Information Transfer Research Articles

Concealed hazardous object detection for terahertz images with cross-feature fusion transformer

Terahertz (THz) waves can penetrate many non-metallic materials (such as paper, plastic, and clothing), making them highly valuable in security inspection areas. However, the low contrast between target objects and the background in THz images poses problems for object detection and recognition tasks. Though many schemes have been proposed to tackle the problems, the low detection accuracy and high computational complexity remain challenges. To address these challenges, we propose a concealed hazardous object detection method called Cross-Feature Fusion Transformer YOLO (CFT-YOLO) for THz images. We design a Multi-Channel Spatial Feature Module (MCSFM) to achieve cross-channel and cross-spatial information transfer between feature maps. MCSFM also realizes the feature parameter transfer between the backbone and neck of the network. Additionally, we develop a CrossFuse-Transformer (CF-Former) module that leverages self-attention to fully exploit the correlations and structural information between different feature maps. We conduct a series of experiments on public datasets. The results show that CFT-YOLO outperforms the other advanced methods in THz hazardous object detection tasks. Moreover, the CFT-YOLO achieves a better balance between model complexity and detection accuracy compared to YOLOv8s, making it more practical for real-world applications.

Analyzing the topological properties of resting-state brain function network connectivity based on graph theoretical methods in patients with high myopia

AimRecent imaging studies have found significant abnormalities in the brain’s functional or structural connectivity among patients with high myopia (HM), indicating a heightened risk of cognitive impairment and other behavioral changes. However, there is a lack of research on the topological characteristics and connectivity changes of the functional networks in HM patients. In this study, we employed graph theoretical analysis to investigate the topological structure and regional connectivity of the brain function network in HM patients.MethodsWe conducted rs-fMRI scans on 82 individuals with HM and 59 healthy controls (HC), ensuring that the two groups were matched for age and education level. Through graph theoretical analysis, we studied the topological structure of whole-brain functional networks among participants, exploring the topological properties and differences between the two groups.ResultsIn the range of 0.05 to 0.50 of sparsity, both groups demonstrated a small-world architecture of the brain network. Compared to the control group, HM patients showed significantly lower values of normalized clustering coefficient (γ) (P = 0.0101) and small-worldness (σ) (P = 0.0168). Additionally, the HM group showed lower nodal centrality in the right Amygdala (P < 0.001, Bonferroni-corrected). Notably, there is an increase in functional connectivity (FC) between the saliency network (SN) and Sensorimotor Network (SMN) in the HM group, while the strength of FC between the basal ganglia is relatively weaker (P < 0.01).ConclusionHM Patients exhibit reduced small-world characteristics in their brain networks, with significant drops in γ and σ values indicating weakened global interregional information transfer ability. Not only that, the topological properties of the amygdala nodes in HM patients significantly decline, indicating dysfunction within the brain network. In addition, there are abnormalities in the FC between the SN, SMN, and basal ganglia networks in HM patients, which is related to attention regulation, motor impairment, emotions, and cognitive performance. These findings may provide a new mechanism for central pathology in HM patients.

Causes of extreme events revealed by Rényi information transfer.

Information-theoretic generalization of Granger causality principle, based on evaluation of conditional mutual information, also known as transfer entropy (CMI/TE), is redefined in the framework of Rényi entropy (RCMI/RTE). Using numerically generated data with a defined causal structure and examples of real data from the climate system, it is demonstrated that RCMI/RTE is able to identify the cause variable responsible for the occurrence of extreme values in an effect variable. In the presented example, the Siberian High was identified as the cause responsible for the increased probability of cold extremes in the winter and spring surface air temperature in Europe, while the North Atlantic Oscillation and blocking events can induce shifts of the whole temperature probability distribution.

Evaluating energy harvesting UAV-NOMA network with random user pairing in the finite blocklength regime

This study proposes an integrated system that combines energy harvesting (EH) enabled unmanned aerial vehicles (UAVs) with non-orthogonal multiple access (NOMA) to enhance communication system performance within a cellular network. Addressing the limitations of existing analyses that often assume an infinite blocklength scenario, we explore EH-enabled UAV-NOMA systems within a cellular framework under a finite blocklength (FBL) scenario. The study investigates the complex interactions and advantages resulting from the integration of EH, NOMA, and UAV technologies, aiming to assess whether EH can sustain communication within this framework. The network model considers base stations (BSs), UAVs, and terrestrial devices distributed with independent Poisson point processes (PPPs) over a large area. In this network, BSs employ NOMA to serve cell center devices directly, while cell edge devices, which are nor in direct contact with BS, are served via simultaneous wireless information and power transfer (SWIPT) enabled UAVs. The study derives metrics including joint harvesting and decoding probability for a randomly selected UAV, coverage probability (CP) for cell devices, and end-to-end block error rate (BLER) probabilities for typical device pairs. The findings demonstrate that the proposed scheme effectively supplies all the necessary transmit power for communication purposes through EH, achieving reasonable reliability. Additionally, the study highlights the importance of considering a combination of blocklengths from different phases to achieve optimal performance, rather than solely relying on an increment in blocklength. Finally, the effects of parameter variations on network performance are examined.

An ankyrin G–binding motif mediates TRAAK periodic localization at axon initial segments of hippocampal pyramidal neurons

The axon initial segment (AIS) is a critical compartment in neurons. It converts postsynaptic input into action potentials that subsequently trigger information transfer to target neurons. This process relies on the presence of several voltage-gated sodium (NaV) and potassium (KV) channels that accumulate in high densities at the AIS. TRAAK is a mechanosensitive leak potassium channel that was recently localized to the nodes of Ranvier. Here, we uncover that TRAAK is also present in AISs of hippocampal and cortical neurons in the adult rat brain as well as in AISs of cultured rat hippocampal neurons. We show that the AIS localization is driven by a C-terminal ankyrin G-binding sequence that organizes TRAAK in a 190 nm spaced periodic pattern that codistributes with periodically organized ankyrin G. We furthermore uncover that while the identified ankyrin G-binding motif is analogous to known ankyrin G-binding motifs in NaV1 and KV7.2/KV7.3 channels, it was acquired by convergent evolution. Our findings identify TRAAK as an AIS ion channel that convergently acquired an ankyrin G-binding motif and expand the role of ankyrin G to include the nanoscale organization of ion channels at the AIS.

Understanding Knowledge Mobilisation between Community Champions and Parents: Evidence from a Community-Based Programme to Support Parents with Young Children.

Community champions have been employed across various settings to disseminate evidence-based public health information. The Building Babies' Brains programme trains champions to work with parents in communities, equipping them with child development knowledge and parental engagement strategies. We explored what makes community champions effective in distributing information to parents, including how the champion-parent relationship and champions' personal characteristics affect information dissemination. Champions included both peers and professionals working with parents in target communities. We administered an online survey (n = 53) and follow-up interviews (n = 14) with champions, with representation from across all training cohorts. We conducted a realist-informed reflexive thematic analysis to generate themes in the data and highlight the contexts, mechanisms, and outcome patterns identified. We observed 15 Context-Mechanism-Outcome configurations across five themes: information sharing opportunities, information relevance, the nature of the champion-parent relationship, interaction expectations, and champion confidence. Our programme theory for how the community champion approach works identified that peer champions focused more on building rapport, modelling behaviours, and being a trusted community resource than direct information transfer. Professional champions, in contrast, showed greater expertise and confidence in discussing parenting practices directly. For both groups, traits such as friendliness and the ability to establish a trusting relationship enhanced effectiveness. This research identifies the impacts of champion role, characteristics, and the champion-parent relationship on the effectiveness of knowledge mobilisation in this context, with implications for training and recruitment of champions. Those using a champion model in comparable settings should ensure that champions have the necessary knowledge, skills, and confidence to engage parents and share information effectively.

Emerging insights into the pathogenesis and therapeutic strategies for vascular endothelial injury-associated diseases: focus on mitochondrial dysfunction.

As a vital component of blood vessels, endothelial cells play a key role in maintaining overall physiological function by residing between circulating blood and semi-solid tissue. Various stress stimuli can induce endothelial injury, leading to the onset of corresponding diseases in the body. In recent years, the importance of mitochondria in vascular endothelial injury has become increasingly apparent. Mitochondria, as the primary site of cellular aerobic respiration and the organelle for "energy information transfer," can detect endothelial cell damage by integrating and receiving various external stress signals. The generation of reactive oxygen species (ROS) and mitochondrial dysfunction often determine the evolution of endothelial cell injury towards necrosis or apoptosis. Therefore, mitochondria are closely associated with endothelial cell function, helping to determine the progression of clinical diseases. This article comprehensively reviews the interconnection and pathogenesis of mitochondrial-induced vascular endothelial cell injury in cardiovascular diseases, renal diseases, pulmonary-related diseases, cerebrovascular diseases, and microvascular diseases associated with diabetes. Corresponding therapeutic approaches are also provided. Additionally, strategies for using clinical drugs to treat vascular endothelial injury-based diseases are discussed, aiming to offer new insights and treatment options for the clinical diagnosis of related vascular injuries.

Insights from the Active Use of Neuroscience Findings in Teaching and Learning.

The aim of this paper is to show how teachers apply teaching and learning strategies related to the principles of the nervous system's functions. In our view, understanding what constitutes good teaching is about identifying how it engages the underlying cognitive and neurosystemic processes within the human brain in relation to learning. Using a student self-assessment questionnaire, we have investigated several key processes involved in neurodidactics (excitation, perception, memory, and the use, transfer, and adaptation of information and/or actions). The sample consisted of 884 7-10th grade students. The results showed that students' excitation, understanding, and consolidation of educational material are directly related to the work of the teacher and the teaching strategies they apply to attract and stimulate the student's attention and to help the student to understand and remember information. The learning strategies used by the students reflect the learner's learning activity, i.e., the use and application of strategies that allow internal knowledge to emerge. The consolidation of the learning material and the learning strategies used by the students was statistically significantly higher among the female participants. There are significant differences between low- and high-achieving students in terms of the effectiveness of teaching strategies for consolidation and the learning strategies applied by learners. The paper provides practical recommendations for teachers.

Power-Efficient Resource Allocation for Active STAR-RIS-Aided SWIPT Communication Systems

Simultaneous wireless information and power transfer (SWIPT) has emerged as a pivotal technology in 6G, offering an efficient means of delivering energy to a large quantity of low-power devices while transmitting data concurrently. To address the challenges of obstructions, high path loss, and significant energy consumption associated with long-distance communication, this work introduces a novel alternating iterative optimization strategy. The proposed approach combines active simultaneous transmission and reflection of reconfigurable intelligent surfaces (STAR-RIS) with SWIPT to maximize spectrum efficiency and reduce overall system energy consumption. This method addresses the considerable energy demands inherent in SWIPT systems by focusing on reducing the power output from the base station (BS) while meeting key constraints: the communication rate for information receivers (IRs) and minimum energy levels for energy receivers (ERs). Given complex interactions between variables, the solution involves an alternating iterative optimization process. In the first stage of this approach, the passive beamforming variables are kept constant, enabling the use of semi-definite relaxation (SDR) and successive convex approximation (SCA) algorithms to optimize active beamforming variables. In the next stage, with active beamforming variables fixed, penalty-based algorithms are applied to fine-tune the passive beamforming variables. This iterative process continues, alternating between active and passive beamforming optimization, until the system converges on a stable solution. The simulation results indicated that the proposed system configuration, which leverages active STAR-RIS, achieves lower energy consumption and demonstrates improved performance compared to configurations utilizing passive RIS, active RIS, and passive STAR-RIS. This evidence suggests that the proposed approach can significantly contribute to advancing energy efficiency in 6G systems.

Music reward sensitivity is associated with greater information transfer capacity within dorsal and motor white matter networks in musicians.

There are pronounced differences in the degree to which individuals experience music-induced pleasure which are linked to variations in structural connectivity between auditory and reward areas. However, previous studies exploring the link between white matter structure and music reward sensitivity (MRS) have relied on standard diffusion tensor imaging methods, which present challenges in terms of anatomical accuracy and interpretability. Further, the link between MRS and connectivity in regions outside of auditory-reward networks, as well as the role of musical training, have yet to be investigated. Therefore, we investigated the relation between MRS and structural connectivity in a large number of directly segmented and anatomically verified white matter tracts in musicians (n = 24) and non-musicians (n = 23) using state-of-the-art tract reconstruction and fixel-based analysis. Using a manual tract-of-interest approach, we additionally tested MRS-white matter associations in auditory-reward networks seen in previous studies. Within the musician group, there was a significant positive relation between MRS and fiber density and cross section in the right middle longitudinal fascicle connecting auditory and inferior parietal cortices. There were also positive relations between MRS and fiber-bundle cross-section in tracts connecting the left thalamus to the ventral precentral gyrus and connecting the right thalamus to the right supplementary motor area, however, these did not survive FDR correction. These results suggest that, within musicians, dorsal auditory and motor networks are crucial to MRS, possibly via their roles in top-down predictive processing and auditory-motor transformations.

CLIP2TF:Multimodal video–text retrieval for adolescent education

With the rapid advancement of artificial intelligence technology, particularly within the sphere of adolescent education, a continual emergence of new challenges and opportunities is observed. The current educational system increasingly requires the automation of teaching activities detection and evaluation, offering fresh perspectives for enhancing the quality of adolescent education. Although large-scale models are receiving significant attention in educational research, their high demand for computational resources and limitations in specific applications constrain their widespread use in analyzing educational video content, especially when handling multimodal data. Current multimodal contrastive learning methods, which integrate video, audio, and text information, have achieved certain successes in video–text retrieval tasks. However, these methods typically employ simpler weighted fusion strategies and fail to avoid noise and information redundancy. Therefore, our study proposes a novel network framework, CLIP2TF, which includes an efficient audio–visual fusion encoder. It aims to dynamically interact and integrate visual and audio features, further enhancing the visual features that may be missing or insufficient in specific teaching scenarios while effectively reducing redundant information transfer during the modality fusion process. Through ablation experiments on the MSRVTT and MSVD datasets, we first demonstrate the effectiveness of CLIP2TF in video–text retrieval tasks. Subsequent tests on teaching video datasets further proves the applicability of the proposed method. This research not only showcases the potential of artificial intelligence in the automated assessment of teaching quality but also provides new directions for research in related fields studies.

EHR Solutions for Information Transfer Deficits During Transitions in Care for Sepsis Survivors.

In a previous study, sepsis was noted as a diagnosis on the home health record only 4% of the time for 165,000 sepsis survivors transitioning from hospital to home health care in America. If sepsis and other conditions are not clearly documented in the transitional care record this can lead to unpreparedness, missed, care, and poor patient outcomes. Our implementation science study discovered a source of this problem regarding the sepsis documentation in 16 hospitals referring to five home care agencies. Together, researchers, hospital, and home care personnel developed and implemented two information technology solutions to address this deficit in seven hospitals. The automated method was more readily adopted and effective in improving information transfer between hospital and home health care.

Enhancers and super-enhancers as master regulators in cancer

Gene expression regulation is one of the most fundamental cellular processes, enabling the activation of a gene to produce either the translatable protein-coding transcript (mRNA) or a functional non-coding RNA with gene regulatory functions, ultimately determining cell identity and function. Although gene expression regulation can occur at transcriptional, translational, and post-translational levels, transcription initiation is the first and the most important step in gene expression, facilitating the transfer of biological information from DNA to protein. Enhancers and super-enhancers are among the master regulators of tissue- and cell-specific transcription regulation involved in cell differentiation and tumor formation. Despite four decades passing since the first discovery of enhancers in eukaryotes and extensive efforts undertaken to identify enhancers on a genomic scale during the last decade, the discovery of enhancers still faces certain limitations and needs further investigation. The perturbation of enhancer function due to genetic or epigenetic changes is closely linked to a range of human disorders, including the development and progression of cancers. Thus, the detection of early cancer-related enhancer activity and the subsequent normalization of expression abnormalities using enhancer-targeting CRISPR epigenetic editing, as well as enhancer-targeting pharmaceuticals, are regarded as groundbreaking therapeutic tactics in preclinical stages.

Information Transfer Improvement by Parallax Correction and Ptychography Reconstruction Applied to Fast Large-Area 4D STEM Experiments

Information Transfer Improvement by Parallax Correction and Ptychography Reconstruction Applied to Fast Large-Area 4D STEM Experiments

The Role of Health Information Technology During Hospital to Home Transitions.

The use of healthcare information technology (HIT) is vital for storing and exchanging health information during patient transitions, playing a significant role in care coordination for sepsis survivors. The critical role of HIT was evident during the pre-implementation phase of a study to implement an evidence-based protocol supporting the timely transition of sepsis survivors to home health and outpatient care. Through 61 semi-structured interviews involving 91 stakeholders, over half of the 33 identified themes were related to HIT. Notably, electronic health record (EHR) alert systems led to over-capture and alarm fatigue. Efficient information transfer during HHC referral highlighted the need for improved EHR access. The study underscores HIT's importance and potential while emphasizing the need for collaborative policy and interface development to promote effective transitions in care.

Exploring discrete space–time models for information transfer: Analogies from mycelial networks to the cosmic web

Fungal mycelium networks are large scale biological networks along which nutrients, metabolites flow. Recently, we discovered a rich spectrum of electrical activity in mycelium networks, including action-potential spikes and trains of spikes. Reasoning by analogy with animals and plants, where travelling patterns of electrical activity perform integrative and communicative mechanisms, we speculated that waves of electrical activity transfer information in mycelium networks. Using a new discrete space–time model with emergent radial spanning-tree topology, hypothetically comparable mycelial morphology and physically comparable information transfer, we provide physical arguments for the use of such a model, and by considering growing mycelium network by analogy with growing network of matter in the cosmic web, we develop mathematical models and theoretical concepts to characterise the parameters of the information transfer.

Control Methods in Hyperbolic PDEs

Control of hyperbolic partial differential equations (PDEs) is a truly interdisciplinary area of research in applied mathematics nurtured by challenging problems arising in most modern applications ranging from road traffic, gas pipeline management, blood circulation, to opinion dynamics and socio-economical models, as well as in environmental and biological issues, or more recently in the analysis of deep learning and machine learning methods. The topic has gained an increasing attraction of researchers in the last twenty years due to fundamental theoretical as well as numerical advances achieved in the field of nonlinear hyperbolic PDEs. The hyperbolic and the control of PDEs communities, while pursuing separate interests in their respective range of action with a different focus and, often, with a different array of technical tools, do share a substantial body of common knowledge and background. We think the time is right and the momentum is propitious to bring those communities together at a joint workshop, to mutually stimulate each other and inter- act with one another, for a marked advancement of this area of research on a broad spectrum of control ranging from theoretical to numerical problems and covering also the emerging challenges involving the interplay between (topics of) control and learning. In order to also attract young scientists to this striving field we focus on selected lectures, in-depth discussions, transfer of information from senior to young researchers, and vice versa, and invited plenary talks.

Secure and Privacy-Protected Bioinformation Implementation in Air Passenger Transport Based on DLT

Aviation information systems are a key component in ensuring efficient and smooth air transport operations. In this regard, the transfer of passenger information between parties is of paramount importance. With the continuous improvement of biometrics technology, this kind of individual identification that can provide accurate and unforgeable identification is widely used in various fields. This research presents the significance and effective application scenarios of facial recognition in biometrics in air transport operations. Due to the characteristics of aviation information systems, Distributed Ledger Technology (DLT) is used in this study for secure and private transmission of facial recognition information. Distributed systems can give a transparent and secure platform to multiple parties to access sensitive passenger data. This study uses the Corda framework as the DLT that supports CorDapp development. Based on the above techniques, this study proposes two feasible application scenarios. One is a baggage match detection system to prevent misplaced baggage, and the other is an iAPIS system that transmits passenger information in real-time communication between airlines and border control agencies. This article details how to apply the research in these two scenarios, as well as the benefits and implications of the applications. Finally, this article presents an outlook for future development and feasible directions for improvement.

Transferable, Living Data Sets for Predicting Global Minimum Energy Nanocluster Geometries.

Modeling of nanocluster geometries is essential for studying the dependence of catalytic activity on the available active sites. In heterogeneous catalysis, the interfacial interaction of the support with the metal can result in modification of the structural and electronic properties of the clusters. To tackle the study of a diverse array of cluster shapes, data-driven methodologies are essential to circumvent prohibitive computational costs. At their core, these methods require large data sets in order to achieve the necessary accuracy to drive structural exploration. Given the similarity in binding character of the transition metals, cluster shapes encountered for various systems show a large amount of overlap. This overlap has been utilized to construct a living data set which may be carried over across multiple studies. Iterative refinement of this data set provides a low-cost pathway for initialization of cluster studies. It is shown that utilization of transferable structural information can reduce model construction costs by more than 90%. The benefits of this approach are particularly notable for alloy systems, which possess significantly larger configurational spaces compared to the pure-phase counterparts.

Parametric method of information transfer in energy resources expenditure control systems

The article examines the justification of the parametric method of information transmission for the construction of energy resource consumption control systems. It is shown that the system of accounting for energy resources should be a distributed multi-level system of measurements, processing, storage and transmission of commercial accounting data and should be built on the principles of open architecture and distributed functioning. It is shown that the organization of hierarchical complexes for solving control tasks depends to a large extent on the issues of effective information transmission and that the creation of information networks is the most difficult task. sensors, into a voltage proportional to it and the corresponding binary code. The structural diagram of the device implementing the specified principle is presented. A method of calculating the parameters of the device for transmitting information from two-position sensors is proposed and an example of calculating the parameters of such a device is given