Information Network Research Articles

Research on Heterogeneous Information Network Link Prediction Based on Representation Learning

A heterogeneous information network, which is composed of various types of nodes and edges, has a complex structure and rich information content, and is widely used in social networks, academic networks, e-commerce, and other fields. Link prediction, as a key task to reveal the unobserved relationships in the network, is of great significance in heterogeneous information networks. This paper reviews the application of presentation-based learning methods in link prediction of heterogeneous information networks. This paper introduces the basic concepts of heterogeneous information networks, and the theoretical basis of representation learning, and discusses the specific application of the deep learning model in node embedding learning and link prediction in detail. The effectiveness and superiority of these methods on multiple real data sets are demonstrated by experimental verification.

Enhancing network robustness with structural prior and evolutionary techniques

Robustness optimization in complex networks is a critical research area due to its implications for the reliability and stability of various systems. However, existing algorithms encounter two key challenges: the lack of integration of prior network knowledge, leading to suboptimal solutions, and high computational costs, which hinder their practical application. To address these challenges, this paper introduces Eff-R-Net, an efficient evolutionary algorithm framework aimed at enhancing the robustness of complex networks through accelerated evolution. Eff-R-Net leverages global and local network information, featuring a novel three-part composite crossover operator. Prior network knowledge is incorporated in mutation and local search operators to expedite the construction of networks with superior robustness. Additionally, a simplified method for calculating robustness enhances efficiency, while adaptive hyper-parameters dynamically adjust operators execution probabilities for optimal evolution. Extensive evaluations on both synthetic (Scale-Free, Erdös-Rényi, and Small-World) and three infrastructure real-world networks demonstrate the superiority of Eff-R-Net. The algorithm improves robustness by 12.8% and reduces computational time by 25.4% compared to state-of-the-art algorithm in real-world network experiments. These findings underscore Eff-R-Net's versatility and potential in enhancing network robustness across different domains.

Exploring the workload of informal caregiving in the context of HIV/NCD multimorbidity in South Africa.

The importance of informal caregiving for chronic illness has been well established in African contexts but is underexplored in the context of HIV/NCD multimorbidity, particularly in South Africa. Building on treatment burden theories that investigate workload in the context of chronic illness, this paper explores how informal caregiving networks impact the capacity of people living with multimorbidity (PLWMM) in low-income settings in urban and rural South Africa. Qualitative semi-structured interviews were carried out with thirty people living with multimorbidity and sixteen informal caregivers between February and April 2021 in two settings, Cape Town (urban) and Bulungula (rural). Interviews were transcribed and data analysed both inductively and deductively using framework analysis, hereby, building on the principles of the burden of treatment theory (BoTT) as a theoretical lens. Our findings show that informal carers provided different types of support to people living with multimorbidity, including emotional, logistical, health services and informational support to ease the patient's treatment burden. Additional support networks, access to grants or financial security, and feeling a duty to care eased the perceived carer burden while a lack of social support, financial hardship and insufficient information decreased their capacity to support others. Overall, the availability of informal caregiving increases the self-management capacity of people living with multimorbidity in low-income settings in South Africa. Informal caregiving in the context of multimorbidity is structured through social obligations, kinship connections, cultural expectations, and an individual sense of agency. Carers, even when committed to assist, also experience caregiving opportunity costs, which are rarely addressed in the literature. By proposing interventions that can actively support informal caregivers, we can begin to develop solutions that can optimize the role of informal care networks, with a view to improve health-outcomes of PLWMM in South Africa.

A Heterogeneous Information Networks with an Attention Mechanism for Improving Recommender Systems

A Heterogeneous Information Networks with an Attention Mechanism for Improving Recommender Systems

The obscure object of desire: The role of political reflections, strategic calculations and informal networks in the development of national social dialogue across time in Spain over five decades

This article provides an in-depth analysis of the dynamics of social dialogue in Spain and highlights that to understand the relations between organised labour and the state a greater degree of historical sensibility in the way risks and calculations are developed in terms of exchanges and expectations is required. It goes beyond traditional institutionalist analysis to further understand how social dialogue at the state level occurs across different and complex trade-offs within political networks, even in weaker state contexts such as that of Spain. The article uses interviews with union leaders from the main Spanish unions involved in different historical moments to understand a range of uneven or opaque activities, the features of which can only be understood by expanding what we mean by the notion of political exchange, as well as the deliberate or conscious calculations and longer-term risks of such exchanges during different points in time.

A Study on Assessment of politics at the workplace At United polymers Mysuru

Assessment of politics in the workplace refers to the evaluation of power dynamics, relationships, and informal networks that influence decision-making and behavior among employees. It involves understanding how individuals use influence, alliances, and internal politics to achieve personal or professional goals. This assessment helps identify both positive and negative impacts of workplace politics on morale, productivity, and culture. It also focuses on the strategies employees use to navigate these dynamics. Ultimately, assessing workplace politics can improve leadership, communication, and organizational effectiveness

Improved Multi-Size, Multi-Target and 3D Position Detection Network for Flowering Chinese Cabbage Based on YOLOv8.

Accurately detecting the maturity and 3D position of flowering Chinese cabbage (Brassica rapa var. chinensis) in natural environments is vital for autonomous robot harvesting in unstructured farms. The challenge lies in dense planting, small flower buds, similar colors and occlusions. This study proposes a YOLOv8-Improved network integrated with the ByteTrack tracking algorithm to achieve multi-object detection and 3D positioning of flowering Chinese cabbage plants in fields. In this study, C2F-MLCA is created by adding a lightweight Mixed Local Channel Attention (MLCA) with spatial awareness capability to the C2F module of YOLOv8, which improves the extraction of spatial feature information in the backbone network. In addition, a P2 detection layer is added to the neck network, and BiFPN is used instead of PAN to enhance multi-scale feature fusion and small target detection. Wise-IoU in combination with Inner-IoU is adopted as a new loss function to optimize the network for different quality samples and different size bounding boxes. Lastly, ByteTrack is integrated for video tracking, and RGB-D camera depth data are used to estimate cabbage positions. The experimental results show that YOLOv8-Improve achieves a precision (P) of 86.5% and a recall (R) of 86.0% in detecting the maturity of flowering Chinese cabbage. Among them, mAP50 and mAP75 reach 91.8% and 61.6%, respectively, representing an improvement of 2.9% and 4.7% over the original network. Additionally, the number of parameters is reduced by 25.43%. In summary, the improved YOLOv8 algorithm demonstrates high robustness and real-time detection performance, thereby providing strong technical support for automated harvesting management.

Ring-assisted, racetrack, and Mach-Zehnder modulator: which one offers the lowest voltages and chirp-free operation?

This study presents a comparison between resonant and non-resonant electro-optical modulator configurations. The focus lies on finding the configuration with the highest modulation amplitude at the lowest drive voltage while achieving a large electro-optical bandwidth. It is found that the ring-assisted Mach-Zehnder modulator (RaMZM) offers chirp-free and resonantly enhanced modulation without bandwidth limitations imposed by the ring. In contrast, a racetrack modulator (RTM) offers resonant enhancement at the cost of a chirped modulated signal and with a bandwidth limitation. The traditional non-resonant Mach-Zehnder modulator (MZM) configuration requires higher modulation voltages while offering chirp-free operation with a flat frequency response. The RaMZM, therefore, looks like an ideal candidate for encoding information in backbone networks where small modulation voltages and perfect control over the phase of a signal are needed. The results are supported by experiments that show driverless plasmonic modulation at 220 GBaud 2PAM, 160 GBaud 4PAM and 100 GBaud 8PAM with record low peak voltages of 0.5 V.

Determinants of livelihood diversification in an integrated agricultural and non-agricultural livelihood system in Ghana

The diversification of livelihoods by households has been widely acknowledged as a way to overcome food insecurity and poverty challenges in developing countries. Diversification of livelihoods helps spread the risk among multiple livelihood earning activities to provide households with a range of their food needs all year round. By examining the integrated livelihood systems of 405 rural farm households in the Upper East Region of Ghana, empirical evidence is provided in this study using the Sustainable Livelihoods Framework to advance arguments in the literature for the creation of sustainable strategies that improve diversified livelihood systems. The mean diversification indices estimated were 0.45 for agricultural diversification systems, 0.32 for non-agricultural diversification systems and 0.59 for integrated agricultural and non-agricultural diversification systems. With the use of the Cragg two-step regression model, we demonstrate that the decision to diversify and the extent of diversification of rural livelihoods are distinct decisions and are influenced by distinct sets of factors. Similarly, for the three categories of livelihood diversification studied, the effect of these factors also differed. The results emphasize the significance of access to good road network, credit and market information in encouraging rural farm households to diversify their livelihoods. In the short term, improving access to credit and market information through community-based initiatives can provide immediate support to rural households. Communities should also organize local markets and cooperatives to strengthen their economic resilience. While government and stakeholders should focus on long-term infrastructure projects, these community actions can complement such efforts and contribute to achieving global and regional goals targeting food insecurity and poverty eradication.

Critical analysis of educational theories and their pedagogical practices: the applicability and the impact in the school context

The analysis of the main educational theories – Constructivism, Behaviorism, Socio-Constructivist Theory, Cognitivism, Humanism, and Connectivism – and their practical applications demonstrates the importance of a diverse and adaptive pedagogical approach. Constructivism: Focused on the active construction of knowledge by the student, it promotes meaningful and contextualized learning. Project-based learning (PBL) is a practice that increases student motivation and performance. Behaviorism: Emphasizes changing behavior through positive and negative reinforcements. Classroom reinforcement programs encourage appropriate behaviors, resulting in a more productive learning environment. Socio-Constructivist Theory: Highlights the importance of social and cultural interaction in learning. Methods such as cooperative learning improve academic performance and strengthen collaboration among students. Cognitivism: Focuses on internal thought processes, using tools such as mind maps to help students organize and structure knowledge, promoting critical thinking skills. Humanism: Focused on the student's personal and emotional development, it values ​​self-actualization and well-being. Welcoming learning environments and student-centered curricula promote individual growth. Connectivism: Addresses learning in the digital age, highlighting the importance of information networks and educational technologies. Integrating online platforms expands access to knowledge and involves students and parents more in the educational process.

Comparison of patch testing Brazilian (Green) propolis and Chinese (poplar-type) propolis: Clinical epidemiological study using data from the Information Network of Departments of Dermatology (IVDK).

Propolis types differ regarding their chemical composition. To compare patch test results based on Brazilian (Green) propolis with data based on Chinese (poplar-type) propolis, and to evaluate the specifications of raw materials used for the PT preparations. In the Information Network of Departments of Dermatology (IVDK), 1290 consecutive patients were patch tested with Brazilian (Green) propolis (NH400, SmartPractice Europe). Patch test reactivity was compared with results obtained with Chinese (poplar-type) propolis (NA71, SmartPractice Europe) by calculating frequencies and corresponding 95% confidence intervals. Data on the specifications of raw materials used for NH400 and NA71 were obtained from the manufacturer. Positive reactions to NH400 were found in 303 (23.5%) patients with unclear clinical relevance in most cases. Patients reacting to NH400 were less often sensitised to fragrances and colophony, but more often to nickel sulphate and cobalt chloride than patients reacting to NA71. The NH400 batch used contained high levels of aerobic bacteria, and was not purified by ethanolic extraction. Pattern of concomitant reactivity along with raw material properties suggests that the high frequency of positive reactions to NH400 may primarily result from bacterial contamination or impurities in the PT preparation rather than from propolis constituents.

The safety and efficacy of stapler method for transection of the pancreatic parenchyma during pancreatoduodenectomy (STRAP-PD trial): study protocol for a randomized control trial.

Pancreaticoduodenectomy is a highly difficult and invasive type of gastrointestinal surgery. Prevention of postoperative pancreatic fistula is important, and this may be possible by the stapler method. STRAP-PD is a single center randomized controlled trial. We compare a method of transecting the pancreatic parenchyma in pancreaticoduodenectomy using a surgical stapler device with a conventional transecting method using energy devices (e.g., scalpel, ultrasonic coagulator and incision devices). Patients with soft pancreas who are scheduled to undergo pancreaticoduodenectomy are randomized to arm A (conventional method) or arm B (stapler method). We aim to examine the safety and usefulness of dissection by the automatic suture device, with attention to the rate of pancreatic fistula ISGPF grade B or C and to postoperative complications. This is a single-center randomized study, which began in September 2023 at Wakayama Medical University Hospital. Pancreatic parenchymal transection is typically performed either by direct incision using a scalpel or by employing energy devices such as ultrasonic coagulating cutting devices during pancreaticoduodenectomy. In a prospective pilot study, we conducted pancreatic parenchymal transection in 20 consecutive normal pancreatic cases during pancreaticoduodenectomy, observing postoperative pancreatic fistula grade B in one case (5%). Traditional methods involving scalpel incision or the use of ultrasonic coagulating cutting devices have been historically favored but perceived as technically challenging, and they have been reliant upon the surgeon's skill. Notably, relatively high incidences of postoperative pancreatic fistula among patients with soft pancreas have also been observed. Our proposed stapler method may therefore be a useful method responsible for reducing the development of pancreatic fistula. This method would be as part of minimally-invasive surgery for pancreaticoduodenectomy. It uses an endoscopic linear stapler to cut the pancreatic parenchyma, so it is likely to be more convenient than conventional methods and can be used universally. TRIALREGISTRATION: University Hospital Medical Information Network Clinical Trials Registry,UMIN000052089. the Registration Date on 1st September 2023.

Higher-order network information propagation model based on social impact theory

User relationships are becoming increasingly diverse in current online social networks. This paper utilizes simplicial complexes in higher-order networks to depict multiple user relationships and characterize the topology of social networks. By employing social impact theory and factors such as user interest and information aging to define state transition rules among users, we establish a UAPR information propagation model based on simplicial complexes to simulate the information propagation process in higher-order social networks. The proposed model is simulated on three types of synthetic networks and four real-world simplicial complexes, demonstrating its ability to accurately describe the dynamics and influences of information propagation. Furthermore, our results indicate that different network structures, user interest values, information aging speeds, and intimacy levels significantly influence the information transmission process.

Link-Quality Aware Routing for Software-Defined Vehicular Networks

The routing protocol for Vehicular Ad Hoc Networks (VANETs) uses hop-count as a routing metric to determine the shortest route from source to destination. The presence of unstable links in the selected route may cause packet failures, resulting in an increase in packet retransmissions, causing network congestion, increasing total end-to-end delay, and reducing throughput. Thus, route selection based on hop count may not always be optimal in terms of route link quality. In Software-Defined Vehicular Networks (SDVN), the global view of link-state information for the vehicular networks is created at the controller; thus, a better route can be computed. Our study proposes an SDVN routing technique that considers link quality while determining the route. Our proposed framework examines the link quality using two metrics: Expected Transmission Count (ETX) and Expected Transmission Time (ETT), and this information is used by the controller to compute the flow rule. The routing performance of the proposed scheme is compared to traditional VANETs and other existing works with the help of network simulations using the NS-3 simulator. The obtained simulation results for our proposed scheme outperform in terms of performance metrics such as packet delivery ratio, average throughput, and end-to-end delay.

Необходимость установления цифрового следа при незаконном обороте лекарственных препаратов, содержащих наркотические средства, психотропные, сильнодействующие вещества

This article examines the use of the criminal element of the Internet and digital devices in criminal activities. The active use of information and telecommunication networks and digital devices in the commission of crimes in the field of illicit trafficking in medicines containing narcotic drugs, psychotropic and potent substances is emphasized. The concept of a digital footprint is given and its abandonment is indicated when a person uses digital devices and the Internet. The main advantages that the criminal world receives over the law enforcement system, with the active use of digitalization in the commission of crimes, are considered. It is pointed out the need for mandatory detection, fixation and analysis of digital traces in law enforcement activities, in order to identify the identity of the alleged offender and in order to establish the involvement of a person in the commission of a crime. Examples of the capabilities of law enforcement agencies in collecting a digital footprint in order to identify a person and establish involvement in a crime are given. The article summarizes the need to intensify the activities of law enforcement agencies related to the detection, fixation, consolidation and analysis of the digital footprint in order to fully and comprehensively document criminal acts and investigate criminal cases in the field of illicit trafficking in medicines containing narcotic drugs, psychotropic, potent substances.

The Impact of Supply Chain ESG Management on Supply Chain Resilience With Emerging IT Technologies

Supply chain resilience is an important topic, defined as the ability of a fractured supply chain to rebuild itself, maintain stability in response to changes in the external environment. This study explores the impact of supply chain ESG management on supply chain resilience. In this paper, a total of 371 questionnaires were collected from Chinese firms, and a PLS-based structural equation model was constructed for empirical testing. This study reveals the positive impact of supply chain ESG management on supply chain resilience. Information network capability mediates the relationship between supply chain ESG management and supply chain resilience. The application of emerging IT technologies positively moderates the impact of supply chain ESG governance on supply chain network capability. This study provides a novel perspective that contributes to the understanding of the importance of supply chain ESG governance in improving supply chain resilience, offers empirical evidence for the role of information network capabilities and emerging IT technologies.

Optimization of the age of correlated information in V2X networks with edge computing

Vehicle-to-Everything (V2X) communication has the potential to revolutionize the travel experience in intelligent transportation, which has received the great attention recently. However, ensuring the freshness of information from multiple sources is critical for the real-time and reliable communication in vehicular networks, especially for timely updates of service centers. To address this issue, we use a promising metric called Age of Correlated Information (AoCI), which can characterize the freshness of multi-source information. Therefore, we propose a novel model that can dynamically regulate the channel activation matching and edge computing collaboration strategy to minimize AoCI in V2X vehicular networks. Firstly, we describe the system model of a V2X network with edge computing, including definitions and assumptions for freshness of information, edge co-computing, etc. Secondly, we formulate the joint optimization problem as a source-related age minimization (SRAM) problem, which is NP-complete. A heuristic algorithm is proposed to solve it under fast-fading channel. Finally, since traditional graph models cannot capture the changing correlation between nodes in dynamic networks, we use graph convolutional networks(GCN) to extract the features of multi-source correlation. The features extracted by GCN include relevant attributes of the sources and its communication links. The features are provided as input to a double deep Q network (DDQN) for training the model that can adapt to a dynamic network environment. Extensive simulation experiments in different network scenarios validate that our proposed method can effectively and efficiently reduce the average AoCI and the computational resources.

A network security protection scheme for tax system based on elliptic curve cryptography

With the rapid development of modern information technology and network technology, the construction of tax informatization plays an important role in improving the level of tax management and work efficiency. However, in the centralized data processing mode, the establishment of large data center and the efficient, stable, and secure connection of server bandwidth have become key challenges. Moreover, the openness and interconnectivity of the tax system network pose various network security threats, seriously threatening the integrity and security of data. For the above issues, this article proposes a tax system network security protection scheme based on elliptic curve cryptography. This scheme combines hash function and elliptic curve cryptography to achieve user anonymity and secure generation of session keys, effectively ensuring the secure transmission of confidential information. The security and effectiveness of the scheme are verified through informal and formal security analysis based on security proof, BAN logic and AVISPA tool. And a comprehensive evaluation of the scheme is conducted, and the results show that the scheme significantly reduced the costs while providing security features.

Efficient photon-pair generation in layer-poled lithium niobate nanophotonic waveguides

Integrated photon-pair sources are crucial for scalable photonic quantum systems. Thin-film lithium niobate is a promising platform for on-chip photon-pair generation through spontaneous parametric down-conversion (SPDC). However, the device implementation faces practical challenges. Periodically poled lithium niobate (PPLN), despite enabling flexible quasi-phase matching, suffers from poor fabrication reliability and device repeatability, while conventional modal phase matching (MPM) methods yield limited efficiencies due to inadequate mode overlaps. Here, we introduce a layer-poled lithium niobate (LPLN) nanophotonic waveguide for efficient photon-pair generation. It leverages layer-wise polarity inversion through electrical poling to break spatial symmetry and significantly enhance nonlinear interactions for MPM, achieving a notable normalized second-harmonic generation (SHG) conversion efficiency of 4615% W−1cm−2. Through a cascaded SHG and SPDC process, we demonstrate photon-pair generation with a normalized brightness of 3.1 × 106 Hz nm−1 mW−2 in a 3.3 mm long LPLN waveguide, surpassing existing on-chip sources under similar operating configurations. Crucially, our LPLN waveguides offer enhanced fabrication reliability and reduced sensitivity to geometric variations and temperature fluctuations compared to PPLN devices. We expect LPLN to become a promising solution for on-chip nonlinear wavelength conversion and non-classical light generation, with immediate applications in quantum communication, networking, and on-chip photonic quantum information processing.

Bayesian pathway analysis over brain network mediators for survival data.

Technological advancements in noninvasive imaging facilitate the construction of whole brain interconnected networks, known as brain connectivity. Existing approaches to analyze brain connectivity frequently disaggregate the entire network into a vector of unique edges or summary measures, leading to a substantial loss of information. Motivated by the need to explore the effect mechanism among genetic exposure, brain connectivity, and time to disease onset with maximum information extraction, we propose a Bayesian approach to model the effect pathway between each of these components while quantifying the mediating role of brain networks. To accommodate the biological architectures of brain connectivity constructed along white matter fiber tracts, we develop a structural model which includes a symmetric matrix-variate accelerated failure time model for disease onset and a symmetric matrix response regression for the network-variate mediator. We further impose within-graph sparsity and between-graph shrinkage to identify informative network configurations and eliminate the interference of noisy components. Simulations are carried out to confirm the advantages of our proposed method over existing alternatives. By applying the proposed method to the landmark Alzheimer's Disease Neuroimaging Initiative study, we obtain neurobiologically plausible insights that may inform future intervention strategies.