Efficient Information Transfer Research Articles

Design and Development of UART Protocol Using Verilog with UVM Testbench

This paper's primary goal is to use Verilog (V) to design and validate a full duplex UART module. The Universal Asynchronous Receiver/Transmitter, or UART, is a two-way transmission channel that not only significantly increases the efficiency of information transfer between computers and external devices but also guarantees information accuracy and consistency through the use of baud rate settings, the elimination of metastable state, and other techniques. In this work, the definition and operation of UART are well understood, and the UART is constructed using the Verilog HDL language, EDA simulation, picture, and data. The findings of the experiment demonstrate that this module's sending and receiving module functions well and satisfies the specifications of full-duplex serial communication equipment. Without a doubt, the layout of this paper has made the fundamental working concept of UART more clearly explained, which will aid in its future. Key Words:- UART, EDA , BRG, IC, DUT, UVM

Skin Cancer Segmentation using CNN

This groundbreaking research introduces a comprehensive strategy for advancing medical image segmentation, merging two pivotal concepts to significantly enhance both the accuracy and efficiency of the segmentation process. The first component of our approach involves the integration of polar transformations as a preprocessing step applied to the original dataset. This transformative technique is designed to address the challenges associated with segmenting single structures of elliptical shape in medical images, such as organs (e.g., heart and kidneys), skin lesions, polyps, and various abnormalities. By centering the polar transformation on the object's focal point, a reduction in dimensionality is achieved, coupled with a distinct separation of segmentation and localization tasks. Two distinct methodologies for selecting an optimal polar origin are proposed: one involving estimation through a segmentation neural network trained on non-polar images, and the other employing a dedicated neural network trained to pre dict the optimal origin. The second key element of our approach is around the integration of the DoubleU-Net architecture, a powerful encoder-decoder model specifically designed for the task of semantic image segmentation. DoubleU- Net is a group of two U-Net architectures, each with a specific purpose. The initial U-Net is pre-trained on VGG-19 as the encoder and uses features learned from ImageNet to provide efficient information transfer. In order to store more semantic information and content, a second U-Net was added to the base to enhance the capabilities of the network. Join Atrous Spatial Pyramid Pooling (ASPP) to develop network data extraction content. The combination of DoubleU-Net architecture and joint transformation as a step forward shows good segmentation performance in different clinical tasks, including liver segmentation, polyp detection vision, skin segmentation, and epicardial fat tissue segmentation. It shows that various medical projects, including various diagnostic methods such as colonoscopy, dermoscopy, microscopy, have a positive impact on the plan. More importantly, the method performs well in difficult cases, such as the segmentation of small and flat polyps in CVC-ClinicDB and the 2015 subset of the MICCAI Automated Polyp Detection dataset. The results demonstrate the accuracy and generality of the combination, making it the best way to evaluate medical images in context; Our study has revealed a new method of skin cancer diagnosis that combines the power of deep learning with innovation. Advanced technology. The combination of dual U-Net architecture and polar coordinate transformation not only improves the accuracy of classification of lesions but also improves the robustness of the model to changes in image features. This study contributes to the development of computer-aided diagnostic systems for early diagnosis. Experimental results show that our method provides good accuracy, sensitivity, and specificity in detecting malignant and benign tumors. Additionally, we are conducting ablation studies to determine the contribution of each presentation and treatment of skin cancer to ultimately benefit patients and determine these benefits. We also apply the transformation of the joint as the first step to improve the discrimination ability of the model. This mechanical change effectively reduces the impact caused by changes in wound size, shape, and direction by displaying the original image of the polar system. By standardizing the representation of skin diseases, polar transformation improves the model's ability to generalize across different data sets and improves overall performance.

Air Quality Prediction in Smart Environment using Lightweight Residual Network: Sustainable Light-AirNet Approach

In densely populated places, air pollution prediction is crucial since it directly affects human health and the local governance. The main objective of this work is to analyze the spatial and temporal patterns of the concentration of the main air pollutants in Bangalore, India. In this paper, a lightweight residual network with an attention mechanism is created using a collection of residual concatenation blocks layered with recursive residual blocks. This aids in the adaptive extraction of useful features, the learning of more expressive spatial context information, and the efficient transfer of information through gradient flow in the network. A unique attention mechanism, known as the Two-Fold Attention Module, has been created with the purpose of enhancing the model’s ability to represent information. The Light-AirNet model was designed to provide hourly forecasts by using past pollution data and three measured weather variables were collected from weather stations. Light-AirNet is compared with existing approaches in terms of different metrics and it was found that it achieves 24.5% of root-mean-square error, 21.5% of mean square error, 12.59% of mean absolute error, and 97.45% of prediction accuracy.

The topology of interpersonal neural network in weak social ties

The strategies for social interaction between strangers differ from those between acquaintances, whereas the differences in neural basis of social interaction have not been fully elucidated. In this study, we examined the geometrical properties of interpersonal neural networks in pairs of strangers and acquaintances during antiphase joint tapping. Dual electroencephalogram (EEG) of 29 channels per participant was measured from 14 strangers and 13 acquaintance pairs.Intra-brain synchronizations were calculated using the weighted phase lag index (wPLI) for intra-brain electrode combinations, and inter-brain synchronizations were calculated using the phase locking value (PLV) for inter-brain electrode combinations in the theta, alpha, and beta frequency bands. For each participant pair, electrode combinations with larger wPLI/PLV than their surrogates were defined as the edges of the neural networks. We calculated global efficiency, local efficiency, and modularity derived from graph theory for the combined intra- and inter-brain networks of each pair. In the theta band networks, stranger pairs showed larger local efficiency than acquaintance pairs, indicating that the two brains of stranger pairs were more densely connected. Hence, weak social ties require extensive social interactions and result in high efficiency of information transfer between neighbors in neural network.

Visualizing the trans-synaptic arrangement of synaptic proteins by expansion microscopy.

High fidelity synaptic neurotransmission in the millisecond range is provided by a defined structural arrangement of synaptic proteins. At the presynapse multi-epitope scaffolding proteins are organized spatially at release sites to guarantee optimal binding of neurotransmitters at receptor clusters. The organization of pre- and postsynaptic proteins in trans-synaptic nanocolumns would thus intuitively support efficient information transfer at the synapse. Visualization of these protein-dense regions as well as the minute size of protein-packed synaptic clefts remains, however, challenging. To enable efficient labeling of these protein complexes, we developed post-gelation immunolabeling expansion microscopy combined with Airyscan super-resolution microscopy. Using ~8-fold expanded samples, Airyscan enables multicolor fluorescence imaging with 20-40 nm spatial resolution. Post-immunolabeling of decrowded (expanded) samples provides increased labeling efficiency and allows the visualization of trans-synaptic nanocolumns. Our approach is ideally suited to investigate the pathological impact on nanocolumn arrangement e.g., in limbic encephalitis with autoantibodies targeting trans-synaptic leucine-rich glioma inactivated 1 protein (LGI1).

Topological light transport in low-symmetry valley photonic crystals

Valley photonic crystals represent a cornerstone in the field of topological photonics, which promotes the development of cutting-edge photonic waveguides. These waveguides support robust transmission by using valley-dependent edge states. This innovation marks a great leap forward in enhancing transmission efficiency, (especially in sharp bends), thus opening up a new way for efficient optical information transmission. However, although the role of symmetry in topology and photonic crystals cannot be exaggerated, it is worth noting that valley photonic crystals provide a unique platform for exploring the interplay between symmetry and topological phenomena. An intriguing analogy between valley photonic crystals and the quantum valley Hall effect is an example, which will be shown when the symmetry of spatial inversion is broken. At present, the characteristic of most valley photonic crystals is <i>C</i><sub>3</sub>-rotational symmetry, which leads to an interesting study, that is, whether crystals with lower symmetry can also support topological light transmission. In order to solve this problem head-on, our work focuses on constructing and characterizing valley photonic crystals with low symmetry by carefully adjusting the unit cell morphology. Through theoretical analysis and numerical simulation, we unveil the remarkable ability of these low-symmetry valley photonic crystals to facilitate topological light transport. Initially, we analyze the bulk bands of these low-symmetry crystals, observing a narrowed photonic band gap and a shift in the irreducible Brillouin zone compared with <i>C</i><sub>3</sub>-rotation symmetric crystals. To examine edge state transmission, we calculate dispersion relations and electric field distributions, revealing two edge states with opposite phase chirality at the same frequency. Using this point, we achieve unidirectional excitation of edge states. Additionally, we manipulate the refractive index of the surrounding medium and explore various scenarios of external light beam coupling. Moreover, we investigate the robust transmission of edge states, demonstrating smooth passage of light through sharp corners in <i>Z</i>-shaped bend waveguides without backscattering. In conclusion, our findings underscore the pivotal role played by edge states in facilitating unidirectional excitation and robust transmission in low-symmetry valley photonic crystals. By enriching the diversity of topological photonic structures and providing valuable insights into the behavior of topological light transport in structures with lower symmetry, our work contributes to the ongoing quest for novel photonic platforms with enhanced functions and performance.

Aging effects on dual-route speech processing networks during speech perception in noise.

Healthy aging leads to complex changes in the functional network of speech processing in a noisy environment. The dual-route neural architecture has been applied to the study of speech processing. Although evidence suggests that senescent increases activity in the brain regions across the dorsal and ventral stream regions to offset reduced periphery, the regulatory mechanism of dual-route functional networks underlying such compensation remains largely unknown. Here, by utilizing functional near-infrared spectroscopy (fNIRS), we investigated the compensatory mechanism of the dual-route functional connectivity, and its relationship with healthy aging by using a speech perception task at varying signal-to-noise ratios (SNR) in healthy individuals (young adults, middle-aged adults, and older adults). Results showed that the speech perception scores showed a significant age-related decrease with the reduction of the SNR. The analysis results of dual-route speech processing networks showed that the functional connection of Wernicke's area and homolog Wernicke's area were age-related increases. Further to clarify the age-related characteristics of the dual-route speech processing networks, graph-theoretical network analysis revealed an age-related increase in the efficiency of the networks, and the age-related differences in nodal characteristics were found both in Wernicke's area and homolog Wernicke's area under noise environment. Thus, Wernicke's area might be a key network hub to maintain efficient information transfer across the speech process network with healthy aging. Moreover, older adults would recruit more resources from the homologous Wernicke's area in a noisy environment. The recruitment of the homolog of Wernicke's area might provide a means of compensation for older adults for decoding speech in an adverse listening environment. Together, our results characterized dual-route speech processing networks at varying noise environments and provided new insight for the compensatory theories of how aging modulates the dual-route speech processing functional networks.

Aktywność polityczna i kulturalna kobiet w świetle rękopiśmiennej i drukowanej prasy polskiego oświecenia (XVIII w.)

Political and Cultural Activism of Women As Seen in Handwritten and Printed Press in the Polish Enlightenment (Eighteenth Century) The rapid development of the press in the Republic of Poland in the eighteenth century enabled a much more efficient transfer of information. During the Enlightenment, the Polish press market was graced by a number of magazines the editors of which were guided by the goals of reforming, moralizing, and promoting scientific knowledge. At the same time, the old Polish social communication system based on the creation and sending of handwritten newspapers to recipients was still in operation. In various press outlets in the Republic of Poland in the second half of the eighteenth century, one can also find an ever‑growing amount of information devoted to women. In addition to pedagogical issues that were discussed in the Enlightenment, i.e., the upbringing and education of girls, information about women’s activities, which were diverse in their nature, spread more and more widely. Both in printed and handwritten newspapers, one can, above all, read about the achievements of women in the fields of politics and culture. Although Polish women in the eighteenth century had limited opportunities to act in politics and culture, resulting from the specificity of the Polish state system and from the dominance of men, their important role in these areas was often highlighted in the press. Press advertisements also allow us to conclude that literary works written by women could take root in social consciousness thanks to newspaper advertising.

Maritime Communications—Current State and the Future Potential with SDN and SDR

The rise of the Internet of Things (IoT) has opened up exciting possibilities for new applications. One such novel application is the modernization of maritime communications. Effective maritime communication is vital for ensuring the safety of crew members, vessels, and cargo. The maritime industry is responsible for the transportation of a significant portion of global trade, and as such, the efficient and secure transfer of information is essential to maintain the flow of goods and services. With the increasing complexity of maritime operations, technological advancements such as unmanned aerial vehicles (UAVs), autonomous underwater vehicles (AUVs), and the Internet of Ships (IoS) have been introduced to enhance communication and operational efficiency. However, these technologies also bring new challenges in terms of security and network management. Compromised IT systems, with escalated privileges, can potentially enable easy and ready access to operational technology (OT) systems and networks with the same privileges, with an increased risk of zero-day attacks. In this paper, we first provide a review of the current state and modalities of maritime communications. We then review the current adoption of software-defined radios (SDRs) and software-defined networks (SDNs) in the maritime industry and evaluate their impact as maritime IoT enablers. Finally, as a key contribution of this paper, we propose a unified SDN–SDR-driven cross-layer communications framework that leverages the existing SATCOM communications infrastructure, for improved and resilient maritime communications in highly dynamic and resource-constrained environments.

Systematic Review of Behavioural Determinants Impacting Managerial Accounting Decision-Making: A Meta-Analysis Approach

Purpose. Analyse and evaluate the behavioural determinants of the formation of a management circulation system at an enterprise. Methodology. The creation of a management accounting model is determined by: user orientation and efficiency of information transfer. Approach. Decision-making models can be created in different ways. The article also defines the set of tasks as a set of alternative sets. Findings. The initial decision must first be correctly formulated based on the conditions and constraints of the external system that affect the problem to be solved. Practical Implications. The results of the article can be used by managers of different levels at an enterprise to assess and predict the determinants of the external and internal environment when making management decisions. Originality. This article is aimed at a systematic analysis of behavioural determinants in the system of management accounting at an enterprise. It covers not only the influence of the determinants of the internal environment but also aims to systematically take into account the full cycle of the management decision-making process. Value. The decision-making process is considered as a system consisting of certain typical steps and their interaction. Their number may vary depending on conditions and types of tasks.

Digitisation of Rail Transport: The Application that Delivers Faster and More Efficient Services

Abstract The article analyses the use of modern technologies in rail freight transport with a specific focus on the process of transferring information from transport documents through automatic identification technology. The main transport document in this context is the consignment note, where automatic identification is required. The automatic identification technologies investigated are RFID/NFC and QR code, with the analysis suggesting that QR code is more accessible and convenient in the current railway environment. However, in practice, limitations have emerged regarding the capacity of the stored information and the readability of the QR code data. It concludes that the use of modern technologies in rail freight transport brings new opportunities and increases the efficiency of information transfer associated with transport documents. Despite the advantages of QR code technology, limitations have been identified, in particular in terms of capacity and readability. The results also show that users with access to modern technologies, such as internet-enabled mobile phones or computers with internet access, are able to handle this technology efficiently, suggesting potential process improvements in rail freight transport. Overall, the paper highlights the importance of integrated technology solutions within this sectoral area and suggests that technological advances are opening up new opportunities for more efficient management and monitoring of rail transport processes.

Blockchain-Powered Education: A Sustainable Approach for Secured and Connected University Systems

The collection and examination of student data, encompassing academic achievements, awards, and certifications, assume an essential function within the field of education as a means of showing students’ capabilities. Nevertheless, it is crucial to note that regular paper-based records are vulnerable to both physical destruction and the act of fabrication, while standard databases can have security holes. Moreover, the process of manually gathering physical papers from centralized organizations is both laborious and complicated. To address the concerns above and foster sustainability in the field of education, this study first suggests using Scorechain. This innovative solution integrates blockchain technology into a comprehensive data-management system for managing all student-related data. Secondly, by utilizing the inherent security features of blockchain technology, Scorechain develops a stable multi-role hierarchy, increasing the integrity and reliability of data. This also facilitates the efficient transfer of information among various stakeholders, including parents, recruiters, and educational institutions, thus fostering transparency and accountability. Lastly, the Scorechain system facilitates collaboration and data exchange among universities inside a shared network. Scorechain was constructed using the Rust programming language and is based on the Substrate blockchain architecture. It underwent careful development, testing, and analysis to ensure operational efficiency. The feasibility and long-term viability of Scorechain in genuine educational contexts are highlighted as blockchain technology facilitates seamless integration into the education sector.

A Gastroenterologist’s Guide to Care Transitions in Cystic Fibrosis from Pediatrics to Adult Care

Cystic Fibrosis is a chronic disease affecting multiple systems, including the GI tract. Clinical manifestation in patients can start as early as infancy and vary across different age groups. With the advent of new, highly effective modulators, the life expectancy of PwCF has improved significantly. Various GI aspects of CF care, such as nutrition, are linked to an overall improvement in morbidity, lung function and the quality of life of PwCF. The variable clinical presentations and management of GI diseases in pediatrics and adults with CF should be recognized. Therefore, it is necessary to ensure efficient transfer of information between pediatric and adult providers for proper continuity of management and coordination of care at the time of transition. The transition of care is a challenging process for both patients and providers and currently there are no specific tools for GI providers to help ensure a smooth transition. In this review, we aim to highlight the crucial features of GI care at the time of transition and provide a checklist that can assist in ensuring an effective transition and ease the challenges associated with it.

Directed functional connectivity of the sensorimotor system in young and older individuals.

Studies in the sensorimotor system of older versus young individuals have shown alterations in functional connectivity and organization. Our objective was to explore the implications of these differences in terms of local organizations, and to identify processes that correlate with neuropsychological parameters. Using a novel multivariate analysis method on resting-state functional MRI data obtained from 50 young and 31 older healthy individuals, we identified directed 4-node functional pathways within the sensorimotor system and examined their correlations with neuropsychological assessments. In young individuals, the functional pathways were unidirectional, flowing from the primary motor and sensory cortices to higher motor and visual regions. In older individuals, the functional pathways were more complex. They originated either from the calcarine sulcus or the insula and passed through mutually coupled high-order motor areas before reaching the primary sensory and motor cortices. Additionally, the pathways in older individuals that resembled those found in young individuals exhibited a positive correlation with years of education. The flow pattern of young individuals suggests efficient and fast information transfer. In contrast, the mutual coupling of high-order motor regions in older individuals suggests an inefficient and slow transfer, a less segregated and a more integrated organization. The differences in the number of sensorimotor pathways and of their directionality suggests reduced efferent degenerated pathways and increased afferent compensated pathways. Furthermore, the positive effect of years of education may be associated with the Cognitive Reserve Hypothesis, implying that cognitive reserve could be maintained through specific information transfer pathways.

High-speed rail and stock return comovement in China

This study explores the impact of China’s high-speed rail network on reducing local bias and fostering capital market integration. Our research reveals that implementing high-speed rail in a city decreases the return comovement of its local stocks but increases its return comovement with the national stock market. Our results are robust and consistent across various model specifications. After examining the underlying economic mechanism, we find that the impact of high-speed rail on stock return comovement is stronger for small firms, non-state-owned enterprises (non-SOEs), firms with poor corporate governance, and firms’ headquarters in more segmented and less-developed regions. This effect did not change after controlling for other information-dissemination channels and regional economic development. Overall, geographical proximity contributes to information transfer and market efficiency.

Retail investor attention and stock market behavior in Russia-Ukraine conflict based on Chinese practices: Evidence from transfer entropy causal network

From the non-linear information transmission angle, we look into the interactions between retail investor attention and the stock market before and during the Russia-Ukraine conflict. We construct transfer entropy causal networks between retail investor attention and stock market behavior on three counts: return, trading volume and volatility. We discover that bi-directional causal relations exist between investor attention and the stock market. We also find that after the conflict outbreak, retail investor attention becomes more influential on return, trading volume and volatility. The stock market return and volatility have more impact on investor attention. Information transfer efficiency increases after the outbreak.

DNA nanopores as artificial membrane channels for bioprotonics

Biological membrane channels mediate information exchange between cells and facilitate molecular recognition. While tuning the shape and function of membrane channels for precision molecular sensing via de-novo routes is complex, an even more significant challenge is interfacing membrane channels with electronic devices for signal readout, which results in low efficiency of information transfer - one of the major barriers to the continued development of high-performance bioelectronic devices. To this end, we integrate membrane spanning DNA nanopores with bioprotonic contacts to create programmable, modular, and efficient artificial ion-channel interfaces. Here we show that cholesterol modified DNA nanopores spontaneously and with remarkable affinity span the lipid bilayer formed over the planar bio-protonic electrode surface and mediate proton transport across the bilayer. Using the ability to easily modify DNA nanostructures, we illustrate that this bioprotonic device can be programmed for electronic recognition of biomolecular signals such as presence of Streptavidin and the cardiac biomarker B-type natriuretic peptide, without modifying the biomolecules. We anticipate this robust interface will allow facile electronic measurement and quantification of biomolecules in a multiplexed manner.

Individual differences in T1w/T2w ratio development during childhood

Myelination is a key developmental process that promotes rapid and efficient information transfer. Myelin also stabilizes existing brain networks and thus may constrain neuroplasticity, defined here as the brain's potential to change in response to experiences rather than the canonical definition as the process of change. Characterizing individual differences in neuroplasticity may shed light on mechanisms by which early experiences shape learning, brain and body development, and response to interventions. The T1-weighted/T2-weighted (T1w/T2w) MRI signal ratio is a proxy measure of cortical microstructure and thus neuroplasticity. Here, in pre-registered analyses, we investigated individual differences in T1w/T2w ratios in children (ages 4–10, n = 157). T1w/T2w ratios were positively associated with age within early-developing sensorimotor and attention regions. We also tested whether socioeconomic status, cognition (crystallized knowledge or fluid reasoning), and biological age (as measured with molar eruption) were related to T1w/T2w signal but found no significant effects. Associations among T1w/T2w ratios, early experiences, and cognition may emerge later in adolescence and may not be strong enough to detect in moderate sample sizes.

Ranking nodes in complex networks based on TsRank

It is theoretically and practically meaningful to rank and identify nodes in complex networks in various fields, however, many existing methods consider single feature of graph. To utilize multiple attributes of graph, a novel ranking method based on Tsallis entropy is proposed in this paper, which considers information transfer efficiency as global information of nodes and takes extended mixed degree and core neighborhood centrality as local information of nodes. We utilize the monotonicity function index, cumulative distribution (CDF), Kendall’s tau coefficient, Jaccard similarity coefficient, and the total number of infected nodes based on susceptible–infected–recovered (SIR) model as evaluation metrics to measure the performance of the proposed method. The simulation results demonstrate that the proposed method has great superiority in terms of monotonicity, resolution, the accuracy of both the whole ranking results and top-c ranked nodes, and spreading ability of the top-10 nodes.

Altered dynamic functional network connectivity states in patients with acute basal ganglia ischemic stroke

BackgroundDynamic functional network connectivity (dFNC) patterns are successfully able to capture the time-varying features of intrinsic fluctuations throughout a scan. We explored dFNC alterations across the entire brain in patients with acute ischemic stroke (AIS) of the basal ganglia (BG). MethodResting-state functional magnetic resonance imaging data were acquired from 26 patients with first-ever AIS in the BG and 26 healthy controls (HCs). Independent component analysis, the sliding window method, and the K-means clustering method were used to obtain reoccurring dynamic network connectivity patterns. Moreover, temporal features across diverse dFNC states were compared between the two groups, and the local and global efficiencies across states were analyzed to explore the characteristics of the topological networks among states. ResultsFour dFNC states were characterized for comparison of dynamic brain network connectivity patterns. In contrast to the HC group, the AIS group spent a significantly higher fraction of time in State 1, which is characterized by a relatively weaker brain network connectome. Conversely, compared with HC, patients with AIS showed a lower mean dwell time in State 2, which was characterized by a relatively stronger brain network connectome. Additionally, functional networks exhibited variable efficiency of information transfer across 4 states. ConclusionsAIS not only altered the interaction between the different dynamic networks but also promoted characteristic alterations in the temporal and topological features of large-scale dynamic network connectivity.