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Cracks exist in the majority of components of ancient Chinese timber structures and have led to serious mechanical property degradation problems, threatening the safety of the whole structures and making the cracks' detection for wooden components a necessity. With the rapid development of intelligent protection technology of cultural buildings, it is important to establish a scientific identification and quantification method for cracks in wooden components to replace traditional manual detection techniques. Deep learning is precisely such an advanced technology. In this study, images of cracked wooden components were first collected from the Yingxian wooden pagoda and the crack characteristics were analyzed. A dataset for crack segmentation was established using a total of 501 images of cracked wooden components, including a training dataset of 450 images and a validation dataset of 51 images. Based on the mathematical principles of deep learning and the fully convolutional neural networks (FCNN), a deep fully convolutional neural network (d‐FCNN) model was constructed based on encoding and decoding methodology. Four model indicators, pixel accuracy (PA), average pixel accuracy (mPA), mean intersection over union (mIoU), and F1‐score were analyzed to train the model and determine the optimal model parameters, including learning rate, batch size, and epoch. It concluded that the optimal initial learning rate takes the value of 10−4, batch size of 6, and epoch of 100, achieving the average accuracy of 78.8%. Further, based on the pixel's accumulation principle, a quantitative calculation method for crack length and maximum width was proposed. Two cracked wooden columns were prepared, and crack image identification and quantification experiments were conducted to verify the correctness of the constructed d‐FCNN model and the proposed crack quantification method. The results show that the model is suitable for crack intelligence detection, identification, and quantification of cracked wooden components. [ABSTRACT FROM AUTHOR]

ABSTRACT Recent work in philosophy of technology has come to bear on the question of responsibility gaps. Some authors argue that the increase in the autonomous capabilities of decision‐making systems makes it impossible to properly attribute responsibility for AI‐based outcomes. In this article we argue that one important, and often neglected, feature of recent debates on responsibility gaps is how this debate maps on to old debates in responsibility theory. More specifically, we suggest that one of the key questions that is still at issue is the significance of the reactive attitudes, and how these ought to feature in our theorizing about responsibility. We will therefore provide a new descriptive categorization of different perspectives with respect to responsibility gaps. Such reflection can provide analytical clarity about what is at stake between the various interlocutors in this debate. The main upshot of our account is the articulation of a way to frame this ‘new’ debate by drawing on the rich intellectual history of ‘old’ concepts. By regarding the question of responsibility gaps as being concerned with questions of metaphysical priority, we see that the problem of these gaps lies not in any advanced technology, but rather in how we think about responsibility. [ABSTRACT FROM AUTHOR]

Extrusion-based 3D bioprinting techniques are revolutionizing bioengineering by facilitating the creation of complex 3D microstructures. This review offers a thorough overview of extrusion-based 3D bioprinting methods, particularly highlighting the innovative electric-assisted coil-write 3D bioprinting technology. The review begins by explicating the fundamental principles underlying various extrusion-based 3D bioprinting technologies. It covers the printing equipment composition, suitable materials for 3D bioprinting, and the latest breakthroughs in technology. A critical aspect of this review is the in-depth comparison of the strengths and weaknesses associated with each 3D bioprinting approach. The electro-microfluidic extrusion method and the electric-assisted coil-write 3D bioprinting technology are highlighted. This advanced technology successfully overcomes the limitations of conventional extrusion-based methods, notably in the precise printing of intricately curved line structures with high resolution and speed. This method ingeniously integrates mechanical motion for creating microscale features with electrical coiling for sub-micron details, thus achieving remarkable printing speeds and structural complexity. This review concludes by exploring the potential applications and future advancements of this state-of-the-art technology. It underscores the ability of electric-assisted coil-write 3D bioprinting to develop pioneering materials and micro-devices for a variety of technological sectors, highlighting its transformative impact in bioengineering. [ABSTRACT FROM AUTHOR]

Amid the rapid advancement of technology, social robots are increasingly becoming a part of human society. This study explored the associations between promotion focus, prevention focus, anthropomorphism, facial expression, monetary sacrifice, and overall attitudes with users' intention to use social robots. We employed a survey-based design and analyzed data from 300 adult users through partial least squares structural equation modeling. The results showed significant associations of promotion focus, anthropomorphism, monetary sacrifice, and overall attitude with the intention to use social robots. Notably, monetary sacrifice was associated with a positive perception, indicating that higher costs might be seen as an indicator of superior quality and advanced technology. Conversely, prevention focus and facial expression did not show significant associations with the intention to use social robots. These findings provide useful guidelines for product developers and marketers in social robotics who want to appeal to consumers while optimizing both time and cost. [ABSTRACT FROM AUTHOR]

This study posits that U.S.-China technology competition has promoted the spread of techno-economic statecraft in East Asia. The emergence of techno-economic statecraft in East Asia requires systematic analysis because it affects not only the dynamics of U.S.-China technology competition but also the restructuring of the regional order. Since both the United States and China do not have complete self-sufficiency in the high-tech innovation ecosystem, it has become an urgent task for them to reduce their vulnerability to winning technological competition. Against this backdrop, East Asian countries have emerged as actors playing an important role in technological competition. Since East Asian countries are key players in the supply chain of high-tech industries, cooperation with East Asian countries has emerged as a factor that can influence the landscape of U.S.-China technology competition. Based on these observations, this study aims to explain the following four phenomena: First, it explains the process by which the United States and China seek to securitize high technology as a means of reducing their own structural vulnerabilities while redrawing new boundaries for cooperation with East Asian countries. Second, I argue that U.S.-China technology competition has accelerated the rise of techno-economic statecraft in East Asia. Third, I assert that there are significant differences in the techno-economic statecraft pursued by East Asian countries in the U.S.-China technology competition. Fourth, the divergence of techno-economic statecraft in East Asian countries has created systemic effects in the regional order. [ABSTRACT FROM AUTHOR]

Summary The advanced technology in recent years that has achieved more attention among researchers and the social community is the wireless sensor network (WSN) that includes a number of nodes that are commonly distributed in remote zones. While deploying the WSN in huge areas, WSNs produce a massive amount of data. Thus, there is a significant need to process the data through efficient models. The data aggregation technique is the common solution widely employed to obstruct congestion on large‐scale WSNs. However, the demanding part of the data aggregation scheme is to mitigate the network overhead without affecting the system efficiency. Most of the data transmitted by sensor nodes are repetitious and thus result in high power consumption. Therefore, sensor nodes should utilize an efficient data aggregation model for data transmission that minimizes duplicate data. In order to maintain such complications, this article proposes a hierarchical Taylor quantized kernel least mean square (HTQKLMS) filter for aggregating data in WSN. For this purpose, WSN is initially simulated, and then data aggregation is accomplished using developed HTQKLMS filter. Additionally, the HTQKLMS is derived by amalgamating the hierarchical fractional quantized kernel least mean square (HFQKLMS) filter with the Taylor series. Here, the data prediction mechanism is done by employing HFQKLMS model that is an integration of quantized kernel least mean square (QKLMS) and hierarchical fractional bidirectional least mean square (HFBLMS). Apart from this, data redundancy is achieved by broadcasting needed data utilizing data detected at the destination. Furthermore, HTQKLMS approach has delivered a minimum energy consumption of 0.0333 J and less prediction error of 0.0326. [ABSTRACT FROM AUTHOR]

High-resolution and thermal infrared hyperspectral data acquired from the Thermal Infrared Airborne Spectrographic Imager (TASI) have been recognized as efficient tools in geology, demonstrating significant potential for rock discernment. Deep learning (DL), as an advanced technology, has driven substantial advancements in lithological mapping by automatically extracting high-level semantic features from images to enhance recognition accuracy. However, gathering sufficient high-quality lithological samples for model training is challenging in many scenarios, posing limitations for data-driven DL approaches. Moreover, existing sample collection approaches are plagued by limited verifiability, subjective bias, and variation in the spectra of the same class at different locations. To tackle these challenges, a novel sample generation method called multi-lithology spectra sample selection (MLS3) is first employed. This method involves multiple steps: multiple spectra extraction, spectra combination and optimization, lithological type identification, and sample selection. In this study, the TASI hyperspectral data collected from the Liuyuan area in Gansu Province, China, were used as experimental data. Samples generated based on MLS3 were fed into five typical DL models, including two-dimensional convolutional neural network (2D-CNN), hybrid spectral CNN (HybridSN), multiscale residual network (MSRN), spectral-spatial residual network (SSRN), and spectral partitioning residual network (SPRN) for lithological mapping. Among these models, the accuracy of the SPRN reaches 84.03%, outperforming the other algorithms. Furthermore, MLS3 demonstrates superior performance, achieving an overall accuracy of 2.25–6.96% higher than other sample collection methods when SPRN is used as the DL framework. In general, MLS3 enables both the quantity and quality of samples, providing inspiration for the application of DL to hyperspectral lithological mapping. [ABSTRACT FROM AUTHOR]

Calcitonin gene-related peptide monoclonal antibodies (CGRP mAbs) are novel high-cost treatments for the prevention of migraine. This study presents data on utilization, expenditure, and treatment patterns with CGRP mAbs available under a managed access protocol in Ireland, to a cohort of treatment refractory patients (failed 3 or more previous treatments) with chronic migraine. Data were extracted from the Primary Care Reimbursement Service High Tech claims database and special drug request online system and analyzed using Microsoft Excel and SAS. Treatment persistence was evaluated by refill patterns, and adherence was evaluated using the proportion of days covered method. Expenditure data were extracted directly from the database. Between September 1, 2021 and April 30, 2023, 1517 applications for reimbursement approval for a CGRP mAb were received; 1458 (96.1%) were approved for reimbursement. Total expenditure on CGRP mAbs in year 1 (September 1, 2021 to August 31, 2022) was €3.2 million. The majority of patients initiated treatment with fremanezumab (60.8%) or erenumab (37.1%). Almost 90% of patients were considered adherent, and treatment persistence was high, with more than 75% of patients receiving more than 12 months of treatment in our 18-month study time frame. This study demonstrates the importance of active health technology management, after reimbursement, in enabling cost-effective use of high-cost treatments while providing budget certainty for the healthcare payer. High levels of adherence and persistence suggest that treatment is successfully targeted in situations which unmet clinical need is greatest. • Calcitonin gene-related peptide monoclonal antibodies are novel, high-cost treatments for the prevention of migraine. • In 1 year of reimbursement in Ireland, the total expenditure on calcitonin gene-related peptide was €3.2 million, with the majority of approved patients being highly treatment adherent. • Health technology management can ensure cost containment while maintaining access to treatment in situations which unmet clinical need is greatest. [ABSTRACT FROM AUTHOR]

A new decoupling element technology is used to create a tiny circular patch mutiple input multiple output (MIMO) antenna measuring 20 × 25 × 1.6 mm3. A simple split‐ring resonator (SRR) metamaterial design with adjustable inner ring inductance and capacitance allows MIMO antennas to operate across several frequency bands. Tunable‐split ring resonators (T‐SRRs) are small and improve antenna element isolation. The proposed MIMO system provides isolation larger than 20 dB from 5.93 to 12.63 GHz. It is useful for radar applications since it includes the C‐band upper link (5.925–6.425 GHz) and the X‐band (8–12 GHz). With good tuning and network structure decoupling, antennas can operate in dual bands with isolation levels below −15 dB. Over 85% radiation efficiency and 72% miniaturization were achieved in the proposed MIMO antenna. The antenna has good radiation and diversity performance, including an envelope correlation coefficient < 0.1 and a diversity gain of 9.98 dB. These qualities make it suitable for advanced technology. [ABSTRACT FROM AUTHOR]

In tracking scenarios involving groups with dense targets, achieving effective data association is challenging due to mutual occlusion and interference among targets. The complexity of the tracking problem is further exacerbated in low‐observable environments by the increase in false alarm rates. The track‐before‐detect (TBD) is an advanced technology for detecting and tracking low‐observable targets, effectively mitigating data association problems by integrating multi‐frame echo data. However, the existing multi‐target TBD algorithms typically assume that the targets are spatially separated and are not suitable for scenarios involving group targets. A group target maximum‐likelihood probabilistic data association (GT‐ML‐PDA) algorithm, based on the concept of TBD, is proposed to track group targets effectively in low‐observable environments. The proposed algorithm divides group target tracking into two stages: group centre trajectory estimation and individual target trajectory estimation. To enhance the performance of the proposed algorithm, two strategies are suggested: modifying the equivalent measurements and extracting independent measurement sets for individual targets. Simulation results demonstrate that the proposed algorithm is capable of effectively tracking numerous individual targets within a group, even in the presence of heavy clutter. [ABSTRACT FROM AUTHOR]

In a construction project, especially in risky environments, subcontractors are considered as important as the main contractor since most work is carried out by them. A crucial step in building projects is choosing the finest subcontractor. When choosing subcontractors, a variety of considerations must be taken into account. A poor choice of subcontractors might cause a lot of issues when the job is being done. These include subpar work and project length delays. Many things influence this process. From earlier studies, variables that affect the choice of a subcontractor have been compiled. The main aim of the paper is to predict the failure of the subcontractor by using a mix of several advanced technology as BIM, machine leaning and building a system. The methodology of the paper is first to use BIM to see the mistakes and unqualified quantity estimation by the subcontractors which lead to increase the cost of the projects and hence failures of the projects. The second step is to identify primary reasons for subcontractors' failure and identify and evaluate the major reasons why contractors fail on industrial projects in Iraq. The third step is to predict the performance of the subcontractor using three algorithms (logistic regression, decision tree and Naive Bayes) with data collected from 234 projects and see how the wrong selection of the subcontractors leads to incomplete projects in the future. The variables that used in the paper include the most effective one, as change order effect directly on the projects performance as well as cost, time, deviation, type of projects and the rate of project completion, the low the percentage of completion the worse the performance. The final step is to develop a system to manage the subcontract in different projects stage. The results show that there is a different in the quantity estimated between the actual and the estimated range between (5% to 15%) in several item of the building, which consider high. the best algorithms for the is Naive Bayes as give accuracy about 97%. [ABSTRACT FROM AUTHOR]

Soft robots have been advancing rapidly, but their control is still limited by rigid control elements. Soft valves offer a solution to this problem by enabling soft robots to no longer rely on rigid control elements. They have become an emerging research topic in soft robotics. However, with a large number of publications on soft valves, it may be challenging for researchers to quickly grasp the advanced technology related to soft valves. To address this issue, this article summarizes the current state of development in soft valves. The design principles and applications of soft valves in terms of structures and materials are discussed, along with the modeling ideas for soft valves. Finally, the current challenges faced by soft valves are outlined, and potential solutions to these problems are proposed. [ABSTRACT FROM AUTHOR]

Gastroesophageal reflux disease (GERD), a prevalent clinical condition, is often attributed to aberrant esophageal motility, leading to gastric content reflux and associated symptoms or complications. The rising incidence of GERD presents an escalating healthcare challenge. Endoscopic and esophageal reflux monitoring can provide a basis for the diagnosis of patients with gastroesophageal reflux disease, but when the diagnostic basis is at an inconclusive value, some additional supportive evidence will be needed. Advanced technology is the key to improving patient diagnosis, accurate assessment, and the development of effective treatment strategies. High-resolution esophageal manometry (HREM) and endoscopic functional lumen imaging probe (EndoFLIP) represent the forefront of esophageal motility assessment. HREM, an evolution of traditional esophageal manometry, is considered the benchmark for identifying esophageal motility disorders. Its widespread application in esophageal dynamics research highlights its diagnostic significance. Concurrently, EndoFLIP's emerging clinical relevance is evident in diagnosing and guiding the treatment of coexisting esophageal motility issues. This review integrates contemporary research to delineate the contributions of HREM, EndoFLIP, and novel technologies in GERD. It examines their efficacy in facilitating an accurate diagnosis, differentiating similar gastrointestinal disorders, quantifying the extent of reflux, assessing the severity of the disease, forecasting patient responsiveness to proton pump inhibitor therapy, and guiding decisions for surgical interventions. The overarching aim is to deepen the understanding of GERD's underlying mechanisms and advance the formulation of holistic, efficacious treatment approaches. [ABSTRACT FROM AUTHOR]

This study on regional development investigates if digital transformation is a means to attract innovative establishments to municipalities. By doing so, the relationship between the availability of high-speed broadband close by and the number of innovative establishments (workplaces) across all 290 municipalities in Sweden is explored. Panel data for eleven years (2010-2021) originate from official registers. Results based on Fixed Effects Poisson estimations including spatially weighted variables indicate that the digital transformation in the guise of high-speed broadband access is important for ICT (micro) establishments and those in declining municipalities, although the proportion of highly skilled inhabitants renders stronger estimates. For high technology and R&D establishments, access to high-speed broadband is not a relevant location factor. The estimates are robust to endogeneity as tested by the control function approach. [ABSTRACT FROM AUTHOR]

The promotion of R&D carries the risk that economically strong regions will benefit to a greater extent and that regional disparities will increase by focusing the economy on high technology. However, this is expected to depend on the specific sectoral and technological composition of R&D funding. R&D funding for a bio-based economy in Germany is particularly illustrative for a shift in funding focus from a narrow concept of biotechnology to a broader concept of bioeconomy. Along with this shift, an impact on the spatial distribution of R&D funding is assumed. Against the background of inclusive innovation policy, this study examines the potential of the bioeconomy for a reduction of regional disparities in public R&D funding. Based on a database containing publicly-funded R&D projects in Germany and further regional data, comparative regressions are conducted in order to identify spatial patterns. The results demonstrate distinct funding mechanisms in the different areas of the bioeconomy. The broadening of R&D funding for bio-based activities from the biotechnology vision towards bioresources and bioecology leads to a greater participation of rural and lagging regions which is expected to be the result of the inclusion of more traditional industries as recipients of R&D funding. [ABSTRACT FROM AUTHOR]

The Fourth Industrial Revolution, shortly called Industry 4.0, is a technology-based paradigm characterized by fully automated and unmanned smart factories to increase productivity and efficiency in manufacturing and production environments. Although Industry 4.0 has been successful in its economic goals in the last decade, its negative effects on social and environmental sustainability have been discussed for a long time. As a result of the discussions focusing especially on the exclusion of human workforce and potential from production environments, the European Commission announced a novel approach in 2021 called Industry 5.0, with the vision of benefiting from all advanced technology for, and with humans. This new paradigm, which points out a human-centric, resilient, and sustainable European industry for the future, suggests prioritizing the needs and well-being of employees and society rather than economic concerns in the development, design, and adaptation of innovative technologies. In this study, the adaptation of the Industry 5.0 approach to supply chain management is examined on the basis of human centricity, and a framework for strategic and technological requirements is presented for a successful implementation. [ABSTRACT FROM AUTHOR]

China is indeed the biggest investor in South Africa but it is very important to understand the effects that its investment has on the youth of South Africa. This study aims to analyse whether China's investment empowers the youth of South Africa through entrepreneurial skills, access to advanced technology, and provisions of scholarships. The findings of the study reveal that there is a level of inconsistency when it comes to China empowering the youth of South Africa. The study, therefore, recommends that the government of South Africa should work together with China to empower its youth and be consistent in doing so to contribute to their development as individuals. [ABSTRACT FROM AUTHOR]

This article proposes a method to uncover opportunities for exploitation and exploration from consumer IoT interaction data. We develop a unique decomposition of cosine similarity that quantifies exploitation through functional similarity of interactions, exploration through cross-capacity similarity of counterfactual interactions, and differentiation of the two opportunities through within-similarity. We propose a topological data analysis method that incorporates these components of similarity and provides for their visualization. Functionally similar automations reveal exploitation opportunities for substitutes-in-use or complements-in-use, while exploration opportunities extend functionality into new use cases. This data-driven approach provides marketers with a powerful capability to discover possibilities for refining existing automation features while exploring new innovations. More generally, our approach can aid marketing efforts to balance these strategic opportunities in high technology contexts. [ABSTRACT FROM AUTHOR]

Fusarium head blight (FHB) is a major threat to global wheat production. Recent reviews of wheat FHB focused on pathology or comprehensive prevention and lacked a summary of advanced detection techniques. Unlike traditional detection and management methods, wheat FHB detection based on various imaging technologies has the obvious advantages of a high degree of automation and efficiency. With the rapid development of computer vision and deep learning technology, the number of related research has grown explosively in recent years. This review begins with an overview of wheat FHB epidemic mechanisms and changes in the characteristics of infected wheat. On this basis, the imaging scales are divided into microscopic, medium, submacroscopic, and macroscopic scales. Then, we outline the recent relevant articles, algorithms, and methodologies about wheat FHB from disease detection to qualitative analysis and summarize the potential difficulties in the practicalization of the corresponding technology. This paper could provide researchers with more targeted technical support and breakthrough directions. Additionally, this paper provides an overview of the ideal application mode of the FHB detection technologies based on multi-scale imaging and then examines the development trend of the all-scale detection system, which paved the way for the fusion of non-destructive detection technologies of wheat FHB based on multi-scale imaging. [ABSTRACT FROM AUTHOR]

A science writer who has been covering advanced technology for over 40 years gives a different, rarely seen view of tech startups: how they work, the common problems they seem to encounter – and why there are so many "Valley of Death" pitfalls waiting for them. [ABSTRACT FROM AUTHOR]

High-tech vegetable production is becoming a priority in agricultural development in Vietnam in the context of digital economic development. This study aims at identifying factors involving the adoption of high technology in vegetable production by local farmers in Hanoi. We used the theory of planned behavior and other farmers’ personal, social and economic factors to develop empirical model and hypotheses. Primary data was collected from a survey of 450 vegetable producers in Hanoi using cluster sampling method combined with random selection. Then, binary logit model was used to analyze the impact of influencing factors. Results showed that there were 7 factors having significant influences the decision to apply technology in vegetable production of farmers including attitude on high tech production, access to information, size of farm, member of extension organization, education level, access to credit and perceived behavior control, in which attitude variable was the most influential factor. Main management implications raised included enhancing access to technological information, providing demostration visits, giving more extension services, improving social inclusion and implementing hi- tech training for farmers in vegetable production. [ABSTRACT FROM AUTHOR]

This document is a summary of a collection of research papers that focus on innovation in the wine and spirit industries. The papers cover a range of topics including the evaluation of different wine varieties, the production of high-value red fruit spirits, and the use of specific yeasts in wine fermentation. The research highlights strategies for improving production processes, alternative fermentation technologies, and the use of different raw materials to create new products. The papers also emphasize the importance of sustainability in the wine and spirit industries. [Extracted from the article]

Over the past few years, China's economy has been on a rapid upswing, and corporate R&D and innovation performance, the first driver of high-quality development, has been considered the key to achieving a breakthrough in China's economic development. At the same time, the ability of companies to assume social responsibility while operating has been the focus of public attention. This study examines the impact of taking social responsibility on the ability of enterprises to invest in innovation. This study uses A-share high-tech enterprises in China from 2017–2019 as the research sample and uses ordinary least squares (OLS) to conduct the analysis. The results illustrate that shouldering social responsibility is a facilitator of innovation investment, and external financing can enhance the facilitation effect of CSR on innovation investment. [ABSTRACT FROM AUTHOR]

Big data is growing fast following Big data has the characteristics of high volume, speed, and variety (3v) and continues to grow exponentially following the development of the world's use of information and communication technology. The main problem with big data is the data deluge. The need for technology and large data storage and processing methods to keep pace with the exponential data growth rate is potentially limitless, giving rise to the problem of exponentially increasing technology requirements as well. The weakness of previous big data analysis approaches (batch and online real time processing) is that it requires high technology (large storage, memory and processing). This paper proposes a new approach in big-data analysis by separating the basic knowledge (BK) construction process from original data with a much smaller volume (volume reduction), then analyzing it into final knowledge, thus requiring smaller/simpler analysis technology. The proposals include formulating the definition and representation of BK, developing methods for constructing BK from source data, and analyzing BK into final knowledge. We propose a BK construction method based on a knowledge extraction technique using BIRCH clustering algorithm for instance reduction, and handling high-dimensional problems by parallelizing the dimension calculation process to calculate the distance between instances. We use the Adjusted Rand Index (ARI) to measure the similarity of the final knowledge of the baseline and proposed methods. First, the BIRCH baseline was modified by parallelizing the calculations has succeeded in increasing speed from 17% to 25%. Next, the parallel BIRCH (PBIRCH) baseline was broken into BK construction and BK analysis, has succeeded in reducing volume by 96% or more and increasing speed by 43.50%, with similar final knowledge results (ARI=1). Based on these results, we conclude that the BK construction method and analysis from BK into final knowledge for highdimensional big data have significantly reduced volume and speed up the analytical process without reducing the quality of the final knowledge. [ABSTRACT FROM AUTHOR]

The adoption and development of high technology situations such as additive manufacturing is complicated because the technology system characteristics used by manufacturers are different than the technology-performance characteristics evaluated by customers. This study explores the relationship between the desktop 3D printers' underlying technology characteristics, its performance, and its price. Data were collected for 107 Fused Deposition Modelling desktop 3D printers from 2014 to 2019. Twelve technology characteristics were included such as the build volume, the material of the build platform and whether it is heated, the number of extruders, type of movements and whether it uses open source software, hardware or filament. It was found that 8% of the technology characteristics only matter for performance, 33% only matter for price, 33% for neither and 25% of the characteristics matter for both performance and price. [ABSTRACT FROM AUTHOR]

Introduction: The aim of this study was to clarify the perspective of radiography science as an academic discipline. A discipline can be studied by discovering the collective use of concepts, especially core concepts. We have previously identified the core concepts as clinical practices in radiography, radiographers' profession, safe and high‐quality radiation use, and technology in radiography. The relationships between these concepts have not been studied previously. In order to clarify the perspective of radiography science we have investigated further the core concepts, their interrelationships and interdependencies. Methods: Altogether, 53 dissertations meeting the inclusion criteria were selected for a qualitative document analysis. The data were first analysed deductively using an extraction matrix comprising four core concepts developed from previous studies, then relational statements were synthesised, and the statements were analysed semantically. Results: Analysis revealed the bilateral interrelationships between the concepts and their dependencies. All the concepts were used within healthcare. The rationale for radiography science research was the clinical practice of radiography and the improvement of services in a complex environment as a part of patients' pathways. Safe and high‐quality radiation use was investigated as a means to deliver optimal services. Technology was studied as being functional or a means to deliver services. The perspective of the discipline was seen as the combination of humanistic interaction with advanced technology, where safety and quality were a necessity. Conclusions: Defining core concepts and their interrelations clarifies the perspective of the discipline and gives radiography researchers a way to argue their viewpoint. [ABSTRACT FROM AUTHOR]

Posthumanism stands as a complex and interdisciplinary intellectual movement that challenges and broadens conventional notions of human identity and existence, particularly in light of advancements in science and technology. It emerged in response to the swift evolution of technology and its profound impact on our understanding of what it means to be human. Embarking on a posthumanist inquiry, this research delves into the rich fabric of Charles Stross' Singularity Sky (2003), meticulously unraveling the complexities of human transcendence amidst advanced technology. The article's objective is to unveil the nuanced layers of the author's exploration of posthumanist ideas. The analysis explores the dynamic interplay among characters and their technological surroundings, emphasizing moments where the amalgamation of humanity and cutting-edge technology acts as a catalyst for transcendence. [ABSTRACT FROM AUTHOR]

Motivation: The complexity of the phenomenon of competitiveness among contemporary enterprises implies the legitimacy of searching for sources of competitive advantages beyond traditional success factors. The concepts of enterprise competitiveness have evolved from classical economics to the present day and theories with a practical purpose such as: the theory of five forces by M.E. Porter and the theory of key competences by G. Hamel and C.K. Prahalad. Nowadays research on the phenomenon of the competitiveness of enterprises seeks answers to the following questions: what is the role of intangible resources in being competitive on the market and what types of intangible resources are the most important from the point of view of the research? Aim: The aim of the article is to examine the strength and direction of the impact of intangible resources on the competitiveness of listed companies. The article presents a theoretical model of the impact of intangible resources on the competitiveness of listed companies. The case study used for the empirical verification of the constructed model will be joint-stock companies from the Warsaw Stock Exchange selected according to the criteria defined in the article. Statistical data of the tested objects from 2021 will be implemented in the model in order to analyze its stability. Results: To achieve the aim of the article, the PLS-SEM method of modeling structural equations was used, which allows for the study of relationships between directly unobservable variables. The model consists of two parts: a structural (internal) model and a measurement (external) model. These models are also used in the parameter estimation process — they are interrelated. Two unobservable (hidden) variables were adopted in the constructed model: intangible resources (IR) and competitiveness of companies (CC). Hidden variables were defined based on a potential set of indicators (observable variables). The specification of the PLS-SEM model will make it possible to determine the strength and direction of the impact of intangible resources on the competitiveness of listed companies, based on the theory of key competences. Identification of the most important variables among intangible resources shaping the competitiveness of enterprises will contribute to the determination of theoretical conclusions and practical recommendations for listed companies in Poland. [ABSTRACT FROM AUTHOR]

This paper aims to 'identify', 'analyse', and 'categorise' the barriers affecting the green transformation process in healthcare using Total Interpretive Structural Modelling (TISM) and MICMAC analysis. The TISM technique was utilized to determine how the components interacted and the green transformation process barriers criteria were ranked and categorized using the MICMAC method. This study identified 11 barriers to green transformation process in healthcare organizations. The key factors identified in this study are inadequate strategic planning, financial barriers, and high technology adoption cost, information barriers, international issues in healthcare environmental sustainability, lack of supportive atmosphere. The TISM technique for healthcare is proposed in this paper as a novel attempt to address the subject of green transformation process barriers. This research will aid key stakeholders and academics in the better understanding the barriers affecting the green transformation process in healthcare organizations. [ABSTRACT FROM AUTHOR]

In this work, an analog front-end (AFE) circuit for an electrocardiogram (ECG) detection system has been designed, implemented, and investigated in an industry-standard Cadence simulation framework using an advanced technology node of 45 nm. The AFE consists of an instrumentation amplifier, a Butterworth band-pass filter (with fifth-order low-pass and second-order high-pass sections), and a second-order notch filter—all are based on two-stage, Miller-compensated operational transconductance amplifiers (OTA). The OTAs have been designed employing the g m / I D methodology. Both the pre-layout and post-layout simulation are carried out. The layout consumes an area of 0.00628 mm2 without the resistors and capacitors. Analysis of various simulation results are carried out for the proposed AFE. The circuit demonstrates a post-layout bandwidth of 239 Hz, with a variable gain between 44 and 58 dB, a notch depth of −56.4 dB at 50.1 Hz, a total harmonic distortion (THD) of −59.65 dB (less than 1%), an input-referred noise spectral density of <34 μ Vrms/ Hz at the pass-band, a dynamic range of 52.71 dB, and a total power consumption of 10.88 μW with a supply of ±0.6 V. Hence, the AFE exhibits the promise of high-quality signal acquisition capability required for portable ECG detection systems in modern healthcare. [ABSTRACT FROM AUTHOR]

Ocular inserts offer distinct advantages, including a preservative-free drug delivery system, the ability to provide tailored drug release, and ease of administration. The present research paper delves into the development of an innovative ocular insert using CaliCut technology. Complementing the hot melt extrusion (HME) process, CaliCut, an advanced technology in ocular insert development, employs precision laser gauging to achieve impeccable cutting of inserts with desired dimensions. Its intelligent control over the stretching process through auto feedback-based belt speed adjustment ensures unparalleled accuracy and consistency in dosage form manufacturing. Dry eye disease (DED) poses a significant challenge to ocular health, necessitating innovative approaches to alleviate its symptoms. In this pursuit, castor oil has emerged as a promising therapeutic agent, offering beneficial effects by increasing the thickness of the lipid layer in the tear film, thus improving tear film stability, and reducing tear evaporation. To harness these advantages, this study focuses on the development and comprehensive characterization of castor oil-based ocular inserts. Additionally, in-vivo irritancy evaluation in rabbits has been undertaken to assess the inserts' safety and biocompatibility. By harnessing the HME and CaliCut techniques in the formulation process, the study demonstrates their instrumental role in facilitating the successful development of ocular inserts. Development of ocular inserts using HME and CaliCut and their characterization. [Display omitted] [ABSTRACT FROM AUTHOR]

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Copyright of Pixel-Bit, Revista de Medios y Educacion is the property of Pixel-Bit, Revista de Medios y Educacion and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Canadian Journal of Economics is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

I demonstrate that China is building an Augmented National innovation system or ANIS, with semiconductor industry and AI at the core. There are two dimensions along which China's NIS has been augmented. One is to move toward a more egalitarian innovation system in accordance with the goal of creating a harmonious, moderately prosperous economy and society. And the other is to include the AI and semiconductor base for high technology for the 4th Industrial Revolution. The Chinese ANIS has important regional and geoeconomic implications for the future. [ABSTRACT FROM AUTHOR]

Aluminum is an important metal material in people's modern life, and bauxite is the main raw material for the production of aluminum. With the continuous development of domestic aluminum industry, the demand for bauxite resources is increasing year by year. However, the quality of domestic bauxite resources is poor, the supply is insufficient, and the degree of external dependence of bauxite is high, which brings a serious threat to the supply security of aluminum resources in China and restricts the sustainable development of China's aluminum industry. In order to cope with the scarcity of high-quality bauxite resources in China, the development of complex and difficult-to-process bauxite resources, such as high sulfur and high iron bauxite, is crucial to ensuring the strategic security of China's bauxite resources. China has a large amount of complex bauxite resources, such as high-sulfur and high-iron bauxite, which is more than 1.5 billion tons, accompanied by other strategic metal resources, which is urgently needed to be efficiently developed and advanced technology is used to realize the industrial application of this kind of typical poor and miscellaneous bauxite. Excessive sulfur and iron impurities in bauxite will have non-negligible effects on the process of aluminum extraction by Bayer process, such as corroding equipment and pipes, increasing alkali consumption and red mud, affecting the quality of alumina and so on. Therefore, starting with the present situation and characteristics of high-sulfur and high-iron bauxite resources in China, the current research progress of desulphurization and iron removal process of high-sulfur and high-iron bauxite has been summarized. The main desulfurization technologies such as flotation desulfurization, perorating desulfurization, biological desulfurization and physical iron removal, chemical iron removal and biological iron removal are summarized. The industrial application level of various processes is discussed and several typical examples of industrial application of high-sulfur and high-iron bauxite are given. It will provide theoretical support for the development and utilization of complex bauxite resources in China, make effective use of difficult-to-process aluminum resources, reduce China's dependence on foreign aluminum resources, and improve the supporting force of bauxite resources. [ABSTRACT FROM AUTHOR]

This interview was given in 2008 by Arkady Zakrevsky (1928–2014), Corresponding Member of the National Academy of Sciences of Belarus (1972), Doctor of Technical Sciences (1967), and Professor (1969). He stood at the origins of the birth of cybernetics in the Soviet Union. He proposed the programming language for logical tasks LYaPAS, on the basis of which a series of computer-aided design systems for discrete devices was created, and methods for implementing parallel algorithms for the logical control of interacting processes. Some monographs: LYaPAS: A Programming Language for Logic and Coding Algorithms (N.-Y., L.: Academic Press, 1969; with M. A. Gavrilov); Boolesche Gleichungen: Theorie, Anwendung, Algorithmen (Berlin: VEB Verlag Technik, 1984; with Dieter Bochmann and Christian Posthoff); Combinatorial Algorithms of Discrete Mathematics (Tallinn: TUT Press, 2008; with Yu. Pottosin, L. Cheremisinova); Optimization in Boolean Space (Tallinn: TUT Press, 2009; with Yu. Pottosin, L. Cheremisinova); Design of Logical Control Devices (Tallinn: TUT Press, 2009; with Yu. Pottosin, L. Cheremisinova); Combinatorial Calculations in Many-Dimensional Boolean Space (Tallinn: TUT Press, 2012); Solving Large Systems Logical Equations (Tallinn: TUT Press, 2013). [ABSTRACT FROM AUTHOR]

The article discusses the issue of water scarcity and the need for energy-efficient desalination systems to provide potable water to populations facing water shortages. It explores various physical and chemical methods of desalination, including distillation, membrane processes, and chemical treatments. The article also highlights a special issue focused on small-scale technologies for desalination and water purification, which includes articles on topics such as slow sand filtration, solar distillation, evaporation-assisted humidification-dehumidification cycles, electric field force for ion removal, and a self-regenerating solar evaporation system. These technologies offer potential solutions for individual or small group usage, as well as emergency scenarios. [Extracted from the article]

Prioritization of sub-watersheds is critical in strategic planning for incorporating management practices in delicate semi-arid regions. Geomorphometric as well as land use/cover data sets are essential for determining subwatershed priorities for integrated watershed management. Prioritizing watersheds entails ranking of sub-watersheds according to their susceptibility based on several variables, including the average yearly soil loss, the depletion of water resources, and ecological deterioration. The sub-watershed prioritization for the study area Muzaffarpur district was done by combining Principal Component Analysis (PCA) and Weighted Sum Approach (WSA). PCA was used to differentiate important parameters but WSA was used to measure compound values for priority ranking and determining weights for significant parameters. The PCA was effective in obtaining the most crucial values (i.e., WB, Dt, Re, and Rb). A load of each significant parameter was successfully defined by the WSA application. Traditional prioritizing procedures uses numerous criteria in a complex manner and presumptively contribute equally but PCA-WSA integration results in more dynamic, effective, and efficient solutions. [ABSTRACT FROM AUTHOR]

In 2020, the Azerbaijani army launched a massive attack on Armenian positions in Nagorno-Karabakh. After 44 days of fighting, Azerbaijan scored a major victory, forcing Armenian forces to retreat from the territories around Karabakh, followed by the deployment of Russian peacekeeping troops. While many analysts have focused on advanced technology to explain Azerbaijan's victory, this article argues that a comparative study of the First Karabakh War (1991–1994) and the Second Karabakh War (2020) points to differences at the strategic level, including political transitions, diplomatic policies, and military forecasts, to propose a comprehensive and strategic discussion of the two wars, away from technological determinism. [ABSTRACT FROM AUTHOR]

Copyright of Ciencia y Sociedad is the property of Ciencia y Sociedad and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The evolution of advanced technology across various industries has provided opportunities for improvement in how professionals carry out their jobs. Artificial Intelligence (AI) is a rapidly evolving technology that brings great convenience to life, but at the same time, some risks need to be assessed. This technical paper will discuss AI processes that are taking place in the current scenario at accounting firms and their impact on them. We discussed AI's benefits to the Accounting and Auditing profession and its employees. This paper discussed AI's risks and challenges to Accounting firms and their employees. [ABSTRACT FROM AUTHOR]

This article focuses on the study of issues related to the functionality and structure of an economy. To achieve this, the theory of the cycle of money is used. The structural features of an economy are reflected in its operational characteristics, and vice versa. The index of the cycle of money indexes how well an economic system can counteract a financial crisis and characterizes how well structured a country's economy is. Calculations of the index of the cycle of money in Switzerland were compared with the global average index. The results showed that Switzerland is close to the global average; therefore, it has an excellent economy and is equipped to face any economic crisis. The applied methodology abides by theoretical, mathematical, statistical, and econometrical outcomes. This work is significant as it demonstrates the strength of Switzerland's economy in response to a potential crisis. Prior case studies were reviewed from Latvia, Bulgaria, Serbia, Thailand, Greece, Montenegro, and many other countries. This study postulates that companies with high capital should invest in manufacturing and high technology sectors that should be subject to fewer taxes; this approach facilitates a better distribution of money to the economy by allowing small companies to service the remaining economic activities. The period used for compilations in this study was the global recession of 2007–2017. The reviewed case study results are from a project studying multiple countries, and at present, this article presents the only study about Switzerland's index of the cycle of money. [ABSTRACT FROM AUTHOR]