In recent years, cutting-edge technologies, such as artificial intelligence (AI), blockchain, and digital twin (DT), have revolutionized the healthcare sector by enhancing public health and treatment quality through precise diagnosis, preventive measures, and real-time care capabilities. Despite these advancements, the massive amount of generated biomedical data puts substantial challenges associated with information security, privacy, and scalability. Applying blockchain in healthcare-based digital twins ensures data integrity, immutability, consistency, and security, making it a critical component in addressing these challenges. Federated learning (FL) has also emerged as a promising AI technique to enhance privacy and enable decentralized data processing. This paper investigates the integration of digital twin concepts with blockchain and FL in the healthcare domain, focusing on their architecture and applications. It also explores platforms and solutions that leverage these technologies for secure and scalable medical implementations. A case study on federated learning for electroencephalogram (EEG) signal classification is presented, demonstrating its potential as a diagnostic tool for brain activity analysis and neurological disorder detection. Finally, we highlight the key challenges, emerging opportunities, and future directions in advancing healthcare digital twins with blockchain and federated learning, paving the way for a more intelligent, secure, and privacy-preserving medical ecosystem.
Lucas Bickmann, Matias Rodriguez, Xiaoyi Jiang
et al.
Transposable elements (TEs) constitute a significant portion of eukaryotic genomes and play crucial roles in genome evolution, yet their diverse and complex sequences pose challenges for accurate classification. Existing tools often lack reliability in TE classification, limiting genomic analyses. Here, we present TEclass2, a software employing a deep learning approach based on a linear transformer architecture with k-mer tokenization and sequence-specific adaptations to classify TE consensus sequences into sixteen superfamilies. TEclass2 demonstrates improved classification performance and offers flexible model training on custom datasets. Accessible via a web interface with pre-trained models, TEclass2 facilitates rapid and reliable TE classification. These advancements provide a foundation for enhanced genomic annotation and support further bioinformatics research involving transposable elements.
Monitoring and diagnosis of cardiovascular diseases rely on cardiac motion estimation. The methods used for registering echocardiographic images have drawbacks such as low resolution, noise, and distortion of the anatomy. In order to enhance the prediction of cardiac motion, this research presents an AI-powered architecture that makes use of Vision Transformers, Diffusion Models, and Neural Radiance Fields (NeRF). Adversarial and self-supervised contrastive learning enhance picture quality and generalisability across adult and foetal echocardiography, while a graph neural network (GNN)-based anatomical constraint maintains heart shape. Better, more accurate, more efficient real-time motion tracking without relying on massive labelled datasets is possible with the proposed approach. Cardiac motion analysis in a wide range of patient populations is now therapeutically viable, thanks to this innovative approach that improves echocardiographic picture registration. • Utilizes Vision Transformers, Diffusion Models, and NeRF for high-quality cardiac motion prediction. • Adversarial and self-supervised contrastive learning improve echocardiographic registration across demographics. • A GNN-based anatomical constraint ensures accurate heart morphology during motion analysis.
Many studies have used various time-frequency feature extraction methods to convert ship-radiated noise into three-dimensional (3D) data suitable for computer vision (CV) models, which have shown good results in public datasets. However, traditional feature engineering (FE) has been enhanced to interface matching–feature engineering (IM-FE). This approach requires considerable effort in feature design, larger sample duration, or a higher upper limit of frequency. In this context, this paper proposes a one-dimensional network design for underwater acoustic target recognition (UATR-ND1D), only combined with fast Fourier transform (FFT), which can effectively alleviate the problem of IM-FE. This method is abbreviated as FFT-UATR-ND1D. FFT-UATR-ND1D was applied to the design of a one-dimensional network, named ResNet1D. Experiments were conducted on two mainstream datasets, using ResNet1D in 4320 and 360 tests, respectively. The lightweight model ResNet1D_S, with only 0.17 M parameters and 3.4 M floating point operations (FLOPs), achieved average accuracies were 97.2% and 95.20%. The larger model, ResNet1D_B, with 2.1 M parameters and 5.0 M FLOPs, both reached optimal accuracies, 98.81% and 98.42%, respectively. Compared to existing methods, those with similar parameter sizes performed 3–5% worse than the methods proposed in this paper. Additionally, methods achieving similar recognition rates require more parameters of 1 to 2 orders of magnitude and FLOPs.
This is an article in the field of ceramics and composites. In order to study the early rheological properties of alkali-activated fly ash-slag cementitious system, the composite pastes with different mass ratios of fly ash (FA) to slag (GGBS) and alkaline activator content were prepared. The fluidity and rheological properties of the pastes were tested by mini-cone slump cone, Brookfield DV3T rheometer,respectively. Finally, the hydration exothermic rate of composite pastes with each ratio was tested by isothermal calorimeter. Results show that when FA/GGBS ratio is 3∶7, the fluidity of paste with 4% NaOH content is the lowest. With the increase of FA mass ratio and NaOH molar mass, the fluidity of alkali-activated FA-GGBS cementitious system increased, and the yield stress and plastic viscosity decreased. The growth of FA content decreases the early hydration rate significantly, while the increase of alkali activator content remarkably increases the peak rate of hydration heat release.
Ali Aghazadeh Ardebili, Antonio Ficarella, Antonella Longo
et al.
Autonomous aircraft are the key enablers of future urban services, such as postal and transportation systems. Digital twins (DTs) are promising cutting-edge technologies that can transform the future transport ecosystem into an autonomous and resilient system. However, since DT is a data-driven solution based on AI, proper data management is essential in implementing DT as a service (DTaaS). One of the challenges in DT development is the availability of real-life data, particularly for training algorithms and verifying the functionality of DT. The current article focuses on data augmentation through synthetic data generation. This approach can facilitate the development of DT in case the developers do not have enough data to train the machine learning (ML) algorithm. The current twinning approach provides a prospective ideal state of the engine used for proactive monitoring of the engine’s health as an anomaly detection service. In line with the track of unmanned aircraft vehicles (UAVs) for urban air mobility in smart city applications, this paper focuses specifically on the common hybrid turbo-shaft in drones/helicopters. However, there is a significant gap in real-life similar synthetic data generation in the UAV domain literature. Therefore, rolling linear regression and Kalman filter algorithms were implemented on noise-added data, which simulate the data measured from the engine in a real-life operational life cycle. For both thermal and hybrid models, the corresponding DT model has shown high efficiency in noise filtration and a certain amount of predictions with a lower error rate on all engine parameters except the engine torque.
The paper discusses two eighteenth-century magnates’ residences, the architecture of which functioned as a political statement, drawing on cultural codes rooted in the ancient tradition and borrowing from the model of Versailles. The palaces of Jan Klemens Branicki (1689–1771) in Białystok and of Eustachy Potocki (1720–1768) in Radzyń were built in the mid-eighteenth century. The analysis of their forms, spatial design and sculptures sheds light on their function as a ceremonial space serving political purposes. Our study focuses on the examination of the entrance gates, façade decoration and the sculptures located in the vestibules, which play a key role in the symbolic structures of the residences, as well as the gardens with their pavilions and sculptures. Together these elements constituted the Gesamtkunstwerk (total work of art) of these magnates dreaming of being elected king.
Automatic modulation classification (AMC) used in cognitive radio networks is an important class of methods apt to utilize spectrum resources efficiently. However, conventional likelihood-based approaches have high computational complexity. Thus, this paper proposes a novel convolutional neural network architecture for AMC. A bottleneck and asymmetric convolution structure are employed in the proposed model, which can reduce the computational complexity. The skip connection technique is used to solve the vanishing gradient problem and improve the classification accuracy. The dataset DeepSig:RadioML, which is composed of 24 modulation classes, is used for the performance analysis. Simulation results show that the classification accuracy performance of the proposed model is outstanding in the signal-to-noise ratio (SNR) range from -4 dB to 20 dB compared with MCNet that is the best model in the conventional models, where the proposed model achieves 5.52% and 5.92% improvement regarding classification accuracy at the SNRs of 0 dB and 10 dB, respectively. In terms of the computational complexity, the proposed model not only saves the trainable parameters by more than 67% but also reduces the prediction time for a signal by more than 54.4% compared with those of MCNet.
Public safety communication systems are currently evolving due to emergence of long term evolution (LTE) as a mature solution to replace the legacy ones while providing new services. However, LTE is initially designed for commercial cellular network and needs to be furthermore evolved to tackle the substantial requirements of public safety use cases. For instance, opportunistic deployments require modifications to enable the autonomous operation and meshing of moving base stations while satisfying heterogeneous frequency band availability. In this article, we present a novel radio access network infrastructure architecture that enables multi-hop LTE mesh networking for nomadic and autonomous base stations via in-band self-backhauling. Furthermore, we investigate the coordination and orchestration functionality within the proposed architecture and propose a hierarchical resource scheduling algorithm in order to efficiently meet quality of service (QoS) requirements for real-time traffic while maximizing the throughput for elastic flows. To demonstrate the feasibility and reliability of our proposed architecture, we implement the corresponding self-backhauling air-interface based on OpenAirInterface platform and compare it with the legacy LTE air-interface. Finally, we evaluate the efficiency and adaptability of our proposed resource scheduling algorithm in various network topology and heterogeneous traffic flows with QoS requirements.
Currently in Russia the development of church architecture poses many problems associated with the revival of the national school of monumental religious painting. The article analyzes the main features of the development of monumental decoration of church buildings. It also emphasizes importance of an integrated approach to the solution of the architectural and artistic ensemble of the cult construction. The synthesis of national religious architecture and monumental church painting is the object of research and its features аt the present stage is the subject. The goal of the article is the identification of the main tendencies of integrated approach to the religious architecture, both for Russia and the Republic of Mordovia.
The empirical material of the work is the religious architecture and monumental church painting of Russia and the Republic of Mordovia. The research is based on observation, descriptive and comparative methods of analysis. The article is based on the published research on the church art of Russia and the Republic of Mordovia.
The turn of the 21st century represents the active practice of creating a modern church decor. This is characterized by a complex multistage process of collective creativity, characterized by specific architectural environment of the building, development of the design of the decor and the means of monumental painting.
The turn of the 21st century represents a new step in the development of religious architecture and monumental painting in Russia. It makes a conclusion that at the turn of the century the use of the artistic experience of the past is the leading tendency in the development of modern monumental church painting. The necessity of achieving the synthesis of the architectural building and its monumental and decorative solution is empasized.
Scholarly affinities are one of the most fundamental hidden dynamics that drive scientific development. Some affinities are actual, and consequently can be measured through classical academic metrics such as co-authoring. Other affinities are potential, and therefore do not leave visible traces in information systems; for instance, some peers may share interests without actually knowing it. This article illustrates the development of a map of affinities for academic collectives, designed to be relevant to three audiences: the management, the scholars themselves, and the external public. Our case study involves the School of Architecture, Civil and Environmental Engineering of EPFL, hereinafter ENAC. The school consists of around 1,000 scholars, 70 laboratories, and 3 institutes. The actual affinities are modeled using the data available from the information systems reporting publications, teaching, and advising scholars, whereas the potential affinities are addressed through text mining of the publications. The major challenge for designing such a map is to represent the multi-dimensionality and multi-scale nature of the information. The affinities are not limited to the computation of heterogeneous sources of information; they also apply at different scales. The map, thus, shows local affinities inside a given laboratory, as well as global affinities among laboratories. This article presents a graphical grammar to represent affinities. Its effectiveness is illustrated by two actualizations of the design proposal: an interactive online system in which the map can be parameterized, and a large-scale carpet of 250 square meters. In both cases, we discuss how the materiality influences the representation of data, in particular the way key questions could be appropriately addressed considering the three target audiences: the insights gained by the management and their consequences in terms of governance, the understanding of the scholars’ own positioning in the academic group in order to foster opportunities for new collaborations and, eventually, the interpretation of the structure from a general public to evaluate the relevance of the tool for external communication.
Bibliography. Library science. Information resources
Soledad Natalia Gonzalez, Wanda Mariela Valsecchi, Dante Maugeri
et al.
The enzyme of the pentose phosphate pathway (PPP) ribulose-5-phosphate-epimerase (RPE) is encoded by two genes present in the genome of Trypanosoma cruzi CL Brener clone: TcRPE1 and TcRPE2. Despite high sequence similarity at the amino acid residue level, the recombinant isoenzymes show a strikingly different kinetics. Whereas TcRPE2 follows a typical michaelian behavior, TcRPE1 shows a complex kinetic pattern, displaying a biphasic curve, suggesting the coexistence of -at least- two kinetically different molecular forms. Regarding the subcellular localization in epimastigotes, whereas TcRPE1 is a cytosolic enzyme, TcRPE2 is localized in glycosomes. To our knowledge, TcRPE2 is the first PPP isoenzyme that is exclusively localized in glycosomes. Over-expression of TcRPE1, but not of TcRPE2, significantly reduces the parasite doubling time in vitro, as compared with wild type epimastigotes. Both TcRPEs represent single domain proteins exhibiting the classical α/β TIM-barrel fold, as expected for enzymes with this activity. With regard to the architecture of the active site, all the important amino acid residues for catalysis -with the exception of M58- are also present in both TcRPEs models. The superimposition of the binding pocket of both isoenzyme models shows that they adopt essentially identical positions in the active site with a residue specific RMSD < 2Å, with the sole exception of S12, which displays a large deviation (residue specific RMSD: 11.07 Å). Studies on the quaternary arrangement of these isoenzymes reveal that both are present in a mixture of various oligomeric species made up of an even number of molecules, probably pointing to the dimer as their minimal functional unit. This multiplicity of oligomeric species has not been reported for any of the other RPEs studied so far and it might bear implications for the regulation of TcRPEs activity, although further investigation will be necessary to unravel the physiological significance of these structural findings.
La avenida Presidente Perón es una de las obras de infraestructura con gran impacto en el desarrollo metropolitano de Tucumán en los últimos 20 años. Es considerada una vía de acceso troncal hacia la ciudad de Yerba Buena que permitió la expansión noroeste del AMET, modificando un suelo agrícola por urbano residencial de alto nivel social.
Actualmente se han localizado actividades complementarias al uso residencial y otras compatibles como el campus del Colegio Santa Rosa, el centro comercial Open Plaza, la universidad privada del Norte Santo Tomás de Aquino, complejos de oficinas, entre otros.
El presente trabajo tiene como objetivo describir las transformaciones producidas en el sector de análisis evidenciando cómo el sector privado representado por grandes promotores inmobiliarios, se beneficia con la obra pública generando, como denomina Cuenya, un entorno urbano exclusivo, sin precedente en el AMET de Tucumán.
Dichos cambios se verifican y cuantifican a partir del análisis sincrónico. Para ello, se trabaja mediante tres cortes espacio temporales: antes de la construcción de la avenida (principios década de los ‘90), durante las primeras intervenciones en el sector (década del 2000) y la situación actual sobre imágenes satelitales tipo Landsat y Digital Globe, procesadas en una plataforma SIG
Architecture, Urban groups. The city. Urban sociology
The paper indicates the importance of spatial planning as a specific
instrument for the protection and management of World Heritage sites in
Serbia. The paper analyses the obligations set forth in the international and
national documents and legislation relevant for spatial planning, on the one
hand, and World Heritage protection, on the other hand. The notion, criteria,
method of zoning, systems and approaches to the management of sites inscribed
on the World Heritage List are shown through the concept of World Heritage.
The paper also emphasizes the importance of adopting management plans for all
World Heritage sites and their incorporation into the national legislation
and planning documents, primarily into the special purpose area spatial
plans. It also gives examples of special purpose spatial plans in order to
consider the treatment of World Heritage in these documents, and to make
proposals for improving the spatial planning and the existing protection and
management of the World Heritage sites in Serbia. [Projekat Ministarstva
nauke Republike Srbije, br. TR36016: Sustainable spatial development of
Danubian Serbia]
This article analyzes the value chain of high-tech products in Asia and the role of this phenomenon in the further consolidation of trade blocs and alliances in the region. The presence of these chains and their gradual transition from a vertically integrated model to a system of horizontal linkages and interdependence leads to the formation of mechanisms of economic de-facto integration (so-called regionalization process). The East Asian region has demonstrated unprecedented high rates of economic growth in recent decades. The countries are actively developing mechanisms of multilateral cooperation, involving partners from across the Asia-Pacific region. Particular features of a new regional architecture of economic relations are becoming more tangible, and the essential element of this architecture is the intra-regional integration. The author presents an assessment of further developments of the Regional comprehensive economic partnership (RCEP) using the structural-functional approach and analytical instruments of the international political economy, The creation of this trade block will help less advanced countries of ASEAN to accelerate economic growth and improve the conditions for integration into global value chains. For advanced economies, participation in the RCEP seems controversial, because production chains have well-established formats within the framework of ASEAN +. The political standoff between Washington and Beijing has an impact on dynamics of regional integration. The split among the East Asian countries was galvanized by the Trans-Pacific Partnership Project (TTP), because TPP has objectives that are very similar to those of RCEP (trade liberalization and economic integration). The author concludes that the extension of this partnership in the ASEAN countries can seriously complicate the operation RVEP and enhance the impact of political factors on economic cooperation. In this case, the value of production and supply chains of high-tech products will decline, which may affect the economic cooperation in the region as a whole.
In this work, an improved plating solution was prepared aiming at improving the utilization rate of effective components and reducing the content of hypophosphite in the plating solution to some extent. Considering the variation of complex reductant in the plating solution, the performance of the coating was evaluated by various electrochemical measurements, including potentiodynamic polarization curves and electrochemical impedance spectroscopy, and surface characterization. It was found that the coating resulted from proper addition of complex reductant was able to effectively serve as a barrier layer to block corrosive species from reaching the steel surface.
Industrial electrochemistry, Physical and theoretical chemistry
Presenting simultaneous but spatially discrepant visual and auditory stimuli induces a perceptual translocation of the sound towards the visual input, the ventriloquism effect. General explanation is that vision tends to dominate over audition because of its higher spatial reliability. The underlying neural mechanisms remain unclear. We address this question via a biologically inspired neural network. The model contains two layers of unimodal visual and auditory neurons, with visual neurons having higher spatial resolution than auditory ones. Neurons within each layer communicate via lateral intra-layer synapses; neurons across layers are connected via inter-layer connections. The network accounts for the ventriloquism effect, ascribing it to a positive feedback between the visual and auditory neurons, triggered by residual auditory activity at the position of the visual stimulus. Main results are: i) the less localized stimulus is strongly biased toward the most localized stimulus and not vice versa; ii) amount of the ventriloquism effect changes with visual-auditory spatial disparity; iii) ventriloquism is a robust behavior of the network with respect to parameter value changes. Moreover, the model implements Hebbian rules for potentiation and depression of lateral synapses, to explain ventriloquism aftereffect (that is, the enduring sound shift after exposure to spatially disparate audio-visual stimuli). By adaptively changing the weights of lateral synapses during cross-modal stimulation, the model produces post-adaptive shifts of auditory localization that agree with in-vivo observations. The model demonstrates that two unimodal layers reciprocally interconnected may explain ventriloquism effect and aftereffect, even without the presence of any convergent multimodal area. The proposed study may provide advancement in understanding neural architecture and mechanisms at the basis of visual-auditory integration in the spatial realm.