Link Information Research Articles

Development of e-pocket book learning media on environmental pollution based on environmental issues in Cirebon region

In the Cirebon region, there are several environmental issues exists, one of the problems is pollution. In the context of modern information technology, there's a growing preference for electronic-based educational materials. This study aims to evaluate the environmental pollution levels in Cirebon and develop a e-pocket book as a biology learning resource for high school students. The research follows the ADDIE model (Analysis, Design, Development, Implementation, Evaluation) and utilizes observations, questionnaires, and documentation for data collection. The environmental assessment was conducted in Cirebon city and regency, and the learning media developed at MAN 2 Cirebon City. Results from the Environmental Quality Index (IKLH) indicate moderate pollution levels in Kejaksan District and mild-moderate levels in Talun District. The e-book was created using the Canva application and finalized into a link format compatible with laptops and Android smartphones. It underwent validation by material experts, media experts, biology educators, and student users, receiving favorable feedback with an overall rating of 87.24% deemed very satisfactory. It can be concluded that the development of this e-book on environmental pollution can be used as a learning media.

Scientific narrative as a factor of intensification of communicative relations of the «science — society» system

The article offers an analysis of communicative interaction in the modern academic field — among individual researchers, research teams and groups in conditions of high competition against the background of exponential growth of publication activity and digitalization of communications both within the professional community and taking into account the strengthening and transparency of interactions with the public. The author puts forward a working hypothesis, according to which it is the narrative attribute in the representation of the results of scientific research that can contain a reserve for evolutionary success within the framework of the systemic nature of communication and have a high potential for the formation of stable links between subsystems of science and other public actors, such as non-professional external observers.

Роль государственного управления автотранспортной отраслью в Кемеровской области в 1946–1965 гг.

The aim of the article is to analyze the role of state management of the motor transport industry in the Kemero-vo region in 1946–1965. Objectives: to characterize the various structures that were created by the state to con-trol the industry; to identify specific individuals who stood at the origins of the development of the automotive industry; to reveal government solutions for the effective functioning of the industry in the region. Based on the results of the analysis, the authors concluded that the state management of the motor transport industry in the Kemerovo region played a leading role during this period: the foundation of a separate region (1943 – the year of formation of the Kemerovo region) stimulated the formation of state management industry links in the field; an extensive network of various departments was created in the region, which oversaw various types of transport and road construction; a competent state policy of long-term lending under the production develop-ment fund was carried out. This made it possible to build pioneer camps, recreation centers, etc. The scientific novelty of the study lies in the fact that the authors have expanded existing knowledge on this topic, relying, among other things, on new archival materials.

Some Aspects of Animal Husbandry in Africa

It is emphasized that animal husbandry, which has existed since ancient times in many regions of Africa and is one of the most important areas of human activity, is an integral part of the socio-cultural code of the African population. To date, pastoralism plays an important role not only in the economic, but also in the social sphere of the inhabitants of vast regions of the continent; the size of herds is the main criterion for assessing the property and social status of its owner. Being the subject of trade and direct exchange, cattle bring a significant and stable income to their sellers, while at the same time performing the function of a bride price at the conclusion of marriages. The challenges of our time require a certain degree of flexibility and adaptability from the population of livestock regions, which is associated with inevitable changes in the centuries-old way of life and the system of socio-cultural ties. Attention is drawn to the fact that the tradition of husbandry is influenced by numerous factors of modern development: climate change and epizootics of recent decades have a negative imprint on livestock activities. High losses of livestock, a reduction in their per capita population over time, combined with demographic growth, have had a negative impact on the well-being of pastoralists, significantly increasing their poverty level. The governments of many African countries, in which husbandry plays a leading role, have an interest not only in maintaining existing positions, but also in improving them. In situations of epizootic danger, national livestock health surveillance systems in African countries are approached by international partners, including FAO, WHO, as well as one of the world’s leading organization whose functions include the formation of links in the field of veterinary medicine, ensuring the interaction of national and regional veterinary authorities – the International Epizootic Office (OIE). Continuous field research in livestock regions in a number of African countries provides significant assistance in the fight against livestock diseases. The use of modern information technologies in epizootiological diagnostics is increasingly becoming the basis of anti-epizootic and preventive measures.

Research of Green Innovation of Companies of Countries with Different Levels of Technological Development of Production

Abstract In the conditions of the transition to higher technological systems in the conditions of the implementation of the Sustainable Development Goals, the companies of the world face the question of effective management of green innovative development in their economic activities. The goal of the research is the formation of effective organizational and economic support for green innovations of companies of countries with different levels of technological development of production. This research contains: to describe the known positions of scientific schools regarding the managerial aspects of green innovations of companies of the world; to form the economic support of this administration, by developing an assessment of the potential of green innovations of companies of the world (the data of the Global Innovation Index Report were taken as a source of empirical data), to form criterion values of the potential of green innovations of companies of the countries for the purpose of their clustering. The research methods used include: system method; bibliometric analysis; method of assessing competitiveness; criterion method; method of generalization. The objects of evaluation include companies from five countries of Central and Eastern Europe. The main results of the study include: development of management theory; forming an assessment of the green innovation potential of companies from countries of the world with different levels of technological development of production (the data of the Global Innovation Index Report were taken as a source of empirical data); formation of criterion support for the results of evaluation of the green innovation potential of the countries’ companies. The conclusions of the study should include establishing the actualization of managing green innovations by companies of the world by involving the results of the assessment of the green innovation potential of companies of the world to the formation of the criterion values of this assessment in order to make effective management decisions on the part of all interested stakeholders. For further scientific research, to focus on the formation of effective communication links between different groups of stakeholders, the basis of this scientific direction is the criteria developed by the authors to ensure the level of green innovation potential of companies of countries in order to make effective decisions on the part of stakeholders (state bodies, investors, manufacturers, suppliers, clients, financial institutions) regarding organizational, social, economic support of green innovations of companies of countries with different levels of technological development of production. This study can be useful for the governments of countries in the development of international and national programs for the innovative development of the economy in terms of the implementation of the Sustainable Development Goals; to company managers when forming strategic and tactical plans for green innovative business development; to students and scientists in the implementation of scientific and educational programs.

A Local Pre-Rerouting Algorithm to Combat Sun Outage for Inter-Satellite Links in Low Earth Orbit Satellite Networks

Satellite networks show the development trend in global coverage, flexible access, and reliable transmission. They are the key to building a wide coverage, massive connection, three-dimensional, all-round, all-weather, space-, air- and ground-integrated information network. Due to its high frequency and large bandwidth, the laser inter-satellite link (ISL) is easily interfered with by sunlight. When sun outage occurs, the laser inter-satellite link will be interrupted for a long time. Most of the existing satellite link failure-routing algorithms are distributed and have poor load balancing capabilities. The centralized algorithm calculates paths independently for different services, and the effect is not ideal. In this paper, a local pre-rerouting algorithm (LPRA) is proposed. The center node collects the link information from the limited area before sun outage and the service information in the link that is about to be interrupted, and reroutes these services before sun outage occurs. After the occurrence of sun outage, services that originally needed to go through the failed link are forwarded according to the path calculated in advance, thereby avoiding link congestion and reducing the packet loss rate. Simulation results show that the proposed algorithm performs better than existing algorithms in terms of packet loss ratio, total delay and load balancing capabilities.

AutoEdge-CCP: A novel approach for predicting cancer-associated circRNAs and drugs based on automated edge embedding.

The unique expression patterns of circRNAs linked to the advancement and prognosis of cancer underscore their considerable potential as valuable biomarkers. Repurposing existing drugs for new indications can significantly reduce the cost of cancer treatment. Computational prediction of circRNA-cancer and drug-cancer relationships is crucial for precise cancer therapy. However, prior computational methods fail to analyze the interaction between circRNAs, drugs, and cancer at the systematic level. It is essential to propose a method that uncover more valuable information for achieving cancer-centered multi-association prediction. In this paper, we present a novel computational method, AutoEdge-CCP, to unveil cancer-associated circRNAs and drugs. We abstract the complex relationships between circRNAs, drugs, and cancer into a multi-source heterogeneous network. In this network, each molecule is represented by two types information, one is the intrinsic attribute information of molecular features, and the other is the link information explicitly modeled by autoGNN, which searches information from both intra-layer and inter-layer of message passing neural network. The significant performance on multi-scenario applications and case studies establishes AutoEdge-CCP as a potent and promising association prediction tool.

Wire and Cable Quality Traceability System Based on Industrial Internet of Things and Blockchain

Wire and cable are important industrial products involving the national economy and people’s livelihood, which are hailed as the “blood vessel” and “nerve” of the national economy, providing the basic guarantee for the normal operation of modern economy and society. The data traceability of their production and circulation process is a key factor in ensuring their quality and safety management. We aim to solve the problems of unsafe data transmission, weak quality control, and information islands in the process of wire and cable quality traceability in order to improve the production management efficiency of wire and cable manufacturing enterprises and to reduce the cost of consumer quality traceability of wire and cable products. We analyzed the technical characteristics and advantages of Industrial Internet of Things (IIoT) identity resolution and the blockchain. Key technologies are introduced, a traceability method that integrates the two is proposed, and a quality traceability framework based on the IIoT identity resolution system and blockchain technology is constructed. By analyzing the quality information composition of the wire and cable supply chain, a new quality traceability model based on the wire and cable supply chain is established. Finally, through the verification of the developed quality traceability system, the quality traceability function and quality information of each production link of wire and cable are successfully realized. This paper fills a gap in the field of cable product quality traceability using the combination of IIoT and blockchain technology. According to this model, it also has some potential for the traceability of other industrial products.

Inter-channel nonlinearity compensation in long-haul optical fiber communication using overlapped-dense LSTM network: Complexity reduction and visual understanding

The nonlinear distortion resulted from the Kerr effect in optical fibers limits the transmission capacity in long-haul optical fiber communications. In wavelength-division multiplexing (WDM) systems, the inter-channel nonlinear distortion is generally stronger than the intra-channel one, and also more difficult to be compensated, despite that there exist many reports on the nonlinearity compensation methods. Recently, recurrent neural networks have emerged as a potential solution without relying on detailed transmission link information. However, these networks often suffer from high computational complexity and lack interpretability due to their black-box nature. In this paper, we propose a novel overlapped-dense long short-term memory network (OD-LSTM). It can track the correlation of cross-phase-modulation (XPM) and consequently is capable of compensating the inter-channel nonlinear distortion. For a lower complexity, the overlapped-dense structure reduces the hidden units at time steps of different regions, since the correlation of XPM is reduced for the more distant symbols. To evaluate the effectiveness of our proposed scheme, we conduct a numerical simulation on a nine-channel WDM coherent optical transmission over a 1600-km standard single-mode fiber (SSMF) with DP-16QAM at 40 Gbaud. At the optimal optical power of −3 dBm, we observe a 0.52 dB Q-factor gain with the OD-LSTM equalizer, outperforming the digital back-propagation (DBP) with three steps per span and the Co-LSTM regressor. In terms of complexity, our proposed approach achieves a 13.5 % reduction compared to the Co-LSTM classifier, and its complexity is slightly lower than that of the ultralow complexity Co-LSTM regressor. We also discuss the visual understanding of the OD-LSTM, which provides insights into the internal mechanisms of the network.

Research on the Application of Northwest Traditional Patterns in Modern Design under the Background of Big Data

Abstract Northwest traditional patterns possess a rich history and a distinctive artistic style, offering immense potential for innovative design applications. This paper delves into the integration of these conventional motifs into contemporary design frameworks. Initially, we employ the semantic differential method to select vocabulary for the perceptual assessment of Northwest traditional patterns when incorporated into modern designs. We analyze the components of the design samples and utilize the partial least squares method to construct a correlation model between the perceptual assessment vocabulary and the design elements. This approach facilitates a detailed correlation analysis between the application of Northwest traditional motifs and their perceptual evaluation, leading to the formation of associative links between the imagery vocabulary and design features. Subsequently, we define theme, symbol, composition, and color as independent variables, with audience preference as the dependent variable, to conduct a multiple regression analysis. This analysis explores the impact of these dimensions on audience preference. The findings indicate that the significance levels of theme, symbolism, composition, and color are all below 0.05, demonstrating a positive influence on audience preferences. Notably, symbolism, with a regression coefficient of 0.356, exerts the most substantial impact on audience preference. The established correlations between design elements and perceptual evaluations, alongside the analysis of design dimensions’ influence on audience preferences, provide valuable insights for the application of Northwest traditional motifs in modern design contexts.

Cross-Industry Technological Link and Analyst Information Sharing

Cross-Industry Technological Link and Analyst Information Sharing

A Novel Similarity-Based Link Prediction Approach for Transaction Networks

A network consists of nodes and links, which represent components of a system and interactions between them, respectively. An example of networks is transaction networks, in which nodes and links represent firms and transactions, respectively. Link prediction in transaction networks is an important problem, which aims to estimate the likelihood of a transaction between two firms. It can be used to predict missing link information between firms to gain fuller knowledge as transaction information is not easily accessible between firms. In addition, firms can use it to predict future transactions as transactions evolve over time for various reasons such as a shift in customer demand, resource availability, etc. Many link prediction methods have been proposed for networks. However, to the best of our knowledge, there is no existing link prediction method for transaction networks. Existing methods are not suitable for transaction networks as they assume homophily, the tendency of individuals to associate with similar others, which may not be true in transaction networks. In addition, they do not consider the hierarchy structure exhibited in transaction networks. In this article, we propose a new similarity score for transaction networks that account for multiple, temporal, and directed transactions. We then propose a link prediction procedure based on the proposed similarity score to predict new transactions in transaction networks, which avoids the homophily assumption and exploits the hierarchical structure of transaction networks. The proposed method is tested on real-world transaction networks and yields better area under the receiver operating characteristic curve compared to existing methods.

Raspberry-like PLA/PGS biodegradable microparticles with urethane linkages: Unlocking tailored release of magnesium ions and oxygen for bone tissue engineering

Designing biodegradable microparticles with finely controlled release properties for tissue engineering systems remains a significant scientific challenge. This study introduces a novel approach by fabricating urethane-linked PLA/PGS microparticles loaded with magnesium peroxide. The microparticles offer potential applications in bone tissue engineering due to their ability to provide a controlled release of oxygen and magnesium ions while maintaining physiological pH. The PGS pre-polymer was synthesized via polycondensation and characterized using FTIR, 1H NMR, and GPC. Microparticle morphology transformed from smooth to raspberry-like upon incorporation of PGS, as observed by SEM. Microparticle size was tuned by varying PGS and PLA concentrations. FTIR analysis confirmed the successful formation of urethane links within the microparticles. MgO2-loaded PLA/PGS microparticles exhibited sustained release of dissolved oxygen and magnesium ions for 21 days while maintaining physiological pH better than PLA microparticles. Cell viability assays confirmed microparticle cytocompatibility, and ALP and Alizarin red assays demonstrated their ability to induce osteogenic differentiation. These findings highlight the potential of pH-controlled MgO2-loaded microparticles as an effective system for bone tissue engineering. In conclusion, this study presents a novel approach to designing biodegradable microparticles with adjustable release properties for bone tissue engineering. The urethane-based MgO2-loaded microparticles provide controlled release of oxygen and magnesium ions and regulate the environment’s pH, making them a promising system for bone tissue engineering applications.

SPREAD OF COMMERCIAL EDUCATION IN SOUTHERN UKRAINE AT THE BEGINNING OF THE 20TH CENTURY: KHERSON COMMERCIAL SCHOOL

The article is devoted to the birth of commercial education in one of the leading commercial, economic and industrial regions of Southern Ukraine at the beginning of the 20th century. The rapid development of economy in Kherson intensified the process of training specialists in professional education, similar to Odesa and Mykolaiv. However, there were also its own obstacles, which in turn determined certain features of the formation of this educational link. The purpose of this article is an attempt to characterize the activities of the first commercial school in one of the economic centers of Southern Ukraine at the beginning of the 20th century. Having worked out the existing source and historiographical base of this issue, it was possible to determine the prerequisites that contributed to its initiation, to outline the main stages of its functioning and to clarify its significance in the process of spreading commercial education.

Geographic proximity and homophily effects drive social interactions within VGI communities: an example of iNaturalist

ABSTRACT Social interactions among online community members contributing to volunteered geographic information (VGI) are a key element and often crucial to VGI project success. Existing studies on VGI lack investigations into the patterns of social interactions within VGI communities and the drivers that may have shaped these patterns. This study bridges this gap by analyzing social interaction patterns in the iNaturalist citizen science project and exploring potential driving factors through social network analysis. The relationships between potential drivers of social interactions in iNaturalist (i.e. geographic distance, species taxon composition similarity, and land cover composition similarity) and the establishment, intensity, and clustering of interactions were examined. The results revealed that geographic proximity, common interests in species taxon categories, and shared preferences in observation environments are major drivers of inter-contributor species identification interactions in iNaturalist. These findings are supported by theories that explain the social forces behind social link formation. Geographic distance represents physical proximity, whereas species taxon composition similarity and land cover similarity reflect homophily effects. iNaturalist and many other VGI communities are spatially embedded social networks. The discovered interaction drivers in iNaturalist generally align with those in spatial social networks and are expected to be generalizable to VGI communities beyond iNaturalist.

Основные направления взаимодействия образовательных учреждений между собой /

The relevance of the stated issues is due to the fact that at the present stage, traditional forms of education are no longer enough to provide quality services in the field of education. Today's realities dictate the need for interaction of educational institutions not only among themselves, but also with other subjects of the external environment, including employers, social institutions, public authorities, etc. This article examines such issues as types of interaction, levels of interaction, key problems, structural elements, subject composition, etc. The author pays special attention to the organization of network interaction of educational institutions, which is understood as a stable system of connections that allow developing, testing and offering innovative models of educational content and management of the educational system to the professional pedagogical community. It is important that network interaction is characterized by some features, among which the principle of openness, the formation of horizontal links, etc. deserves special attention. This has a positive effect on the quality of training and provides a range of opportunities for all participants in the interaction.

Effect of stirring speed on low acyl gellan gum fluid gels’ rheology, particle morphology and physical ageing

Fluid gels are jammed suspensions of gelled particles widely used across several industries to functionalise materials. They can be obtained for example by applying shear to a gelling hydrocolloid during its sol-gel transition. In the present study, the impact of flow rate, modulated by applying different processing stirring speeds under constant geometrical parameters, on the rheology, particle morphology and physical ageing of low acyl gellan gum fluid gels was investigated. Fluid gel particle elongation was observed in samples processed at higher stirring speeds whereas, no decrease in particle size was measured. The increase in aspect ratio is attributed due to the flow rate experienced by the particles through the geometry used to manufacture the samples. Fluid gels processed at higher stirring speeds generally showed lower low-shear viscosity, elastic modulus and higher yielding properties and interconnectivity. This might be due to the elongation of the fluid gel particles which would decrease particle voluminosity but increase the likelihood of mechanical entanglement, increasing their viscous dissipation. In addition, samples manufactured at higher stirring speeds exhibited a G′ increase with the number of shear cycles performed whereas, samples processed at lower stirring speeds showed a G′ decrease with the number of shear cycles performed. This behaviour might be caused by the balance between two counteracting mechanisms: abrasion (decrease in G′) and compaction (increase in G′). In addition, the higher the stirring speed the higher the ageing exponent. This might be due to the larger surface area of elongated particles which might ease interparticle link formation. Furthermore, the impact of the gravitational field on the physical ageing of low acyl gellan gum fluid gels was investigated by entrapping silica microparticles within the fluid gel particles, allowing tuning the density difference between the continuous and dispersed fluid gel phases. Finally, this study helps providing a better understanding on how processing stirring speed could be used to tune fluid gels’ properties for specific industrial applications.

Link prediction and feature relevance in knowledge networks: A machine learning approach.

We propose a supervised machine learning approach to predict partnership formation between universities. We focus on successful joint R&D projects funded by the Horizon 2020 programme in three research domains: Social Sciences and Humanities, Physical and Engineering Sciences, and Life Sciences. We perform two related analyses: link formation prediction, and feature importance detection. In predicting link formation, we consider two settings: one including all features, both exogenous (pertaining to the node) and endogenous (pertaining to the network); and one including only exogenous features (thus removing the network attributes of the nodes). Using out-of-sample cross-validated accuracy, we obtain 91% prediction accuracy when both types of attributes are used, and around 67% when using only the exogenous ones. This proves that partnership predictive power is on average 24% larger for universities already incumbent in the programme than for newcomers (for which network attributes are clearly unknown). As for feature importance, by computing super-learner average partial effects and elasticities, we find that the endogenous attributes are the most relevant in affecting the probability to generate a link, and observe a largely negative elasticity of the link probability to feature changes, fairly uniform across attributes and domains.

Ensemble clustering with low-rank optimal Laplacian matrix learning

The co-association (CA) matrix that describes connection relationship between instances is of importance for ensemble clustering. Existing ensemble clustering methods demonstrate that Laplacian matrix can help to improve the quality of CA matrix and finally produce better clustering results. However, they usually consider the first-order information only and ignore the higher-order information that exists among base clustering results. To address this issue, this paper introduces the theory of higher-order connectivity in ensemble clustering for the first time and further proposes a low-rank optimal Laplacian matrix learning (LROLML) approach for ensemble clustering. Specifically, the proposed LROLML first constructs a set of multi-order Laplacian matrices and then learns the optimal Laplacian matrix from the Laplacian matrix set with different orders. The optimal Laplacian matrix mines more higher-order link information, thereby improving the ensemble performance. We use alternating direction method of multipliers (ADMM) to solve the optimization problem and then apply the average-link hierarchical agglomerative clustering to get the final result. We conducted extensive experiments on 20 popular datasets to validate the proposed LROLML, which is compared with two types of results of basic k-means clustering and seven state-of-the-art ensemble clustering models. The results demonstrate the LROLML is superior to the compared models, showing that the LROLML is promising for ensemble clustering.

Aggregating distributed KOSs: enriching with meta information and linking to the multilingual KOS registry

PurposeThis study aims to collect distributed knowledge organization systems (KOSs) from various domains, enrich each with meta information and link them to the multilingual KOS registry, facilitating integrated search alongside KOSs from various languages and regions.Design/methodology/approachThis research involved collecting and organizing KOS information through three primary steps. The initial phase involved finding KOSs from Web search results, supplemented by the Korea ON-line E-Procurement System (KONEPS) and the National R&D Integrated Notification Service. After obtaining these KOSs, they were enriched by structuring contextual meta information using Basic Register of Thesauri, Ontologies and Classification (BARTOC) metadata elements and established dedicated media wiki pages for each. Finally, the KOSs were linked to the multilingual KOS registry, BARTOC, ensuring seamless integration with KOSs from various languages and regions and creating connections between each registry entry and its associated KOS wiki page.FindingsThe research findings revealed several insights, as follows: (1) importance of a stable source for collecting KOS: no national body currently oversees KOS registration, underscoring the need for a systematic approach to collect dispersed KOSs. For Korean KOSs (K-KOSs), KONEPS and National R&D Integrated Notification Service are effective data sources. (2) Importance of enhanced metadata: merely collecting KOSs were not enough. Enhanced metadata bridges access gaps and dedicated wiki pages aid user identification and understanding. (3) Observations from multilingual registry uploads: When adding KOSs to a multilingual registry, similarities were observed across languages and regions. Recognizing this, the K-KOSs were linked with their international counterparts, fostering potential global collaboration.Research limitations/implicationsDue to the absence of a dedicated KOS registry agency, the study might have missed KOSs from certain fields or potentially over-collected from others. Furthermore, this study primarily focused on K-KOSs and their integration into the BARTOC registry, which might influence the methods and perspectives on collecting and establishing links among analogous KOSs in the registry.Originality/valueThis research pursued a stable method to detect KOS development and revisions across various fields. To facilitate this, we used the integrated e-procurement and R&D notification system and added meta information to aid in the identification and understanding of KOSs, which includes media wiki pages. Furthermore, link information was provided between the BARTOC registry and the Korean KOS websites and media wiki pages.