Reality Technology Research Articles

Teaching Strategies Against Artificial Intelligence in the Learning of 21st Century Students

Objective: Analyze pedagogical strategies regarding artificial intelligence.
 
 Methods: A documentary exploration was used with the use of the PRISMA model, 33 documents were studied.
 
 Results: The results indicated that the variable, teaching strategies, must have characteristics such as innovation, flexibility, criticism, prospective and guiding level, which allows facing the interference of artificial intelligence that has levels of understanding and versatility with applications. and uses.
 
 Conclusions: Students can use Artificial Intelligence appropriately to develop their knowledge, considering that its trend will increase, and teachers must adapt to the new technological reality.

Scalable expansion of human pluripotent stem cells under suspension culture condition with human platelet lysate supplementation.

The large-scale production of human pluripotent stem cells (hPSCs), including both embryonic stem cells (hESCs) and induced pluripotent stem cells (hiPSCs), shows potential for advancing the translational realization of hPSC technology. Among multiple cell culture methods, suspension culture, also known as three-dimensional (3D) culture, stands out as a promising method to fulfill the large-scale production requirements. Under this 3D culture condition, cell expansion and the preservation of pluripotency and identity during long-term culture heavily relies on the culture medium. However, the xenogeneic supplements in culture medium remains an obstacle for the translation of cell and gene therapy applications from bench to bedside. Here, we tested human platelet lysate (hPL), a xeno-free and serum-free biological material, as a supplement in the 3D culture of hPSCs. We observed reduced intercellular variability and enhanced proliferation in both hESC and hiPSC lines. These cells, after extended culture in the hPL-supplemented system, maintained pluripotency marker expression, the capacity to differentiate into cells of all three germ layers, and normal karyotype, confirming the practicability and safety of hPL supplementation. Furthermore, through RNA-sequencing analysis, we found an upregulation of genes associated with cell cycle regulations in hPL-treated cells, consistent with the improved cellular division efficiency. Taken together, our findings underscore the potential of hPL as a xeno-free and serum-free supplement for the large-scale production of hPSCs, which holds promise for advancing clinical applications of these cells.

Bio-inspired polydopamine layer as a versatile functionalisation protocol for silicon-based photonic biosensors

Photonic biosensors have made major advances in recent years, achieving very high sensitivity, and progressing towards point-of-care deployment. By using photonic resonances, sensors can be label-free, which is particularly attractive for a low-cost technological realisation. A key remaining issue is the biological interface and the efficient and reliable immobilisation of binder molecules such as antibodies; many protocols are currently in use that have led to widely varying sensor performance. Here, we study a very simple and robust surface functionalisation protocol for silicon photonics, which is based on polydopamine, and we demonstrate both its simplicity and its high performance. The use of polydopamine (PDA) is inspired by molluscs, especially mussels, that employ dopamine to adhere to virtually any surface, especially in an aqueous environment. We studied the versatility of the PDA protocol by showing compatibility with 5 different disease biomarkers (Immunoglobulin (IgG), C-reactive protein (CRP), Tumour Necrosis factor-α (TNF-α), Interleukin-6 (IL-6), Matrix metalloproteinase (MMP-9) and show that the protocol is resistant to hydrolysis during incubation; the loss of functionality due to hydrolysis is a major issue for many of the functionalisation protocols commonly used for silicon-based sensors. The study using guided mode resonance-based sensors highlights the wide dynamic range of the protocol (0.01 ng/mL to 1 μg/mL), using IgG, CRP and MMP-9 protein biomarkers as exemplars. In addition, we show that the surface chemistry allows performing measurements in 10% human serum with a sensitivity as low as 10 ng/mL for IgG. We suggest that adopting this protocol will make it easier for researchers to achieve biofunctionalisation and that the biosensor community will be able to achieve more consistent results.

Highly-excited Rydberg excitons in synthetic thin-film cuprous oxide

Cuprous oxide (hbox {Cu}{}_2hbox {O}) has recently emerged as a promising material in solid-state quantum technology, specifically for its excitonic Rydberg states characterized by large principal quantum numbers (n). The significant wavefunction size of these highly-excited states (proportional to n^2) enables strong long-range dipole-dipole (proportional to n^4) and van der Waals interactions (proportional to n^{11}). Currently, the highest-lying Rydberg states are found in naturally occurring hbox {Cu}_2hbox {O}. However, for technological applications, the ability to grow high-quality synthetic samples is essential. The fabrication of thin-film hbox {Cu}{}_2hbox {O} samples is of particular interest as they hold potential for observing extreme single-photon nonlinearities through the Rydberg blockade. Nevertheless, due to the susceptibility of high-lying states to charged impurities, growing synthetic samples of sufficient quality poses a substantial challenge. This study successfully demonstrates the CMOS-compatible synthesis of a hbox {Cu}{}_2hbox {O} thin film on a transparent substrate that showcases Rydberg excitons up to n = 8 which is readily suitable for photonic device fabrications. These findings mark a significant advancement towards the realization of scalable and on-chip integrable Rydberg quantum technologies.

OptiDJS+: A Next-Generation Enhanced Dynamic Johnson Sequencing Algorithm for Efficient Resource Scheduling in Distributed Overloading within Cloud Computing Environment

The continuously evolving world of cloud computing presents new challenges in resource allocation as dispersed systems struggle with overloaded conditions. In this regard, we introduce OptiDJS+, a cutting-edge enhanced dynamic Johnson sequencing algorithm made to successfully handle resource scheduling challenges in cloud computing settings. With a solid foundation in the dynamic Johnson sequencing algorithm, OptiDJS+ builds upon it to suit the demands of modern cloud infrastructures. OptiDJS+ makes use of sophisticated optimization algorithms, heuristic approaches, and adaptive mechanisms to improve resource allocation, workload distribution, and task scheduling. To obtain the best performance, this strategy uses historical data, dynamic resource reconfiguration, and adaptation to changing workloads. It accomplishes this by utilizing real-time monitoring and machine learning. It takes factors like load balance and make-up into account. We outline the design philosophies, implementation specifics, and empirical assessments of OptiDJS+ in this work. Through rigorous testing and benchmarking against cutting-edge scheduling algorithms, we show the better performance and resilience of OptiDJS+ in terms of reaction times, resource utilization, and scalability. The outcomes underline its success in reducing resource contention and raising service quality generally in cloud computing environments. In contexts where there is distributed overloading, OptiDJS+ offers a significant advancement in the search for effective resource scheduling solutions. Its versatility, optimization skills, and improved decision-making procedures make it a viable tool for tackling the resource allocation issues that cloud service providers and consumers encounter daily. We think that OptiDJS+ opens the way for more dependable and effective cloud computing ecosystems, assisting in the full realization of cloud technologies’ promises across a range of application areas. In order to use the OptiDJS+ Johnson sequencing algorithm for cloud computing task scheduling, we provide a two-step procedure. After examining the links between the jobs, we generate a Gantt chart. The Gantt chart graph is then changed into a two-machine OptiDJS+ Johnson sequencing problem by assigning tasks to servers. The OptiDJS+ dynamic Johnson sequencing approach is then used to minimize the time span and find the best sequence of operations on each server. Through extensive simulations and testing, we evaluate the performance of our proposed OptiDJS+ dynamic Johnson sequencing approach with two servers to that of current scheduling techniques. The results demonstrate that our technique greatly improves performance in terms of makespan reduction and resource utilization. The recommended approach also demonstrates its ability to scale and is effective at resolving challenging work scheduling problems in cloud computing environments.

Dynamic Optimization of Construction Time-Cost for Deep and Large Foundation Pit Based on BIM Technology and Genetic Algorithm

With the increasingly fierce market competition, optimizing the construction time-cost of deep and large foundation pit construction projects has become one of the key factors for construction enterprises to remain invincible. By dynamically optimizing the time-cost, the optimal time corresponding to the lowest engineering cost can be found. Based on a comprehensive transportation hub project, considering the time value of capital and the reward and punishment of construction time, a time-cost dynamic optimization model is constructed. Relying on BIM technology, the feasibility of construction plan is analyzed from both qualitative and quantitative perspectives, and the project parameters and resource information is obtained accurately and quickly. Using the MATLAB program, time-cost optimization based on genetic algorithm is carried out, and the static and dynamic optimization results are compared. The results show that the dynamic optimization scheme reduces the total cost by 1.68% while reducing the total construction time by 8.47%. The dynamic optimization scheme extends the construction period by 2 days while reducing the total cost by 89,500 yuan compared to static optimization. The peak value of the fund demand curve before and after optimization has decreased from 128,000 yuan to 127,000 yuan. The time-cost dynamic optimization, considering the time value of capital is more in line with engineering reality, and the optimization results are more reliable and accurate. BIM technology can accurately and quickly obtain project parameters and resource information, solving problems such as complex processes in super deep excavation and huge engineering data statistics. The genetic algorithm can efficiently and accurately search for the optimal solution within the global domain. This study combines BIM technology with the genetic algorithm to solve the dynamic optimization problem of construction period cost for deep and large foundation pits. The research results of this study provide a theoretical reference for the optimization of schedule cost for similar projects.

Retracted: Realization of Single-Phase Grounding Fault Location and Recovery Technology in Distribution Network

Retracted: Realization of Single-Phase Grounding Fault Location and Recovery Technology in Distribution Network

Implications of generative artificial intelligence for the development of the media industry

As an important branch of artificial intelligence research, Generative Artificial Intelligence (GAI) mainly refers to artificial intelligence technology in which algorithms produce results under the given input data conditions. Generative artificial intelligence is one of the most active research directions in the field of artificial intelligence. Generative artificial intelligence has brought new technology innovation and content production mode. This paper discusses the new opportunities and challenges that generative artificial intelligence brings to the media industry from the aspects of technology realization, application status and application prospect. On this basis, it is proposed that the media industry should actively embrace and use generative artificial intelligence to promote its own intelligent transformation and achieve intelligent matching between information production mode and user needs.

Implications of generative artificial intelligence for the development of the media industry

As an important branch of artificial intelligence research, Generative Artificial Intelligence (GAI) mainly refers to artificial intelligence technology in which algorithms produce results under the given input data conditions. Generative artificial intelligence is one of the most active research directions in the field of artificial intelligence. Generative artificial intelligence has brought new technology innovation and content production mode. This paper discusses the new opportunities and challenges that generative artificial intelligence brings to the media industry from the aspects of technology realization, application status and application prospect. On this basis, it is proposed that the media industry should actively embrace and use generative artificial intelligence to promote its own intelligent transformation and achieve intelligent matching between information production mode and user needs.

Phase Unwrapping Method of Φ-OTDR System Based on Recursive-Branch-Cut Algorithm

Phase unwrapping is a crucial technique in phase-sensitive optical time domain reflectometry (Φ-OTDR) systems. Due to the effects of system under-sampling, I/Q imbalance and environmental noise, the traditional method of unwrapping the phase is prone to wrapping or even distortion. In this work, a two-dimensional phase unwrapping method based on the recursive-branch-cut (RBC) algorithm is proposed and studied to improve the accuracy of the demodulated phase waveform. The data near the vibration location is expanded into a two-dimensional wrapped phase map along the time direction. According to the abnormal phase distribution law, the two-dimensional wrapped phase map is divided into sliding windows of different lengths. Under the constraint of ensuring the global continuity of the phase, the local phase is optimized by selecting an appropriate integration path, and the error is minimized, thereby suppressing the propagation of abnormal noise in the global. The experimental results show that in the range of 1-80 Hz, the method can stably increase the upper limit of the system dynamic range by 3.21 dB. At the same time, the system has a good linear strain response capability, and the strain sensitivity is 22.46rad/με×m and R <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> =0.9997. In addition, the method greatly improves the demodulation characteristics without increasing the generality and practicability of the system, which is beneficial to the fully digital realization of the heterodyne detection technology.

A systematic review of Augmented Reality in Science, Technology, Engineering and Mathematics education

A systematic review of Augmented Reality in Science, Technology, Engineering and Mathematics education

A panel data method towards the effectiveness of sources of finance in stimulating the realisation of renewable energy technologies: Empirical evidence for Asia‐Pacific

AbstractMany nations have taken steps to encourage renewables through environmental policy frameworks; however, they still account for a small portion of global power output. This fact suggests that there are still some gaps between the potential advantages of renewables and their implementation, and these gaps must be investigated. Thus, the present study examines the effect of finance for the expansion of renewable energy technologies (RETs) by empirically assessing the sources of finance in facilitating the expansion of RETs on four renewable energy sectors; hydroelectric, biomass, solar photovoltaic and wind. This study applies a fixed effects estimator with Driscoll–Kraay standard errors on private and public sources of finance (financial market, banking sector and public debt) in selected Asia‐Pacific countries between 1998 and 2016. This study has shown that not all sources of finance have the same effect on the clean‐energy sector. The financial market plays a critical role in supplying financial capital for risky and uncertain technologies that require a high degree of financing, which could be particularly helpful for technology deployment in high‐tech industries. Investigations into the effectiveness of source of finance for RETs also indicate that banks discourage their deployment of RETs in the Asia‐Pacific.

Tilted Magnetic Anisotropy with In‐Plane Broken Symmetry in Ru‐Substituted Manganite Films

AbstractControlling the magnetic anisotropy of materials is important in a variety of applications including magnetic memories, spintronic sensors, and skyrmion‐based devices. Ru‐substituted La0.7Sr0.3MnO3 (Ru‐LSMO) is an emerging material, showing tilted magnetic anisotropy (TMA) and possible nontrivial magnetic topologies. Here anisotropic in‐plane magnetization is reported in moderately compressed Ru‐LSMO films, coexisting with TMA. This combination is attractive for technological applications, such as spin‐orbit torque (SOT) based devices and other spintronic applications. A microstructural analysis of films of this material is presented, and Ru single ion anisotropy and strain‐induced structural mechanisms are found to be responsible for both the in‐plane anisotropy and the TMA. The manifestation of these properties in a correlated oxide with Curie temperature near room temperature highlights an attractive platform for technological realization of SOT and other spintronic devices. Illustrating the mechanisms behind these properties provides the necessary engineering space for harnessing these phenomena for practical devices.

Mn–Co Prussian blue analogue cubic frames for efficient aqueous Zn ion batteries

Mn based Prussian blue analogs (PBAs) have emerged as highly promising cathode materials for aqueous zinc-ion batteries (AZIBs), owing to their high specific capacity and operating potential. However, the cycling stabilities of these materials remain unsatisfactory because their structural deformation induces ion intercalation. In this study, a PVP assisted Mn–Co-PBA was synthesized using a simple hydrothermal method. Mn–Co-PBA displays unique cubic frame-like structures with a high specific surface area and fewer zeolitic water molecules in the host lattice. The Mn–Co-PBA||Zn cell displayed an excellent specific capacity of 138 mAh g−1 at 0.1 A g−1, good rate capability (95 mAh g−1 at 1 A g−1), and good cycling stability (capacity retention of 92.8% after 1000 cycles) because of its unique cubic frame structure. This structure can provide a greater number of Zn diffusion pathways and alleviate the structural strain during Zn2+ ion insertion/extraction processes. An ex-situ XRD analysis revealed that the de/intercalation of Zn2+ ions in the Mn–Co-PBA electrodes was highly reversible. These results show that Mn–Co-PBA holds great promise for advancement in the field of AZIBs and contributes to the realization of effective and sustainable battery technologies.

Artistic tapestry from the Republic of Moldova in the period 2021-2023

The artistic tapestry from the first years of the third decade of the 21st century, highlights a series of particularities and valuable aesthetic valences that confirm the ascending character of the creation in the mentioned field. The natural processes of supplementing the creative potential with representatives of the new generations of plastic artists had a beneficial influence on the diversification of the thematic repertoire, the syntactic register and the methods of technological realization of textile works. As a result of some creative morphological-syntactic and technological experiments undertaken by plastic artists, the works of textile art of the examined period were endowed with aesthetic expressions and messages that mirror the areas of artistic interest and themes towards which the creators directed their attention at the time. The aesthetic values promoted by the smooth weaving technology, widely practiced by plastic artists in the previous decades, were accompanied in a new way by values coming from the symbiosis of the mentioned technology with the technique of felting, embroidery and crocheting, as a result of which, the mixed techniques of creating the image found a prominent plastic promotion in the period in question. In turn, the semantic allure generated by the textile works in the given period was ensured, on the one hand, by the stylistic-compositional, textural and chromatic way of creating the image and, on the other hand, by the associative values and the metaphorical-symbolic substrate of the work .

Технологии суггестивной лингвистики в интернет-коммуникациях

Introduction. Modern Internet communication has its own characteristics, one of which is often used suggestion, or suggestion, which is a process of influencing the human psyche, associated with a decrease in criticality in the perception and implementation of the suggestible content. In this case, the information assimilated by suggestion is difficult to comprehend and correct, which determines the relevance of the study, especially in the modern period of information wars.&#x0D; The aim of the article is to investigate the technologies of suggestive linguistics in Internet communications.&#x0D; Methodology. The study used the methods of conversion analysis; intent analysis, the method of group observation.&#x0D; Results. The research determines the technologies of suggestive linguistics and linguistic methods of suggestion which are important for exercising influence on the Internet; the tendencies of use of suggestive means in Internet communications were analyzed; the recommendations for counteraction to suggestive influences on the Internet were given. The separate attention is given to the realization of aggressive suggestive technologies on the example of “Windows Overton”. It is shown that various genres of Internet communication can be used for the suggestive influence.&#x0D; Scientific novelty of the research consists in structuring the most influential techniques of suggestion.&#x0D; Practical significance of research consists in development of recommendations on prevention of suggestive influences in the Internet, representing an algorithm of information-psychological control of the received information.

Quadratic estimation for stochastic systems in the presence of random parameter matrices, time-correlated additive noise and deception attacks

Networked systems usually face different random uncertainties that make the performance of the least-squares (LS) linear filter decline significantly. For this reason, great attention has been paid to the search for other kinds of suboptimal estimators. Among them, the LS quadratic estimation approach has attracted considerable interest in the scientific community for its balance between computational complexity and estimation accuracy. When it comes to stochastic systems subject to different random uncertainties and deception attacks, the quadratic estimator design has not been deeply studied. In this paper, using covariance information, the LS quadratic filtering and fixed-point smoothing problems are addressed under the assumption that the measurements are perturbed by a time-correlated additive noise, as well as affected by random parameter matrices and exposed to random deception attacks. The use of random parameter matrices covers a wide range of common uncertainties and random failures, thus better reflecting the engineering reality. The signal and observation vectors are augmented by stacking the original vectors with their second-order Kronecker powers; then, the linear estimator of the original signal based on the augmented observations provides the required quadratic estimator. A simulation example illustrates the superiority of the proposed quadratic estimators over the conventional linear ones and the effect of the deception attacks on the estimation performance.

Risks and Prospects of Creativity Tokenization

Objective: tokenization of creativity, alongside with cryptoeconomy and Web3 network infrastructure, is a notable trend in the development of modern society in the third decade of the 21st century. The objective of this article is to explore the risks and prospects emerging in the process of disposition of the creative labor results in the form of non-fungible tokens.Methods: the research methodology is based on analysis of varied viewpoints on the problem, including diametrically opposing concepts. The opposing views of the observers manifest their attitude to tokenization of creative products as a speculative scheme, on the one hand, and a promising tool of creative industries development, on the other.Results: the probable negative consequences of tokenization of intellectual activity results are identified; author’s recommendations on managing these risks are given. Another result of this publication is analysis of economiclegal prospects stemming from tokenization of the objects of copyright and neighboring rights by the example of musical pieces.Scientific novelty: it consists in presenting and substantiating a hypothesis that the relations formed in the musical industry under the modern sociocultural and technological realities will be reproduced in other creative industries. Also, scientific novelty consists in the analysis of prospects of tokenization of such results of intellectual activity as gaming artifacts, works of traditional and digital visual arts, patents and scientific achievements. The use of nonfungible tokens the ecosystem of network computer games will allow gamers to buy and sell rights to game pieces autonomously from game publishers. Tokenization of industrial property objects and individualization means will ensure protection of intellectual rights of their authors while waiting for the issuance of a state protection document. In the modern society, there will be many of those wishing to become an owner of a token for a scientific work, as the popularity of science and innovations is constantly growing in developed countries. Ownership of a token for a scientific work will be regarded a moral investment, increasing the prestige and status of its owner. Tokens for scientific works have a high potential as a means of measuring value in a post-economic society.Practical significance: it consists in the description of innovative means of using creative products and business models based on tokenization of the results of intellectual activity, ready to be implemented in practice.

Integrating emerging technologies for improving office technology and management curriculum in the 21st century

Technology keeps evolving as a result of upsurge of new knowledge and technological advancement in the workplace and classroom. For teachers of Office Technology and Management (OTM) to remain relevant in the 21st century classroom, there is an urgent need for further training on modern pedagogical approach to be at par with the realities of the day. This paper is an opinion paper which sought to identify emerging technology for improving Office Technology Management curriculum in the 21st century. From the literature reviewed, the emerging technology for improving Office Technology and Management in the 21st century include; ubiquitous computing, Collaboration Technologies, extended reality technologies, artificial intelligence among others. From the literature reviewed, the researcher recommended that training institutions should be adequately funded by government to enable them procure the necessary machines and equipment to aid teaching and learning, training institutions should from time to time, organize workshops and symposia to enable OTM trainers get acquainted with technological realities of the 21st century and remain relevant in today’s classroom, International organizations such as UNESCO can partner with training institutions and aid in equipping their computer laboratories and workshops among others.

Integrated Waveform Design Based on UAV MIMO Joint Radar Communication

The problem of orthogonal waveform construction in multiple input/multiple output (MIMO) radar communication integration greatly limits the realization of integration technology. In the unmanned aerial vehicle (UAV) MIMO antenna scenario, an orthogonal integrated waveform suitable for a MIMO antenna is designed using a sub−LFM−BPSK waveform combined with a chaotic spread spectrum code. After spread spectrum processing, each MIMO antenna transmits different communication data for orthogonal spread spectrum processing, which is suitable for the omnidirectional detection of MIMO application scenarios; moreover, the closed-form expressions of the integrated orthogonal waveform under certain constraints are derived. Finally, the simulation proves that the integrated orthogonal waveform set in the UAV MIMO scenario has excellent radar detection and communication capabilities.