Priority Selection Research Articles

Optimizing the Agricultural Internet of Things (IoT) with Edge Computing and Low-Altitude Platform Stations.

Using low-altitude platform stations (LAPSs) in the agricultural Internet of Things (IoT) enables the efficient and precise monitoring of vast and hard-to-reach areas, thereby enhancing crop management. By integrating edge computing servers into LAPSs, data can be processed directly at the edge in real time, significantly reducing latency and dependency on remote cloud servers. Motivated by these advancements, this paper explores the application of LAPSs and edge computing in the agricultural IoT. First, we introduce an LAPS-aided edge computing architecture for the agricultural IoT, in which each task is segmented into several interdependent subtasks for processing. Next, we formulate a total task processing delay minimization problem, taking into account constraints related to task dependency and priority, as well as equipment energy consumption. Then, by treating the task dependencies as directed acyclic graphs, a heuristic task processing algorithm with priority selection is developed to solve the formulated problem. Finally, the numerical results show that the proposed edge computing scheme outperforms state-of-the-art works and the local computing scheme in terms of the total task processing delay.

Computational analysis of the Logistics Supply Chain from a global trade perspective

Global trade is based on coordinated factors, that means labor and products are moved from their point of origin to the point of use. Strategies have a significant impact on global trade because they enable the effective development of goods across international borders. The decision making is an important task for the development of Logistics Supply Chain (LSC) infrastructure and process. Decisions on supplier selection, production schedule, transportation routes, inventory levels, pricing strategies, and other issues need to be made. These decisions may have a big influence on customer service, profitability, operational efficiency, and overall competitiveness. The Artificial Intelligence (AI) approach of Fuzzy Preference Ranking Organization Method for Enrichment Evaluation (Fuzzy-Promethee-2) is used to assess the priority selection of the factors associated with the LSC and evaluate the importance in global trade. The role of AI is very useful compare to statistical analysis in terms of decision making. The computational analysis placed promotion of exports as the most important priority out of five selected attributes in LSC, with infrastructure development. The result suggests that LSC depends heavily on export promotion as the most significant attribute. Infrastructural development also appeared another factor influencing LSC. The foreign investment was ranked the lowest. The evaluated results are useful for the policy makers, supply chain managers and the logistics professionals associated with the supply chain management.

Trademark Text Recognition Combining SwinTransformer and Feature-Query Mechanisms

The task of trademark text recognition is a fundamental component of scene text recognition (STR), which currently faces a number of challenges, including the presence of unordered, irregular or curved text, as well as text that is distorted or rotated. In applications such as trademark infringement detection and analysis of brand effects, the diversification of artistic fonts in trademarks and the complexity of the product surfaces where the trademarks are located pose major challenges for relevant research. To tackle these issues, this paper proposes a novel recognition framework named SwinCornerTR, which aims to enhance the accuracy and robustness of trademark text recognition. Firstly, a novel feature-extraction network based on SwinTransformer with EFPN (enhanced feature pyramid network) is proposed. By incorporating SwinTransformer as the backbone, efficient capture of global information in trademark images is achieved through the self-attention mechanism and enhanced feature pyramid module, providing more accurate and expressive feature representations for subsequent text extraction. Then, during the encoding stage, a novel feature point-retrieval algorithm based on corner detection is designed. The OTSU-based fast corner detector is presented to generate a corner map, achieving efficient and accurate corner detection. Furthermore, in the encoding phase, a feature point-retrieval mechanism based on corner detection is introduced to achieve priority selection of key-point regions, eliminating character-to-character lines and suppressing background interference. Finally, we conducted extensive experiments on two open-access benchmark datasets, SVT and CUTE80, as well as a self-constructed trademark dataset, to assess the effectiveness of the proposed method. Our results showed that the proposed method achieved accuracies of 92.9%, 92.3% and 84.8%, respectively, on these datasets. These results demonstrate the effectiveness and robustness of the proposed method in the analysis of trademark data.

Risks assessment to the health of the population in the area of emissions pollutants influence of carbon graphite production enterprises

Risk assessment of the impact of the enterprise's activities on the environment includes risk assessment of the impact of the activity on the health of the population. Risk as the probability of undesirable events is an integral component of any person's life. Risk characterization integrates data on the danger of the analyzed chemical substances, the amount of exposure, parameters of "dose-response" dependence, with the aim of quantitative and qualitative assessment of risk, identification and assessment of the comparative significance of existing problems for the health of the population. In scientific terms, hazard identification is the process of establishing a causal relationship between the action of a chemical substance and the development of adverse effects on human health. The main goal of the hazard identification stage is the selection of priority, indicator chemical substances, the study of which allows to reliably characterize the sources of occurrence and the level of risk of public health impairment. Assessment of dose-response relationships is a process of quantitative characterization of toxicological information and establishment of a relationship between the likely influencing dose (concentration) of a pollutant and the incidence of adverse events in the exposed population. Characteristics of "dose-response" dependence, which are most often used to assess carcinogenic risk, have been sufficiently studied in epidemiological studies. Among them is the factor of carcinogenic potential (ICS), which reflects the probability of the development of a harmful reaction when the dose (concentration) increases by 1 mg/kg or 1 mg/m3 per exposure level, associated with a certain probability of effect (the indicators of this group are used for establishment of reference, i.e., reference doses and concentrations). The individual carcinogenic risk characterizes the upper limit of possible carcinogenic risk during the period corresponding to the average life expectancy of a person (70 years). Today, in the world, the classification and assessment of the acceptable risk to the health of the population caused by the chemical influence of chemical substances that pollute the environment is quite wide. the system of acceptance criteria recommended by WHO is used. In accordance with these criteria, the first range of risk (individual lifetime risk equal to or less than 1·10-6, which also corresponds to an additional case of serious illness or death per 1 million exposed persons) characterizes such levels of risk as are perceived by all strata population as quite small, which do not differ from ordinary everyday risks (De minimas level). Such risks do not require additional measures to reduce them and their levels are subject to periodic control. The second range (greater than 1·10-6 and less than 1·10-4) corresponds to the zone of conditionally accepted (acceptable) risk. It is at this level that most of the foreign and recommended by international organizations hygienic standards for the population as a whole are established. Levels of suitable risk belong to constant control. The third range (greater than 1·10-4 and less than 1·10-3) is suitable for professionals and unsuitable for the general population. The emergence of such a level of risk requires the development and implementation of planned health measures. The fourth range (equal to or greater than 1·10-3) is unsuitable neither for the population nor for professionals. This range is designated as De manifestis Risk, and when it is reached, it is necessary to carry out emergency health measures to reduce the risk on the part of the city authorities. During the assessment of the risk to the health of the population of Zaporizhzhia from the emissions of PJSC "Ukrgrafit", priority pollutants were identified: carbon oxides, nitrogen oxides, sulfur oxides, substances in the form of suspended solid particles of undifferentiated composition. Hazard indices were determined for individual HQ substances (non-carcinogenic risks) and in the case of combined exposure to HI, individual carcinogenic risks (ICR) and combined exposure (CRa) were calculated. Assessment of long-term effects (at the level of average annual concentration) on human health of the investigated substances. allowing to assess the chronic inhalation effect of the occurrence of negative effects in the health of the exposed population during the lifetime for the assessment and characterization of multistage risk showed that the hazard indices (HQ) do not exceed the norms.

Comparison of allo-SCT, auto-SCT and chemotherapy for the treatment of patients with low- or intermediate-risk acute myeloid leukemia: a network meta-analysis

BackgroundThe therapeutic status of allogeneic stem cell transplantation (allo-SCT) as a post-remission treatment for patients with high-risk acute myeloid leukemia (AML) was well-accepted. However, the optimal treatment for patients with low/favorable- or intermediate-risk AML who achieve complete remission has remained controversial. Therefore, we conducted a network meta-analysis to discuss this disputed problem.MethodsWe compared the effects of treatment strategies including allo-SCT, autologous stem cell transplantation (auto-SCT) and consolidation chemotherapy (CT) for patients with low/favorable- or intermediate-risk AML. The pooled HRs and 95% CIs for overall survival and disease-free survival were estimated with Stata12 and R software. Thirty clinical studies with 6682 patients were included in the meta-analysis.ResultsThe results indicated that the treatment outcome of allo-SCT was the best, followed by auto-SCT, and CT was likely the worst in the total AML patients. In patients with low/favorable-risk AML, the treatment outcome of auto-SCT was likely ranked first, followed by allo-SCT, and CT was the worst. In patients with intermediate-risk AML, the treatment outcome of haploidentical stem cell transplantation (haplo-SCT) was the best, followed by allo-SCT (excluding haplo-SCT), and auto-SCT and CT were the worst. However, the median age of the haplo-SCT group was much younger than that of the control group, which may be one of the reasons for the better prognosis of the haplo-SCT group.ConclusionsPatients with low/favorable- and intermediate-risk (non-high-risk) AML should prioritize allo-SCT if they are eligible for transplantation, and auto-SCT is optional. However, in the subgroup analysis, auto-SCT was the optimal treatment choice for patients with low/favorable-risk AML, and allo-SCT was the priority selection for patients with intermediate-risk AML, especially young patients. These findings could provide references for clinical practice.

REGIONAL HETEROGENEITY IN ADAPTING TO EXTERNAL CHALLENGES: METHODOLOGICAL FEATURES OF ASSESSMENT

In conditions of external challenges, each region reacts to changes in a special way, which determines the heterogeneity of adaptations. The aim of the article is to analyze the methodological features of assessing regional heterogeneity of adaptation to the impact of external challenges. Accordingly, the subject of the study is the consideration of the peculiarities of regional heterogeneity of adaptation to external challenges. Drawing on the analysis of scientific literature, the author systematizes and discloses the groups of approaches concerning various aspects of regional adaptation and assessment of its heterogeneity in terms of: adaptations to future changes as a result of digitalization and automation; economic development of regions and financial provision of the population's interests; spatial features of regional development; creation of conditions for population adaptation and implementation of adaptation opportunities. Based on the results of the study, the author identifies methodological features of the assessment, taking into account: the characteristics of the challenge of the external environment, the level of provision of territories with adaptive capabilities, the manifestation of new elements and structures that characterize the changing environment, their inconsistencies with the management context of regional development, the ability of the regional management system to cope with the relevant changes by optimizing regional management on the basis of a targeted impact on the priorities of the elements of the system. The author proposes the use of indicative assessment methods for the implementation of adaptation as a management function, based on the achievement of target development indicators (set by various development programs and projects), which would ensure the selection of priorities and the development of measures to increase the adaptive capacity of regions in order to improve the directions of the state policy of regional equalization. The results obtained may be in demand for further research concerning the study of regional processes and the substantiation of specific forms and mechanisms of adaptation, as well as the development of a methodology for assessing regional heterogeneity of adaptation.

Enhancing smart city operation management: Integrating energy systems with a subway synergism hub

This paper is centered on establishing a secure framework for the optimal concurrent operation of a smart city, encompassing transportation, water, heat, electrical, and cooling energy systems. The studied smart city includes the microgrid, smart transportation system (STS), energy hub (EH) and smart grid. In this regard, a subway synergism hub (SSH) as a new non-energy system is added to the smart city with the aim of serving the subway's water, heat, electrical and cooling demands as well as diminishing the operation cost of the smart city. The EH within the SSH cooperated with a desalination unit is considered to supply the subway's stations water demand by using the sea water. The investigation of the optimal allocation of the SSH unit for reducing the cost of smart city operation is also conducted by introducing a novel intelligent priority selection (IPS) analytical algorithm. In comparison to common meta-heuristic algorithms for allocation problems, the accurate optimal solution can be found in low runtime by the IPS algorithm. To achieve an accurate model of the smart city, directed acyclic graph (DAG) based blockchain approach is provided which can enhance the data and energy exchanges security within the smart city. This research paper introduces a security framework deployed in a smart city setting to establish a secure platform for energy transactions. The findings validate the effectiveness of this model and highlight the value of the IPS method. The effectiveness of the suggested approach has been assessed using the smart city system is comprised of various sections, including EVs, smart grid, microgrid, and SSH, demonstrating the credibility and accuracy of this study.

THE INFLUENCE OF PRODUCTION RISKS ON THE SAFETY OF PRODUCTION PROCESSES: ANALYSIS AND FORECASTING

The study is focused on the analysis of production risks in the field of enterprise management. Production risk is described as the probability of occurrence of undesirable events that may lead to deviations from expected results due to various management decisions. The main characteristics of such a risk are its variability and uncertainty. Risk management is defined as a procedure that includes all aspects of the company’s activities, starting with the formation of a strategy and ending with the control of acceptable risks in order to achieve the set goals. The management process covers the identification of events that may adversely affect the production process and their proper management. The article presents a logical model of production risk management and its integration with the management system of the company’s fixed assets. To assess the level of risk and its comparative analysis, the index method was proposed, which involves the calculation of the production risk index for each type of production resources in order to determine the priority of work. The article also discusses the scales for assessing the probability of production risk and the impact of its consequences, developed on the basis of mathematical forecasting. These scales can be adapted taking into account the opinions of experts and collected data. The article reveals how enterprise resources are prioritized taking into account production risk and budget constraints. This includes developing asset maintenance and repair cost plans, as well as updating the risk register and creating a probability and consequence matrix. An important feature of the model is its difference from existing approaches to the distribution of production resources, which includes the use of a formalized criterion for priority selection of works.

Abstract 2315: AI-enabled precision oncology era: Advanced and interactive interpretation of next-gneneration sequencing (NGS) reports

Abstract Background: Next-generation sequencing (NGS) has been widely adopted in clinical practice, but there are still unmet needs among physicians regarding the interpretation and application of NGS reports. These needs include selecting multi-targeted and combination therapies, keeping up with evolving treatment options and clinical trial results, and incorporating personalized medicine based on real clinical cases. Methods: To address these challenges, we propose using large language model (LLM) to analyze and interpret clinical questions, perform semantic searches in a high-quality database, and provide customized prompts and logical outputs. Our knowledge base includes diagnostic and treatment details for 600+ tumor subtypes, 620,000+ entries, 2,000+ drug details, and 440,000+ clinical trials. The database is updated automatically using a fact engine and medical literature sources. Personalized gene interpretation is incorporated using pretraining, cosine similarity, and context learning prompts. Results: Our tool, named "SmartMTB", enables personalized interpretation of genomic testing reports for precision oncology. Users input the latest clinical features using a selection-based or question-and-answer approach. The tool identifies the treatment stage and genomic variations, provides information on mutation frequencies, sensitivity and resistance of targeted and immunotherapies, and priority selection strategies for multi-gene mutations. It matches similar clinical cases and provides real-time updates on treatment options and clinical trial literature. It also facilitates patient matching for clinical trials and considers economic factors. Conclusion: We present a groundbreaking artificial intelligence (AI) tool in cancer care that revolutionizes precision oncology. This AI system, trained on extensive datasets, swiftly and accurately analyzes and interprets complex genomic and clinical data. It enables clinicians to make informed decisions about personalized treatment strategies, significantly improving patient outcomes in cancer therapy. Citation Format: Hui Chen, Zanmei Xu, Lijuan Chen, Mingmin Wang, Peng Zhang, Fei Pang, Kai Wang. AI-enabled precision oncology era: Advanced and interactive interpretation of next-gneneration sequencing (NGS) reports [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2315.

Selection history and the strategic control of attention.

Attention is biased toward features aligning with task goals and stimuli previously allocated attentional priority (selection history). The relationship between selection history and the strategic control of attention has scarcely been explored. In the present study, we utilized a modified version of the Adaptive Choice Visual Search (ACVS) task to determine whether the choice of visual search strategy varies with the strategies participants have elected to use in the past. Participants were tasked with searching through stimuli presented in two task-relevant colors on each trial to find one of two targets. The distribution of stimuli rendered in these two colors was manipulated between subjects, with one group receiving more imbalanced displays during learning. Participants who experienced the more imbalanced displays quickly learned the optimal visual search strategy of searching through the less abundant color, which maximized performance. Critically, these participants retained their tendency toward this learned strategy in a subsequent test phase in which displays were less imbalanced, in contrast to participants who completed the same test phase but had only experienced the less imbalanced displays. Our results demonstrate that, without explicit instruction, the choice of visual search strategy is to some degree dependent upon selection history. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

FARMER DECISION CRITERIA IN DETERMINING AGRICULTURAL PRACTICES DEVELOPMENT OF HORTICULTURE AND ORGANIC FOOD CROPES

Determining national and regional superior commodities is the first step in agricultural development based on the concept of efficiency in order to gain comparative and competitive advantages in facing the globalization of trade so that regional development needs to be carried out in accordance with its development, potential and development policies. The selection or arrangement of priorities is carried out using a logical and structured procedure. The preparation of the strategy is carried out by competent and representative experts related to the alternatives that will be prioritized. AHP analysis is used to solve measurable (quantitative) problems, which require opinion (judgment) or in complex situations. The three strategies used in this research are Providing Production Facilities, Strengthening Human Resources, and Strengthening Farmer Institutions. To find out the Organic Product Development Strategy, a questionnaire was carried out by distributing questionnaires to relevant government officials or agencies totaling around 30 respondents in order to obtain the information that researchers needed. The questionnaires collected from respondents were then tabulated, then analyzed using Expert Choice software. Strategy for Providing Infrastructure and Production Facilities the selection of irrigation networks has the highest percentage, namely 44.8 percent, in the strategy of strengthening human resources, processing training and product marketing, it has the highest percentage, namely 54.9 percent, in the strategy of strengthening institutions, providing market access facilities, it has the highest percentage, namely 71.0 percent, the criteria for strengthening farmers' human resources shows that the alternative strategy that is the main priority in developing organic products is strengthening farmer institutions 46.2 percent.

Priority Selection of Road Traffic Net-works in Emergency Situations Based on Internet of Vehicles

Priority Selection of Road Traffic Net-works in Emergency Situations Based on Internet of Vehicles

Supplier Selection System Using Fuzzy Analytical Hierarchy Process Method for Shirt Raw Materials

The company has several suppliers to meet the needs of raw materials for t-shirt products. Currently, the selection of suppliers is considered not optimal because there are still problems that result in hampering the production process. Therefore, companies need the right way to select suppliers. This problem can be overcome using the Fuzzy Analytical Hierarchy Process (F-AHP) method. This method is a combination of Analytical Hierarchy Process (AHP) method with fuzzy concept. Fuzzy overcomes the weaknesses of the AHP method, minimizing the level of subjectivity in an assessment of AHP to get more accurate decision results. The result of F-AHP method is supplier priority with more objective results based on priority selection criteria.

Topical issues of antibiotic resistance: modern methods of identification of bacterial pathogens and determination of their qualities

One of the most urgent problems in medicine today is the problem of antibiotic resistance. Why this problem? After all, scientists around the world proclaimed victory over microorganisms in the 50-60s of the last century? And since the 70s already began to appear information about resistant strains. Everything turned out to be not so simple. Due to uncontrolled and irrational use of antibiotics, mankind is rapidly approaching the so-called "post-antibiotic era". How to stop this "approach"? It is necessary to clearly follow the principles of rational antibiotic therapy.
 Rational antibiotic therapy requires identifying the bacterial nature of the disease, determining the sensitivity of the microorganisms to the antibiotic and starting treatment as soon as possible. To comply with these principles, rapid and accurate methods of identification of microorganisms are necessary, because it is on the basis of these methods that the most effective antimicrobial agent is selected.
 There are standard methods of identification, which include the disk-diffusion method and the serial dilution method. The main disadvantage of these methods is the length of time it takes to obtain results.
 So what are the alternative methods available? There are many methods of microbial identification, but not all of them are suitable for widespread use due to the high cost, the need for expensive equipment.
 Of all the current methods, three methods are emphasized in this review: 16S rRNA gene sequencing, MALDI-TOF MS and EUCAST RAST. Sequencing of the 16S rRNA gene is based on decoding the region of the gene, which in bacteria carries information on resistance mechanisms and structure features. MALDI-TOF MS is a desorption method of "soft" ionization caused by exposure of the matrix with the analyzed substance to pulses of laser radiation. The EUCAST RAST method is an accelerated disk-diffusion method.
 This review describes the problem of antibiotic resistance, mechanisms of bacterial resistance, as well as modern and standard methods of bacterial identification and antibiotic sensitivity.
 The aim of this review was to compare routine methods of identification of species and qualitative properties of microorganisms, causative agents of nosocomial infections, with modern technologies of microbiological testing as an important step in solving the problem of priority selection of effective antimicrobial agents.
 So, the main question of this review is: can modern methods displace standard methods of microorganism identification?

Corporate climate risk disclosure: assessing materiality and stakeholder expectations for sustainable value creation

PurposeThis study aims to evaluate the adequacy of climate risk disclosure by providing empirical evidence on whether corporate disclosure meets rising stakeholders’ demand for risk disclosure concerning climate change.Design/methodology/approachDrawing on a triangulated approach for collecting data from multiple sources in a longitudinal study, we perform a panel regression analysis on a sample of multinational firms between 2007 and 2021. Inspired by the Global Reporting Initiative (GRI) principles, our innovative and inclusive model of measuring firm-level climate risks underscores the urgent need to redefine materiality from a broader value creation (rather than only financial) perspective, including the impact on sustainable development.FindingsThe findings of this study provide evidence of limited corporate climate risk disclosure, indicating that organisations have yet to accept the reality of climate-related risks. An additional finding supports the existence of a nexus between higher corporate environmental disclosure and higher corporate resilience to material financial and environmental risks, rather than pervasive sustainability risk disclosure.Practical implicationsWe argue that a mechanical process for climate-related risk disclosure can limit related disclosure variability, risk reporting priority selection, thereby broadening the short-term perspective on financial materiality assessment for disclosure.Social implicationsThis study extends recent literature on the adequacy of corporate risk disclosure, highlighting the importance of disclosing material sustainability risks from the perspectives of different stakeholder groups for long-term success. Corporate management should place climate-related risks at the centre of their disclosure strategies. We argue that reducing the systematic underestimation of climate-related risks and variations in their disclosure practices may require regulations that enhance corporate perceptions and responses to these risks.Originality/valueThis study emphasises the importance of reconceptualising materiality from a multidimensional value creation standpoint, encapsulating financial and sustainable development considerations. This novel model of assessing firm-level climate risk, based on the GRI principles, underscores the necessity of developing a more comprehensive approach to evaluating materiality.

Towards automated homomorphic encryption parameter selection with fuzzy logic and linear programming

Homomorphic Encryption (HE) is a set of powerful properties of certain cryptosystems that allow privacy-preserving operation over the encrypted text. Still, HE is not widespread due to limitations in terms of efficiency and usability. Among the challenges of HE, scheme parametrization (i.e., the selection of appropriate parameters within the algorithms) is a relevant multi-faced problem. First, the parametrization needs to comply with a set of properties to guarantee the security of the underlying scheme. Second, parametrization requires a deep understanding of the low-level primitives since the parameters have a confronting impact on the scheme’s precision, performance, and security. Finally, the circuit to be executed influences, and it is influenced by, the parametrization. Thus, there is no general optimal selection of parameters, and this selection depends on the circuit and the scenario of the application. Currently, most existing HE frameworks require cryptographers to address these considerations manually. It requires a minimum of expertise acquired through a steep learning curve. In this paper, we propose a unified solution for the aforementioned challenges. Concretely, we present an expert system combining Fuzzy Logic and Linear Programming. The Fuzzy Logic Modules receive a user selection of high-level priorities for the security, efficiency, and performance of the cryptosystem. Based on these preferences, the expert system generates a Linear Programming Model that obtains optimal combinations of parameters by considering those priorities while preserving a minimum level of security for the cryptosystem. We conduct an extended evaluation showing that an expert system generates optimal parameter selections that maintain user preferences without undergoing the inherent complexity of analyzing the circuit.

The Selection of Investment Priorities using Expanded Dual Hesitant Fuzzy Sets

The concept of expanded dual hesitant fuzzy set is a concept that can be applied in decision-making problems. In decision-making problems, expanded dual hesitant fuzzy set can be applied to represent the opinions of multiple experts or stakeholders in a more elaborate manner. It enables decision-makers to provide more detailed information about their preferences and hesitancy.

Forecast of changes in the macroeconomic situation in Ukraine: smart economy of the future

Aims: to theoretical development of methodological tools for selecting national priorities for sustainable economic development based on the concept of a smart future economy. Methodology. This article uses a systematic approach to the study of change processes in the fields of macroeconomics, analysis and synthesis, induction and deduction, quantitative and qualitative scientific abstraction, comparison and analysis. Based on the modeling method, the article proposes a model for planning economic growth based on the indicators of socio-economic, investment, and innovation development of Ukraine and major countries of the world. Results. The paper proves the complexity of the problem of choosing the country's development priorities and its specialization, which is observed in many works of Ukrainian scientists and researchers from other countries. For this purpose, 40 scientific papers by foreign and domestic scholars were analyzed, and macroeconomic statistics data presented on official statistics websites were used. Based on the analyzed sources, the main problems of the socio-economic development of the country are determined, and the model provides a systematic approach to the formation and implementation of strategies for sustainable socio-economic development. The knowledge industry was developed, and a model was created for the selection of national innovative development priorities based on two main parameters: Overview of the national structure of innovative and specialized industries. The approach of information and communication platforms as a methodological tool for the formation of strategies for local socio-economic development is proposed. Scientific Novelty. With the help of the developed model, it is possible to determine the factors affecting the growth of Ukraine's GDP and forecast the growth of the country's economy. It is found that the transition to a smart economy and the use of the latest innovative smart technologies have the greatest impact on national economic growth. The proposed model for forecasting and evaluating the national socio-economic, investment, and innovation policy can provide the main directions for resource allocation and budgeting. Conclusion. The proposed proposals will contribute to the further development of an innovative program for socio-economic development of the country by applying the principles of the European concept of smart specialization to the Ukrainian economy. Implementation. The research materials can be used as methodological support for demonstrating the directions of regional socio-economic development.

Formation and Development of Digital Society 5.0

The relevance of this research lies in the fact that in the context of the development of the Fourth Industrial Revolution, deep and systemic transformations are taking place, which act as the driving forces for changing paradigms (concepts, models, theories), which give rise to new megatrends of the digitized society, called digital. The fourth industrial revolution influenced the rapid development of the digital society, caused by deep transformation, fundamental technological changes and their social impact on culture, economy, politics, man, his consciousness and worldview. The formation and development of digital technologies, as a factor in the implementation of the Fourth Industrial Revolution, today include a set of theoretical knowledge and practical skills of sustainable digital development, which requires the development of strategies and the selection of priorities that embrace large-scale digital technologies as the basis of a breakthrough in the technological industry. The object of research is the paradigm of digital society 5.0 as a complex social, cultural and economic phenomenon. The subject of research is the evolution of the digital paradigm of the economy, society and man in the direction of society 5.0

Spatial analysis enables priority selection in conservation practices for landscapes that need ecological security

Global urbanization has not only promoted social and economic development, but also contributed to seriously ecological challenges. As a type of sustainable landscape patterns, ecological security pattern is considered as an effective spatial pathway to simultaneously conserve ecological security and maintain social-economic development. However, the fragmentation issue of ecological sources of ecological security pattern has not been effectively addressed, although many case studies have been conducted to identify ecological security pattern. In this study, we used spatial conservation prioritization to identify the ecological security pattern of the city belt along the Yellow River in Ningxia, China. Ecological sources were selected using Zonation model while ecological corridors and key ecological nodes were identified with circuit model. The results showed that the ecological security pattern was composed of 97 ecological sources, 226 ecological corridors, 267 pinch points and 22 barriers, covering a total area of 7713.1 km2 and accounting for 34% of the study area. Ecological sources were concentrated in the Helan Mountain, Xiang Mountain and along the Yellow River. Besides, ecological corridors were dense in the southern and eastern part of the study area. Both indicated that the Yellow River and Helan Mountain were the conservation hotspots. Landscape connectivity of ecological sources identified through Zonation-based spatial conservation prioritization was better than that with the scoring approach based on ecosystem service importance. Particularly, in the Zonation approach the landscape connectivity increased with 44% while the average patch area increased with 28% when comparing with the scoring approach. The spatial conservation prioritization approach proposed in this study provides a new effective tool to construct ecological security pattern, which is conducive to the synergic enhancement of landscape connectivity and ecosystem services conservation.