeling for the physical ergonomics analysis in the during product development phases in the industry through a systematic review of the literature and patents. In patent documents recovery, we used Derwent Innovation database. The research is based on searching the selected terms in the title, summary, and claims of the documents through a search strategy containing IPC code and keywords. In articles recovery, we searched ScienceDirect, Springer, and IEEExplore databases for scientific publications. The search resulted in 311 patents documents and 16 articles in the scientific database. This study analyzed the patents to map out the technological progress in this area, where we found in the charts and data an increasing number of publications per year and a spread application with a considerable number of new technologies presented in these recent patents. The literature review indicated that Virtual Reality technology complements the Digital Human Modeling during physical ergonomics analysis for manufacturing process already designed. The majority of research on the use of VR and DHM technologies for physical ergonomics analysis focus on the automotive industry and the ergonomic assessment of workstations and current processes. Further research is needed to investigate how Virtual Reality and Digital Human Modeling might assist in the understanding of physical ergonomics in certain tasks throughout the product development process, such as the simulation of worker posture or effort when assembling parts.

This research delves into librarians' perceptions of artificial intelligence (AI) support in learning experiences, lifelong learning, and digital literacy within the library context, undertaking a comparative analysis between Malaysia and Indonesia. Employing a survey methodology, a self-developed questionnaire was administered to 59 librarians in Malaysia and 85 in Indonesia. The questionnaire, utilizing a Likert scale, systematically explored subjective judgments on AI's impact across various dimensions. A noteworthy finding is the consistent and harmonized perception among librarians in both countries, underscoring a universal recognition of AI's perceived support for learning experiences, lifelong learning, and digital literacy. Of particular interest is the emphasis on sustainability in librarians' perspectives, as they recognize the enduring value of AI in fostering educational growth. Despite the limitations inherent in perceptual measures and a relatively modest sample size, the empirical and practical contributions of this study are significant. It offers a nuanced exploration of librarians' viewpoints, providing valuable insights for future research endeavors. Moreover, the study's findings have immediate practical implications for the integration of AI tools in library services, policy-making, and professional development, with a focus on ensuring sustainable implementation for long-term benefits.

The benefits of event-driven architecture (EDA) derive from how systems and components are loosely coupled, which can facilitate independent development and deployment of systems, improved scaling and fault tolerance, and integration with external systems, especially in comparison to monolithic architectures. With the advent of new technologies such as containers, and microservices, a new generation of distributed event streaming platforms are commonly used in event-driven architecture for efficient event-driven communication. However, the asynchronous and distributed nature of EDA poses several problems that include handling failures, the dependence of an end-to-end transaction on individual component stability, etc. In this paper, we describe a new approach to designing self-regulating distributed applications with autopoietic and cognitive workflow management. This approach is based on the new science of information processing structures derived from the General Theory of Information. Just as a genome enables self-organizing and self-regulating biological structures, a digital genome enables a specific software application with several components, the ability to use distributed resources and self-regulate the evolution of the system based on functional and non-functional requirements, and best-practice policies that maintain the stability, safety, and survival under non-deterministic fluctuations in the demand for resources. In addition, cognitive workflow management assures end-to-end transaction delivery.

Background: The use of technology in paediatrics is increasing, and new health technology will change the way in which paediatric care is delivered in the future. This review is part of the Royal College of Paediatrics and Child Health Paediatrics 2040 project, which is developing a credible vision for the future of paediatrics in the UK. Aims: To summarise the impact of health technology on the delivery of paediatric care over the last ten years. To learn from existing technology use and make recommendations for future implementation. Methods: A search strategy was developed and two databases (Cochrane Library and PubMed) were systematically searched in August 2019 for relevant publications in English. Searches were limited to papers published between January 2009 and August 2019 (with further rapid review of papers published between September 2019 and November 2020). We included papers that studied young people up to the age of 24 or on those providing care for this population. A thematic synthesis of the data from the included studies was undertaken using seven domains of paediatric care. Results: 128 studies were included, grouped by domain of care. Most included studies were defined as digital (n=55) or communication (n=37). Studies looked at the different types of health technology used within different domains of care, including secondary and tertiary care (n=39), public health and prevention (n=29), and community (n=20). Studies were assessed on delivery of care outcomes using positive, negative, mixed and no effect. The most common outcomes reported were adherence and satisfaction. Discussion: This review highlights the growing importance of technology in delivering paediatric care. Six themes emerged: the importance of clear guidelines, continuity of care, confidentiality and privacy, digital poverty, using a personalised approach, and using technology to supplement rather than replace. In future, technology development should involve the end user throughout the design process.

Biocultural heritage preservation relies on ethnobotanical knowledge and the paleoethnobotanical data used in (re)constructing histories of human-biota interactions. Biocultural heritage, defined as the knowledge and practices of Indigenous and Local peoples and their biological relatives, is often guarded information, meant for specific audiences and withheld from other social circles. As such, these forms of heritage and knowledge must also be included in the ongoing data sovereignty discussions and movement. In this paper we share the process and design decisions behind creating an online database for ethnobotanical knowledge and associated paleoethnobotanical data, using a content management system designed to foreground Indigenous and local perspectives. Our main purpose is to suggest the Mukurtu content management system, originally designed for physical items of cultural importance, be considered as a potential tool for digitizing and ethically circulating biocultural heritage, including paleoethnobotanical resources. With this database, we aim to create access to biocultural heritage and paleoethnobotanical considerations for a variety of audiences while also respecting the protected and sensitive natures of Indigenous and local knowledges.

The purpose of this study is to bring out a scientometric analysis of the advances of digital transformation in the global banking sector. For this, a background search of the term "Digital Transformation Banking " has been brought out from the Web of Science (Wos) Database, covering records published between 2002 and 2023. A set of 312 publications was identified, which mainly includes a set of 264 academic articles, 29 articles published without cataloging a specific volume of a journal, 9 articles under review, 5 editorial material documents, 4 conference articles, and 1 document is a book chapter. Nowadays the scientific production is low but showing growing development presenting 123 publications and 7,754 citations for the year 2022. Among the scientific production, 43 publications from the Republic of China (8.8%) and 35 publications from Ukraine (7.8%) stand out. ,2%). It is also worth mentioning that the most relevant authors on this topic are Ricardo Palomo, professor and dean of San Pablo University, and Robert J Kauffman, professor at Singapore Management University in terms of influence. Main institutions in terms of scientific production, mainly: the Massachusetts Institute of Technology (MIT) of the United States and the Russian Academy of Sciences of Russia.

Symbolic semantic understanding of staff images is an important part in music information retrieval. Due to the complex composition of staff symbols and the strong semantic correlation between symbol spaces, it is difficult to understand the pitch and duration of each note during performances. In this paper, we design a semantic understanding system for optical staff symbols. The system uses the YOLOv5 to implement optical staff’s low-level semantic understanding stage, which understands the pitch and duration in natural scales and other symbols that affect the pitch and duration. The proposed note encoding reconstruction algorithm is used to implement high-level semantic understanding stage. Such algorithm understands the logical, spatial, and temporal relationships between natural scales and other symbols based on music theory, and outputs digital codes for the pitch and duration of main notes during performances. The model is trained with a self-constructed SUSN dataset. Experimental results of YOLOv5 show that the precision is 0.989 and the recall is 0.972. For the system, the error rate is 0.031 and the omission rate is 0.021. The paper concludes by analysing the causes of semantic understanding errors and offers recommendations for further research. The results of this paper provide a method for multimodal music artificial intelligence applications such as notation recognition through listening, intelligent score flipping and automatic performance.

The home is becoming a key location for healthcare delivery, including the use of technology driven by autonomous systems (AS) to monitor and support healthcare plans. Using the example of a smart mirror, this paper describes the outcomes of focus groups with people with multiple sclerosis (MS; n=6) and people who have had a stroke (n=15) to understand their attitudes towards the use of AS for healthcare in the home. We thematic analysis to analyse the data. The results indicate that the use of such technology depends on the level of adaptability and responsiveness to the users’ specific circumstances, including their relationships with the healthcare system. A smart mirror would need to support manual entry, responsive goal setting, effective aggregation of data sources and integration with other technology, have a range of input methods, be supportive rather than prescriptive in messaging, and give the user full control of their data. Barriers to adoption include a perceived lack of portability and practicality, lack of accessibility and inclusivity, a sense of redundancy, being overwhelmed by multiple technological devices, and a lack of trust in data sharing. These results inform the development and deployment of future health technologies based on the lived experiences of people with health conditions who require ongoing care.

Fundamental science and applied research and technology development (RTD) are facing significant challenges that particularly compound to the notorious credibility, reproducibility, funding and sustainability crises. The underlying, serious shortcomings are substantially amplified by a metrics-obsessed publication culture, and a growing cohort of academics fishing for fairly stagnant (public) funding budgets. This work presents, for the first time, a groundbreaking strategy to successfully address these severe issues; the novel strategy proposed here leverages the distributed ledger technology (DLT) “blockchain” to capitalize on cryptoeconomic mechanisms, such as tokenization, consensus, crowdsourcing, smart contracts, reputation systems as well as staking, reward and slashing mechanisms. This powerful toolbox, which is so far widely unfamiliar to traditional scientific and RTD communities (“TradSci”), is synergistically combined with the exponentially growing computing capabilities for virtualizing experiments through digital twin methods in a future scientific “metaverse”. Project contributions, such as hypotheses, methods, experimental data, modelling, simulation, assessment, predictions and directions are crowdsourced using blockchain, and captured by so-called non-fungible tokens (“NFTs”). The so enabled, highly integrative approach, termed decentralized science (“DeSci”), is destined to move research out of its present silos, and to markedly enhance quality, credibility, efficiency, transparency, inclusiveness, sustainability, impact, and sustainability of a wide spectrum of academic and commercial research initiatives.

Within the framework of theoretical developments in so-called participatory culture and the context of funds of identity, incorporated within what is known as the funds of knowledge approach, an innovative teaching methodology is implemented that allows students to actively participate in knowledge construction. The project translates into a proposal for educational contextualization and personalization based on the students’ funds of identity, that is, those resources (people, artifacts, places, activities, institutions) they consider to be most relevant and significant to define themselves. Once these have been identified through identity artifacts, such as collages or self-drawings, students link some of these funds of identity to curricular content of the subject and produce a video that shows the results of this academic work. The final product is shared on a YouTube channel containing the videos of all of the students in the class. The phases of the project are described and illustrated. We argue that the proposed teaching and learning project, which is cross-disciplinary in nature, allows for principles such as educational contextualization, funds of identity, and participatory culture to be incorporated into what we call here the funds of identity 2.0 approach, putting it into educational practice.

Facing unprecedented global declines in the extent and integrity of ecosystems, the 15^th UN Biodiversity Conference (COP-15) in Kunming, China, presents an opportunity for transformative change. However, a lack of consensus on two key issues – resource mobilization and Access and Benefit Sharing (ABS) associated with Digital Sequence Information (DSI) – risks stalling negotiations for an ambitious ‘Post-2020 Global Biodiversity Framework’ as the next 10-year strategic plan under the Convention on Biological Diversity. We highlight systemic misconceptions concerning the financing of biodiversity and the burden this places on the ABS system. In the context of DSI, we caution that conflating ABS with resource mobilization risks disrupting modern science policy built on open access, with potentially severe ramifications for scientific research and innovation. To resolve these tensions, we call for a recalibration of discussions on ABS in order to maximize the value delivered by biodiversity for all of society, including indigenous peoples and local communities.

Most of the research of mental fatigue evaluation mainly concentrated on some indexes that require sophisticate and large instruments which make the detection of mental fatigue cumbersome, time-consuming, and difficult to apply on a large scale. A quick and sensitive mental fatigue detection index is necessary so that mental workers can be alerted in time and take corresponding countermeasures. But to date, no studies have compared the sensitivity of common objective evaluation indexes. To solve these problems this study recruited 56 human subjects. These subjects were evaluated using six fatigue indexes: the Stanford sleepiness scale, digital span, digital decoding, short-term memory, critical flicker fusion frequency (CFF), and speed perception deviation. The results of fatigue tests before and after mental fatigue were compared, and a one-way analysis of variance (ANOVA) was performed on the speed perception deviation. The result indicated the significance of this index. Considering individual differences, the relative fatigue index (RFI) was proposed to compare the sensitivity of the indexes. The results showed that when the self-rated fatigue grade changed from non-fatigue to mild fatigue, the ranges of RFI values for digital span, digital decoding, short-term memory and CFF were 0.175–0.258, 0.194–0.316, 0.068–0.139, and 0.055–0.075, respectively. Correspondingly, when the self-rated fatigue grade changed from non-fatigue to severe fatigue, the ranges of RFI values for the above indexes were 0.175–0.258, 0.194–0.316, 0.068–0.139, and 0.055–0.075, respectively. These results suggest that the sensitivity of the digital decoding, digital span, short-term memory, and CFF decreased sequentially when the self-evaluated fatigue grade changed from no fatigue to mild or severe fatigue. The RFI individuality of the speed perception deviation is highly variable and is not suitable as an evaluation index. In mental fatigue testing, digital decoding testing can provide faster, more convenient, and more accurate results.

3D-printing with foam concrete, which is known for its distinct physical and mechanical properties, has not yet been purposefully investigated. The article at hand presents a methodological approach for the mixture design of 3D-printable foam concretes and a systematic investigation of the potential application of this type of material in digital construction. Three different foam concrete compositions with water-to-binder ratios between 0.33 and 0.36 and having densities of 1100 to 1580 kg/m³ in the fresh state were produced with a pre-foaming technique using a protein-based foaming agent. Based on the fresh-state tests, including 3D-printing as such, an optimum composition was identified and its compressive and flexural strengths were characterised. The printable foam concrete showed compressive strength above 10 MPa and low thermal conductivity, which make it suitable for 3D-printing applications, while fulfilling both load-carrying and insulating functions.

This paper shows the results of applying high-resolution Unmanned Aircraft System (UAS) photogrammetric surveying on a large landslide. A real case study, where permanently installing GCPs could be complex, where natural shaped and formed land pose severe limitations in deploying ground targets with optimal geometric configuration. We analysed performances in terms of survey accuracy obtained by performing photogrammetric surveys through the Zenmuse P1 DJI optical camera and Phantom 4 Pro 2. In combination with DJI Matrice 300 UAS, the P1 camera allows direct georeferencing through GNSS observations in RTK mode. Photogrammetric surveys, performed through different georeferencing methods, have been compared. Several targets have been permanently installed on the ground over the maximum vegetation height to guarantee long-lasting reference over the years in the area, which is characterised by a diffuse short vegetation coverage. Multitemporal UAS surveys have been then compared using Digital Image Correlation (DIC) algorithms, and deformation maps have been produced. Afterwards, DIC results were compared with observations made by the GNSS ground-based permanent receivers resulting in a standard deviation of 0,077 m. Through results analysis, good accordance between ground-based GNSS observations and DIC analysis on the photogrammetric surveys have been identified for the same time span. To conclude, this type of landslide presents a moderate deformation speed; in such a case, effective deformations monitoring could be achieved using pseudo-direct georeferencing, which permitted a 0.24 m accuracy on the whole tested area.

In response to the growing inspection demand exerted by process automation in component manufacturing, Non-destructive testing (NDT) continues to explore automated approaches that utilize deep learning algorithms for defect identification, including within digital X-ray radiography images. This necessitates a thorough understanding of the implication of image quality parameters on the performance of these deep learning models. This study investigates the influence of two image quality parameters, namely Signal-to-Noise Ratio (SNR) and Contrast-to-Noise Ratio (CNR), on the performance of U-net deep learning segmentation model. Input images were acquired with varying combinations of exposure factors such as kilovoltage, milli-ampere, and exposure time, which altered the resultant quality. The data was sorted into 5 different datasets according to their measured SNR and CNR values. The deep learning model was trained 5 distinct times, utilizing a unique dataset for each training session. Training the model with high CNR values yielded an intersection over Union (IoU) metric of 0.9594 on test data of the same category but drops to 0.5875 when tested on lower CNR test data. The result in this study emphasizes the importance of achieving a balance in training dataset according to the investigated quality parameters, to enhance the performance of deep learning segmentation models in NDT radiography applications.

Welding processes offer a unique capability with a wide range of applications in industries. In recent times, welding has established itself as a tool for large scale additive manufacturing. In general, the quality and repeatability assurance for welding and specifically for additive manufacturing necessitates integrating process monitoring techniques with existing welding and additive manufacturing processes. The process-specific signals such as welding current fluctuations, temperature, and acoustic, generated during the welding operations, make them a suitable candidate for digitization. This chapter comprehensively describes the process monitoring techniques relevant to welding and additive manufacturing. Firstly, various sensors used during welding are described for their construction and working. Subsequently, specific applications of the sensors in digitizing the welding processes are presented.

When “hijacked” by compulsive behaviors that affect the reward and stress centers of the brain, functional changes in dopamine circuitry occur as the consequence of pathological brain adaptation. As a brain explanans for mental health, with a central functional role in behavioral regulation from healthy reward seeking to pathological adaptation to stress in response to adversity, we may use dopamine regulation in interaction with other brain mechanisms, as discussed herein, to gather a deeper insight into environmentally triggered mental health changes to understand, for example, specific behavioral changes observed during and after the COVID-19 pandemic. Pandemic-related adversities, the stresses they engendered, and the long lockdown periods where people had to rely on digital tools to get feed-back rewards via the internet can be seen as the major triggers of changes in motivation and reward seeking behavior worldwide. The pathological adaptation of dopamine-mediated reward circuitry in the brain offers a highly plausible explanation why, when pushed by fate and circumstance into a physiological brain state of anti-reward, human behavior and mental health changes almost inevitably depending on individual vulnerability to stress. A unified conceptual account that places dopamine function at the centre of the current global mental health context is proposed.