Internet Research Articles

What factors moderate the relationship between the dual network tie strength of MNC’s foreign subsidiary in emerging markets and technological innovation?

PurposeThis study examines the moderating effects of cultural distance and the nationality of foreign subsidiaries’ CEOs on the relationship between internal/external network tie strength and technological innovation. This study focuses on foreign subsidiaries of Korean firms operating in emerging markets, based on the knowledge-based view.Design/methodology/approachTo test the hypotheses, a survey was administered to 3,840 foreign subsidiaries of Korean firms in emerging markets. Questionnaires were distributed via phone and email, and 282 (7.34%) completed questionnaires were returned. Accordingly, an empirical analysis was conducted, and the hypotheses were tested.FindingsFirst, internal network tie strength had a significant negative effect on foreign subsidiaries’ technological innovation. Second, external network tie strength had a significant positive effect on foreign subsidiaries’ technological innovation. Third, as for the moderating effect, cultural distance negatively moderates the significant negative effect of internal network tie strength on the technological innovation of foreign subsidiaries. Fourth, cultural distance positively moderates the positive effect of external network tie strength on foreign subsidiaries’ technological innovation. Fifth, foreign subsidiaries’ CEO nationality (parent country nationals) positively moderates the negative effect of internal network tie strength on foreign subsidiaries’ technological innovations. Sixth, foreign subsidiaries’ CEO nationality (parent country nationals) negatively moderates the positive effect of external network tie strength on foreign subsidiaries’ technological innovation.Originality/valuePrevious studies found a positive relationship between dual network tie strength and technological innovation in foreign subsidiaries from a knowledge-based view. This study’s significance lies in its finding that the varying strengths of foreign subsidiaries’ internal and external network connections can have different impacts on their technological innovation in the context of subsidiaries operating in emerging markets. Additionally, the moderating effects of cultural distance and the nationality of the foreign subsidiary’s CEO were examined. Therefore, this study is significant because it expands the literature on technological innovation in foreign subsidiaries.

Tan House Footbridge: Designing with repurposed steel, from early design stages to fabrication

Tan House Footbridge was a collaboration between Network Rail, WSP UK and Format Engineers. The use of repurposed steel has been central to the design process, made possible by creative digital techniques that facilitated a refinement of structural typology to match the available stock of previously unwanted material. The use of generative digital methods permitted an iterative and flexible design process that allowed any material and embodied carbon savings arising from different options to be tracked at each step towards fabrication. The collaboration is a good illustration of how to achieve carbon reduction by making informed early design decisions. The bridge was designed, detailed and fabricated between February 2022 and October 2024. At the time of writing, the authors believe Tan House to have the lowest embodied carbon of any footbridge which Network Rail has constructed on a live site. An internal Network Rail/design team study has determined that Tan House is considerably lower in CO2 than the Network Rail standard Series 400 steel rail bridge. It is testament to the fact that a bespoke and site-appropriate design does not have to be costly in capital expenditure or embodied carbon. This article describes the workflow used to deliver the bridge and shares lessons learned by the team on the use of repurposed/reclaimed material within the design and procurement process.

Fabrication of Network Spherical α-Al2O3 and Its Application on the Separator of Lithium-Ion Batteries

Ceramic-coated polyolefin separator technology is considered a simple and effective method for the improvement of lithium-ion battery (LIB) safety. However, the characteristics of ceramic powder can adversely affect the surface structure and ion conductivity of the separators. Therefore, it is crucial to develop a ceramic powder that not only improves the thermal stability of the separators but also enhances ion conductivity. Herein, network spherical α-Al2O3 (N-Al2O3) with a multi-dimensional network pore structure was constructed. Furthermore, N-Al2O3 was applied as a coating to one side of polyethylene (PE) separators, resulting in N-Al2O3-PE separators that exhibit superior thermal stability and enhanced wettability with liquid electrolytes. Notably, the N-Al2O3-PE separators demonstrated exceptional ionic conductivity (0.632 mS cm−1), attributed to the internal multi-dimensional network pore structures of N-Al2O3, which facilitated an interconnected and efficient “highway” for the transport of Li+ ions. As a consequence, LiCoO2/Li half batteries equipped with these N-Al2O3-PE separators showcased remarkable rate and cycling performance. Particularly at high current densities, their discharge capacity and capacity retention rate significantly outperformed those of conventional PE separators.

Synergistic Strategy of Hard-Template Etching and Soft-Template Protection for Rapid Fabrication of Aerogel Short Fibers

Aerogel fibers are produced by integrating aerogel nanonetworks with structures possessing large aspect ratios, which provide enhanced thermal insulation, noise attenuation, and pollutant adsorption properties compared to those of bulk aerogels. The conventional method for fabricating aerogel fibers, which involves dynamic spinning, depends on the swift solidification of gels within a coagulation bath. This process inevitably affects the gel's internal three-dimensional network structure after it has assumed a formed state, posing substantial difficulties in regulating the pore structure and mechanical strength of the aerogel fibers. In this research, we present a novel technique for the fabrication of poly(methylsilsesquioxane) aerogel short fibers (PAFs), utilizing an ice template-based static molding process. Directional ice crystals act as "hard templates" to form prismatic structures within the wet gel matrix, whereas the electrostatic repulsion from the "soft template," cetyltrimethylammonium bromide (CTAB), safeguards the fiber structure during its formation. Furthermore, the internal pore structure of the aerogel can be precisely controlled by modulating the aggregation states of CTAB micelles in water, which offers diverse reaction sites for silane hydrolysis. The fibers fabricated using this method exhibit large aspect ratios, low density, high specific surface area, and flexibility, displaying excellent insulation properties, stability at high and low temperatures, and hydrophobicity. They are suitable for use as functional fillers in high-performance wearable fabrics.

ConfExp: Root-Cause Analysis of Service Misconfigurations in Enterprise Systems

Misconfiguration is a known and increasingly serious problem in enterprise systems due to frequent code updates and retuning of the configuration parameters. Diagnosing complex, residual misconfiguration problems that lead to inaccessible services or failed transactions often starts with either a user complaint or observation by administrators, followed by a largely manual process of deciding what tests to run and how to proceed with further testing based on the test results. The goal of this paper is to automate this process and thereby make root-cause analysis of accessibility related misconfigurations much speedier and much more effective. We explore a domain-knowledge-driven methodology, called ConfExp using a network emulator that runs real enterprise networking protocols. Thus, by using commonly used tests, we show that the root-cause can be determined in all cases where discriminative tests exist. The methodology also highlights areas where more discriminative tests are needed to pinpoint the precise configuration variables at fault.

Functional Brain Networks Underlying Autobiographical Event Simulation: An Update.

fMRI studies typically explore changes in the BOLD signal underlying discrete cognitive processes that occur over milliseconds to a few seconds. However, autobiographical cognition is a protracted process and requires fMRI tasks with longer trials to capture the temporal dynamics of the underlying brain networks. In the current study, we provided an updated analysis of the fMRI data obtained from a published autobiographical event simulation study, with a slow event-related design (34-sec trials), that involved participants recalling past, imagining past, and imagining future autobiographical events, as well as completing a semantic association control task. Our updated analysis using Constrained Principal Component Analysis for fMRI retrieved two networks reported in the original study: (1) the default mode network, which activated during the autobiographical event simulation conditions but deactivated during the control condition, and (2) the multiple demand network, which activated early in all conditions during the construction of the required representations (i.e., autobiographical events or semantic associates). Two novel networks also emerged: (1) the Response Network, which activated during the scale-rating phase, and (2) the Maintaining Internal Attention Network, which, while active in all conditions during the elaboration of details associated with the simulated events, was more strongly engaged during the imagination and semantic association control conditions. Our findings suggest that the default mode network does not support autobiographical simulation alone, but it co-activates with the multiple demand network and Maintaining Internal Attention Network, with the timing of activations depending on evolving task demands during the simulation process.

The Role of Social Capital in Talent Development to Achieve SDGs: A Conceptual Framework

Objective: The objective of this study is to develop a conceptual framework to elucidate how social capital enhances talent development practice and organizational sustainable development. Theoretical Framework: The theoretical framework integrates social capital theory and organizational support theory to explore how relationships, networks, and organizational support influence talent development. Social capital theory emphasizes bonding (internal cohesion) and bridging (external connections) dimensions, which foster collaboration, trust, and resource access. Organizational support theory highlights how perceived organizational support enhances employee engagement and sustainable growth. Results and Discussion: The research synthesizes insights from existing literature on talent management and social capital. The findings indicate that bonding social capital, characterized by strong ties within an organization, fosters trust and collaboration, which enhance talent development. Bridging social capital, involving weaker, external ties, facilitates access to diverse knowledge and opportunities for resource sharing across organizational boundaries. Together, these dimensions of social capital significantly contribute to developing individual capabilities, organizational performance, and sustainable competitive advantage. Research Implications: This study makes theoretical contributions by integrating social capital theory and organizational support theory into talent development research. Practically, it provides actionable insights for employers and policymakers about leveraging internal and external networks to create inclusive and sustainable talent development strategies. The framework emphasizes the importance of a balanced approach to bonding and bridging social capital, promoting both internal cohesion and external collaboration for professional development. Originality/Value: By linking social capital to talent development, this study advances understanding in the fields of talent management and organizational studies, with implications for achieving Sustainable Development Goals (SDGs) in decent work and economic growth.

How do corporate tax hikes affect investment allocation within multinationals?

Abstract This paper studies how corporate tax hikes transmit across countries through multinationals’ internal networks of subsidiaries. We build a parsimonious multicountry model to highlight two opposing spillover effects: while tax competition between countries generates positive investment spillover, intra-firm production linkages predict negative spillover. Using subsidiary-level data and exogenous corporate tax hikes, we find that local business units cut investment by 0.5% for a 1% increase in foreign corporate tax. This result highlights the importance of production linkages in propagating foreign tax shocks, as the supply-chain-induced negative spillover dominates the positive spillover effect suggested by the conventional wisdom of tax competition.

Implementasi Jaringan VPN Site-to-Site dan Protocol OSPF Menggunakan Cisco di Sekolah Bina Bangsa

The development of technology is currently very rapid. The need for information is critical, especially in work, this need continues to grow along with users who want fast, safe, and efficient information. Sekolah Bina Bangsa is not directly connected to the network so it is very vulnerable to data leaks and can be considered less secure, so it is necessary to implement VPN (Virtual Private Network) technology. With VPN (Virtual Private Network), data delivery can be more secure because of the encryption method provided by this VPN technology. The OSPF (Open Shortest Path First) protocol is a technology that is applied to help reduce bandwidth in network usage because this protocol can determine the best path in choosing a network route, so it is expected to reduce the existing bandwidth. To prevent foreign devices that are not registered in the network system at school, the author proposes the implementation of Switch-port Security with a violation shutdown configuration. With this configuration, if a foreign device accesses the school network, it will automatically be shut down. Thus, by implementing the existing network system at Bina Bangsa School, it is hoped that data transmission between the Kebon Jeruk Campus and PIK can be carried out safely, can reduce bandwidth in the network, and also the internal network cannot be accessed carelessly by outsiders who are not registered in the network system at Bina Bangsa School.

Decentralisation as Resistance: Web3’s Potential in Countering Digital Censorship and Redefining Cyber Sovereignty

The Internet, initially celebrated as a bastion of freedom and openness, is increasingly becoming a domain of control, surveillance, and regulation by both states and private entities. The rise of state control and regulation of the Internet, along with the private sector’s expanding control over information, poses significant challenges to the ideals of freedom and openness that once defined the Internet. This article examines the transformation in Internet governance from a state of minimal regulation to a heavily controlled environment by both governments and corporations and explores how the blockchain technology and decentralised architecture underlying Web3 promise to redefine Internet governance and resist censorship. Through a mixed-method approach that synthesises insights from computer science, political science, and legal studies, the paper argues that public blockchains challenge Internet Corporation for Assigned Names and Numbers’ (ICANN) traditional control over DNS and significantly reduce the ability of centralised entities to exert control over content and communication, thereby enhancing freedom of expression and resisting censorship. The ability of Web3 to fully realise this potential is, however, dependent on overcoming complex technical and regulatory challenges.

The Role of Zero Trust Architecture in Modern Cybersecurity: Integration with IAM and Emerging Technologies

As cyber threats continue to evolve, organizations are increasingly adopting advanced security frameworks such as Zero Trust Architecture (ZTA) to protect their digital assets. ZTA operates under the principle of "never trust, always verify," acknowledging that both internal and external networks may be compromised. Integrated with Identity and Access Management (IAM), ZTA offers a dynamic security model, requiring continuous authentication and authorization for every access request. This integration ensures that sensitive resources are protected by enforcing multifactor authentication, behavioral analysis, and micro-segmentation, which collectively reduce the risk of attacks. A critical aspect of ZTA is its focus on continuous authentication and the principle of least privilege. Unlike traditional IAM systems, which grant static access, ZTA dynamically adjusts access based on real-time conditions, such as user behavior, location, and the sensitivity of data. This reduces the attack surface and minimizes lateral movement within the network. Additionally, ZTA promotes network segmentation, using IAM frameworks to enforce strict access control for each network segment. This limits the potential damage if an attacker compromises one segment. Studies have shown that ZTA is highly effective in mitigating insider threats, reducing the attack surface, and enhancing the resilience of infrastructure. While challenges remain in terms of scalability and integration complexity, the security benefits are undeniable. The increasing use of AI, machine learning, and quantum computing is expected to further strengthen ZTA's security capabilities. As organizations face more sophisticated cyber threats, ZTA is likely to become a standard in cybersecurity strategies, providing a robust, adaptable solution to protect valuable digital assets.

Principles of integrating modern waste processing facilities into the structure of large cities

The necessity for effective and coherent integration of utilitarian industrial enterprises into the urban environment is driven by the increasing ecological and urban planning requirements of large cities regarding the development of waste disposal technologies. To develop new methods and approaches to integrating solid waste processing facilities into the structure of Tyumen, Russia. An assessment of design practices in both international and Russian contexts highlights the following contemporary methods of integration into the urban environment: functional, communicational, and aesthetic. The study demonstrates the urban planning scales of integration within a large city, spanning the urban framework, the structure of urban districts, and the architectural context of development. An experimental model was developed in the study for the integration of a waste processing facility into the historical city center, taking into account the high demands for ecological sustainability of modern technologies. This model can serve as a prototype for creating a network of industrial enterprises that also incorporate social functions. The design concept of the new facility is complemented by requirements for its integration into the surrounding landscape, utilizing terracing techniques in the configuration of primary functional volumes. As a result, the stages of development and integration of modern waste processing facilities for municipal solid waste have been identified and characterized. The paper introduces principles for their integration into the urban environment, which serve as the foundation for future changes in the architectural appearance of such enterprises within the context of large cities.

Discovery of non-retinoid compounds that suppress the pathogenic effects of misfolded rhodopsin in a mouse model of retinitis pigmentosa.

Pathogenic mutations that cause rhodopsin misfolding lead to a spectrum of currently untreatable blinding diseases collectively termed retinitis pigmentosa. Small molecules to correct rhodopsin misfolding are therefore urgently needed. In this study, we utilized virtual screening to search for drug-like molecules that bind to the orthosteric site of rod opsin and improve its folding and trafficking. We identified and validated the biological effects of 2 non-retinoid compounds with favorable pharmacological properties that cross the blood-retina barrier. These compounds reversibly bind to unliganded rod opsin, each with a Kd comparable to 9-cis-retinal and improve opsin stability. By improving the internal protein structure network (PSN), these rod opsin ligands also enhanced the plasma membrane expression of total 36 of 123 tested clinical RP variants, including the most prevalent P23H variant. Importantly, these compounds protected retinas against light-induced degeneration in mice vulnerable to bright light injury and prolonged survival of photoreceptors in a retinitis pigmentosa mouse model for rod opsin misfolding.

Quantum Machine Learning for Anomaly Detection in Cyber Security Audits

Quantum Machine Learning (QML) is emerging as a transformative technology in cybersecurity, particularly in anomaly detection for cyber security audits. Traditional machine learning models are effective but face scalability and efficiency limitations as cyber threats grow more sophisticated. QML, leveraging quantum computing’s ability to process and analyze large datasets in parallel, offers potential breakthroughs in identifying anomalous patterns that could signify cyber threats such as data breaches, insider threats, or unauthorized access. Content Analysis Research Methodology used in this research work. This paper explores the integration of QML into anomaly detection systems for cyber security audits, where detecting deviations from normal behavior is crucial. Quantum algorithms, particularly those based on Quantum Support Vector Machines (QSVM), Quantum Neural Networks (QNN), and Quantum Principal Component Analysis (QPCA) can enhance the detection of subtle anomalies that classical algorithms may overlook due to noise or the complex, high-dimensional nature of cyber data. The inherent properties of quantum computing, such as superposition and entanglement, allow for more efficient feature selection and optimization, potentially leading to faster and more accurate anomaly detection. The impact of implementing QML in cyber security audits is profound. First, it enhances detection capabilities by identifying anomalies with greater precision, reducing false positives, and improving response times to cyber incidents. Second, quantum algorithms’ ability to manage exponentially large datasets makes them ideal for environments with extensive data logs, such as enterprise networks and cloud infrastructures. Third, as cyber threats become increasingly adaptive and stealthy, QML offers a dynamic solution that evolves alongside these threats by continuously learning from new patterns of attack. However, practical challenges remain, including the need for quantum hardware advancements, the development of hybrid quantum-classical models, and ensuring the interpretability of quantum models in audit scenarios. Despite these challenges, early research and experimental implementations demonstrate the potential of QML to revolutionize anomaly detection in cybersecurity audits. This paper concludes that while QML is still in its early stages, its application to anomaly detection holds promise for significantly enhancing the effectiveness of cyber security audits. The impact of this technology, when fully realized, could redefine how organizations protect their networks and data from ever-evolving cyber threats, making QML a critical area for future research and development in cybersecurity.

Unleashing R&D networks for ambidexterity: The interplay between internal and external networking capabilities

Unleashing R&D networks for ambidexterity: The interplay between internal and external networking capabilities

Construction of a Multi-View Deep Learning Model for the Severity Classification of Acute Pancreatitis.

Acute pancreatitis (AP) is a prevalent pathological condition of abdomen characterized by sudden onset, high incidence and complex progression. Timely assessment of AP severity is crucial for informing intervention decisions so as to delay deterioration and reduce mortality rates. Existing AP-related scoring systems can only assess current condition of patients and utilize only a single type of clinical data, which is of great limitation. Therefore, it is imperative to establish more accurate and data-compatible methods for predicting the severity of AP. The artificial intelligence (AI) algorithm based on artificial neural network (ANN) allow for the adaptive feature extraction for objective task through its internal complex network, instead of the hand-crafted methods commonly used in traditional machine learning (ML) algorithms. In this study, we delve into the final severity classification prediction of newly admitted AP patients, using deep learning (DL) algorithm to develop multi-view models, incorporated with patients' demographic information, vital signs, AP-related laboratory indexes and admission computed tomography (CT) images. The pancreatitis database in the platform of Clinical Data Research Center of Acute Abdominal Surgery at the First Affiliated Hospital of Dalian Medical University was used to gather AP cases. Deep neural network (DNN) and convolutional neural network (CNN) were utilized to construct models. The DNN prediction models with clinical data as input, the CNN prediction models with admission CT as input, and the multi-view models combining the two inputs were respectively established to predict the severity of AP. DL models for AP severity classification based on clinical indexes, imaging data and merged data were constructed. The multi-view model based on merged data offered more accurate prediction of the final severity classification of AP, with an overall accuracy rate of 80.26% (95% confidence interval (CI): 79.58%-80.94%). The constituent accuracy rates for mild acute pancreatitis, moderately severe acute pancreatitis, and severe acute pancreatitis were 91.69% (95% CI: 87.80%-95.57%), 64.90% (95% CI: 58.85%-70.95%), and 75.56% (95% CI: 68.58%-82.53%), respectively. The multi-view models using clinical indexes and imaging data as input outperform single-view models in AP severity prediction.

Influence of maleic anhydride grafting on the positive temperature coefficient effect of semi‐conductive composites and space charge injection to XLPE insulation

AbstractTo suppress the resistivity positive temperature coefficient (PTC) effect of ethylene‐butyl acrylate copolymer (EBA)‐based semi‐conductive shielding layer and the injection of charge carriers to insulation layer, the polar molecule maleic anhydride (MAH) is grafted onto EBA macromolecules by melt blending and thermal grafting. The resistivity temperature stability of the grafted semi‐conductive composites, as well as the space charge distribution and direct current (DC) breakdown characteristics of cross‐linked polyethylene (XLPE) insulation using the composites as the electrode is investigated. The results show that MAH grafting can significantly reduce the volume resistivity of semi‐conductive composites, especially at a higher temperature, to suppress the PTC effect. And, the grafted semi‐conductive composites can prevent the injection of charge carriers to XLPE insulation from the semi‐conductive electrode to improve the space charge distribution and DC breakdown strength of XLPE insulation. The polar anhydride groups in the grafted MAH can enhance the interaction between EBA macromolecular chains and between EBA macromolecular chains and carbon black (CB) to improve the dispersion of CB in EBA matrix and the stability of the internal conductive network at the high temperature, improving the properties of EBA‐based semi‐conductive shielding layer and DC electrical properties of XLPE insulation layer.

Three-dimensional bioprinting utilizing sacrificial material support and longitudinal printability evaluation through volumetric imaging.

In three-dimensional (3D) bioprinting, the internal channel network is vital for nutrient and oxygen transport, crucial for cell survival and tissue construction. However, bioinks' poor mechanical properties hinder precise control over these networks. Advancements in 3D printing strategies, structure characterization, and deformation monitoring can improve hydrogel scaffolds with interconnected channels. Using label-free, non-invasive, in-situ optical coherence tomography (OCT) imaging, we monitored the dynamic deformation of 3D bioprinted hydrogel scaffolds. We validated sacrificial materials' role in enhancing internal channels and introduced deformation characteristics, lateral pore ratio and pore-specific surface area as new parameters. Results from cell-laden hydrogels show that 3D bioprinting with sacrificial materials achieves high fidelity, minimizing collapse, inter-filament fusion, and enhancing lateral porosity. Furthermore, these promote cell proliferation and cell viability.

Comprehensive Approaches to Mitigate Cyber Threats Across Global Enterprise Networks and Infrastructures

Comprehensive Approaches to Mitigate Cyber Threats Across Global Enterprise Networks and Infrastructures

Study of Multi-Service Networks and Communication Systems Using Distributed Network Technology in Mountain Areas

It should be noted that the development of the digital economy directly depends on the introduction of advanced technologies: nanotechnology, biotechnology, complex energy systems technologies, quantum technologies, etc. At the same time, it is difficult to imagine the further development of corporate multiservice networks and communication systems without the widespread introduction of innovative technologies in a single information telecommunication infrastructure. The interaction of corporate multiservice networks and innovative technologies allows you to create a virtual transport network, with the help of which you manage transmitted useful and service packages and provide services. The FN concept involves the introduction of virtualization technologies, artificial intelligence methods and tools on a corporate network. The article analyzes the characteristics of corporate multiservice networks and communication systems using the technology of building distributed communication networks. The characteristics of corporate multiservice networks and communication systems using the technology of building distributed communication networks are analyzed and investigated, and a mathematical model of quality of service is proposed taking into account the management of information and network resources. It was found that the integrated performance indicators of multiservice corporate networks are largely determined by the reliability, information security and quality of service of IP / MPLS switching nodes and the IMS-Internet Protocol Multimedia Subsystem multimedia communication system using the signaling system and protocols for providing multimedia services and establishing session sessions. Thus, the results of QoS & QoE quality of service research and an analysis of numerical calculations of the probability and time characteristics of corporate multiservice networks based on the architectural concept of NGN and FN using the concept of SDN, NFV and IMS, requires the study of complex performance indicators of multiservice enterprise networks.