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Recognition and optimization of landscape genes in traditional settlements: a case of Meishan area
Get PDFTraditional settlement landscapes provide vital ecosystem services and represent significant cultural heritage, making their preservation crucial for national cultural development and rural revitalization. This study focuses on Meicheng Town in the Meishan area, utilizing landscape gene theory to classify and identify cultural landscape features. By integrating the Analytic Hierarchy Process (AHP) and Fuzzy Comprehensive Evaluation (FCE), the study develops a landscape gene sorting index system, systematically evaluating 16 sub-categories of landscape factors. The results highlight topography and building decoration as dominant features that should be prioritized for preservation. However, areas such as building materials, traditional culture, and folk customs require significant improvement. Additionally, the river and road landscapes present opportunities for enhancement to strengthen the town’s cultural identity and aesthetic quality. The study provides practical recommendations for optimizing Meicheng Town’s landscape, balancing the preservation of traditional elements with modern development needs. This approach addresses gaps in the literature on settlement landscape genes and offers strategies for sustainable rural cultural landscape development
Lithuania’s economic trajectory in the shadow of the Ukraine conflict
Get PDFThe ongoing situation between Russia and Ukraine has sent shockwaves through Europe, impacting the economies of nearby nations like Lithuania. Lithuania, a member of the European Union, finds itself in a complicated position due to its historical and political connections to Russia and Ukraine. Using such methodology as literature review, correlation, and regression analysis, structural equation modelling this research dives into how war is affecting Lithuania’s economy, including changes in trade, energy security, and relocation of investments. Because of the sanctions against Russia, an important trading partner for Lithuania, their usual trade routes have been thrown off. This has forced Lithuania to look for new markets and other places to get energy. At the same time, Lithuania has had to spend more on its military and faces greater uncertainty because of the conflict, which has changed fiscal policies and investor confidence. The conflict has also sped up Lithuania’s move towards Western markets and strengthened its employment market. This paper takes a deep dive into Lithuania’s economic journey within the changing landscape of security, economic indicators, and policy reactions. The results emphasize both the weaknesses and strengths of Lithuania’s economy in the face of ongoing geopolitical conflict.
Article in English.
Lietuvos ekonominė trajektorija Ukrainos konflikto šešėlyje
Santrauka
Šiuo metu vykstanti situacija tarp Rusijos ir Ukrainos sukėlė didelį atgarsį Europoje, paveikdama ir netoliese esančių šalių, tokių kaip Lietuva, ekonomikas. Lietuva, kaip Europos Sąjungos narė, atsidūrė sudėtingoje padėtyje dėl savo istorinių ir politinių ryšių su Rusija ir Ukraina. Taikant tokius metodus kaip literatūros apžvalga, koreliacijos ir regresinė analizė, struktūrinių lygčių modeliavimas, šiame tyrime gilinamasi į tai, kaip karas veikia Lietuvos ekonomiką – įskaitant prekybos pokyčius, energetinį saugumą ir investicijų perskirstymą. Dėl sankcijų Rusijai, kuri yra svarbi Lietuvos prekybos partnerė, buvo sutrikdyti įprasti prekybos keliai. Tai privertė Lietuvą ieškoti naujų rinkų ir alternatyvių energijos šaltinių. Tuo pačiu metu Lietuva buvo priversta didinti karines išlaidas ir susiduria su didesniu neapibrėžtumu dėl konflikto, kuris paveikė fiskalinę politiką bei investuotojų pasitikėjimą. Konfliktas taip pat paspartino Lietuvos orientaciją į Vakarų rinkas ir sustiprino darbo rinką. Šiame darbe nuodugniai nagrinėjama Lietuvos ekonominė kelionė kintančiame saugumo, ekonominių rodiklių ir politikos atsako kontekste. Rezultatai pabrėžia tiek Lietuvos ekonomikos silpnąsias, tiek stipriąsias puses nuolatinio geopolitinio konflikto akivaizdoje.
Reikšminiai žodžiai: geopolitinis konfliktas, ekonomikos augimas, karas, ekonominis stabilumas
Impact of the war in Ukraine on international trade trends
Get PDFThe ongoing war in Ukraine, which began in 2014, has significantly disrupted global trade, particularly in energy, agriculture, and supply chains. This study integrates economic, trade, and geopolitical theories with empirical data to analyse the conflict’s immediate and long-term effects on international trade. Key findings reveal a sharp decline in Ukraine’s agricultural exports, with grain and oilseed shipments dropping over 40% since 2022, exacerbating global shortages. Fertilizer exports from both Russia and Ukraine have also plummeted, causing a 70% increase in global prices and impacting agricultural productivity in countries like Bangladesh, Egypt, and India. In response, nations have reshuffled trade partnerships, with Egypt increasing wheat imports from India and Brazil, and Indonesia turning to Australia and China for fertilizers, albeit with higher costs and logistical challenges. The conflict has led to a 20% rise in global food prices, worsening food insecurity, especially in vulnerable regions. The study underscores the need for diversified supply sources, enhanced domestic agricultural production, and resilient supply chains to mitigate the impacts of geopolitical conflicts on global trade and food security.
Article in English.
Ukrainos karo įtaka tarptautinės prekybos tendencijoms
Santrauka
Besitęsiantis karas Ukrainoje, prasidėjęs 2014 metais, smarkiai sutrikdė pasaulinę prekybą, ypač energetikos, žemės ūkio ir tiekimo grandinių srityse. Šiame tyrime ekonominės, prekybos ir geopolitinės teorijos yra derinamos su empiriniais duomenimis, siekiant išanalizuoti konflikto tiesiogines ir ilgalaikes įtakas tarptautinei prekybai. Pagrindiniai tyrimo rezultatai atskleidžia staigų Ukrainos žemės ūkio eksporto mažėjimą, javų ir aliejinių sėklų eksportas nuo 2022 metų sumažėjo daugiau nei 40 %, dar labiau pablogindamas pasaulinį maisto produktų trūkumą. Trąšų eksportas tiek iš Rusijos, tiek iš Ukrainos taip pat smarkiai sumažėjo, dėl to pasaulinės kainos išaugo 70 % ir paveikė žemės ūkio produktyvumą tokiose šalyse kaip Bangladešas, Egiptas ir Indija. Į tai reaguodamos, šalys pergrupavo prekybos partnerystes, Egiptas padidino kviečių importą iš Indijos ir Brazilijos, o Indonezija kreipėsi į Australiją ir Kiniją dėl trąšų, nors tai ir kelia didesnes išlaidas bei logistinius iššūkius. Konfliktas lėmė 20 % pasaulinių maisto kainų kilimą, o tai dar labiau pablogino maisto saugumo situaciją, ypač pažeidžiamuose regionuose. Tyrime pabrėžiama būtinybė diversifikuoti tiekimo šaltinius, stiprinti vidaus žemės ūkio gamybą ir atsparias tiekimo grandines, siekiant sušvelninti geopolitinių konfliktų įtaką pasaulinei prekybai ir maisto saugumui.
Reikšminiai žodžiai: pasaulinė prekyba, Ukrainos karas, trąšų ir kviečių rinkos nepastovumas, žemės ūkio eksportas, maisto saugumo įtaka
Dynamical analysis and adaptive synchronization of a new 6D hyperchaotic system with the cosine function
No full textThis paper presents a novel 6D dynamic system derived from modified second-type 3D Lorenz equations using state feed- back control. While these original 3D equations are structurally simpler than the classical Lorenz equations, they generate more topologically complex attractors with a distinctive two-winged butterfly structure. The proposed system is the most compact of its kind in the literature, containing only 11 terms: two cross-product nonlinearities, two piecewise linear functions, one cosine function, five linear terms, and one constant. The newly developed 6D hyper- chaotic system exhibits rich dynamic properties, including hidden attractors and dissipative behavior. A detailed dynamic analysis has identified two unstable hyperbolic equilibrium points, indicating the potential for self-exciting attractors. Additionally, bifurcation diagrams were constructed, Lyapunov exponents were computed, and the maximum Kaplan-Yorke dimension DKY = 3.23 was obtained at parameter value a = 0.5, revealing the high complexity of the hyperchaotic dynamics. Furthermore, multistability and offset boosting control were examined to gain deeper insights into the system’s behavior. Finally, synchronization between two identical 6D hyperchaotic systems was successfully achieved using an adaptive control method
Multi-bus-line joint operation strategy of optimizing bus speed and intersection signal priority to minimize passengers waiting time
Get PDFThe rapid increase in the number of vehicles reduces the efficiency of transportation networks in modern big cities. Thus, minimizing passengers waiting time by bus has become an inevitable approach. Through intelligent bus systems and Dedicated Bus Lanes (DBLs), jointly optimizing bus speed and intersection signal priority has become a feasible research objective for multi-bus-lines. Moreover, the length of Beijing (China) DBLs will be 1020 km in 2022. Considering the requirements of the Beijing Bus Group, a problem model is formulated, including multi-bus-lines, time-varying passenger flow, bus-speed-control only on DBLs, and intersection signal control. In this study, the real-time framework of the multi-bus-line joint operation strategy with the Transformable Salp Swarm Algorithm (TSSA) is proposed. Moreover, the small optimization interval effectively reduces the impact of bus-speed-control inaccuracy and the errors between the joint optimization scheme and actual operation states. In the real-time framework, only the speed of the bus traveling on DBLs could be guided in the form of real-number speed, and this bus-speed scheme is safe. Additionally, the strategy could compensate for the travel time in the non-priority direction after buses pass through intersections, and this is effective to avoid traffic congestion. As the online optimization algorithm, TSSA simulates the grouping activity of salp swarms. Based on actual data from Beijing Bus Group, 6 test problems are constructed, and the joint operation strategy outperforms others.
First published online 20 January 202
The interplay between geometry and numbers of blade in ducted propeller systems
Get PDFThis study designs and optimizes a ducted propeller (DP) via graphical and numerical methods. Ducted propellers with a thrust-to-omega ratio ranging between 0.12 and 0.20 and blade optimizations at the design point were obtained. The geometric selection of the blade path has a significant effect on the airflow in the duct system. Reasonable optimization of the dimensions of the sheath, tube, and curvature can effectively improve the axial flow. For different aerodynamic loads, the corresponding graphs are produced. Therefore, the number of blades increases, and the overall stall margin is expanded for a particular blade. The large discrepancy between the mechatronic properties of experimental and computational studies of DPs implies that the blade geometry can largely affect the mechatronic properties of DP models, thus offering a new direction for designing the development of propulsion systems. In this article, important studies on the impact of the blade geometry and number on DP thrust generation are discussed
Railway multi UAV collaborative encirclement strategy based on Grey Wolf optimization dynamic encirclement points
Get PDFTo address the threat of invading drones along railway lines, this paper proposes a multi-UAV cooperative capture strategy based on the Grey Wolf Optimizer (GWO) algorithm and dynamic capture points. Firstly, a motion model in three-dimensional space is established according to the movement characteristics of invading drones along railway lines. Secondly, three-dimensional capture points are dynamically generated based on the movement direction of invading drones, and a negotiation allocation mechanism is designed to achieve optimal matching between capture points and UAVs. Then, an objective function combining path consumption and encirclement effect is constructed, and the GWO algorithm is used to optimize the UAV heading angle increment in real-time. Finally, the effectiveness of the algorithm is verified through three-dimensional simulations. The simulations show that this strategy can achieve efficient capture in three-dimensional environments. Compared with strategies without GWO optimization, the average capture time is reduced by 55.5%, and the capture success rate is improved by 4.8%. Furthermore, in comparison with other mainstream optimization algorithms such as Particle Swarm Optimization (PSO), Genetic Algorithm (GA), and Differential Evolution (DE), our approach yields superior performance in both the average number of capture steps (55.7 steps) and success rate (100%), providing an efficient and reliable technical solution for railway airspace security protection
Addressing hidden challenges in urban renewable energy integration via a hybrid-decision model
Get PDFThe integration of renewable energy into urban development has some critical legal challenges. However, the literature lacks a systematic framework for prioritizing the most critical obstacles. Existing studies generally address the legal barriers to the integration of renewable energy into urban areas at a general level. Therefore, these studies do not provide a systematic framework to prioritize which barriers are more critical. This deficiency creates some important problems such as increasing investor distrust, delays in projects and increasing costs. This study tries to fill this gap by establishing a novel hybrid decision-making model to evaluate hidden legal challenges in renewable energy integration. The proposed model follows a structured methodology by integrating z-scoring method to ensure expert representativeness, p,q,r-Fractional fuzzy sets to handle uncertainties, entropy method to compute the weights of the identified legal barriers and grey relational analysis to identify the most effective strategy alternatives. The main contribution is that prior investment strategies can be identified to overcome these legal challenges regarding the integration of renewable energy into urban development by creating a novel model. The use of p,q,r-Fractional fuzzy sets in this model provides an important contribution to the literature. With the help of considering these sets, more complex and multi-dimensional uncertainties can be managed more effectively. The findings highlight the significance of financial incentives and streamlined regulatory processes to have the sustainable transformation of urban areas.
First published online 23 September 202
Environmental, social, and governance practices and reporting readiness in small and medium-sized enterprises
Get PDFFollowing the European Sustainability Reporting Standards (ESRS), in 2026, the non-financial reporting obligation will be extended to small and medium-sized enterprises listed on the regulated market and meet employment and financial criteria. The obligation will also affect their contractors, suppliers, customers, and all stakeholders that influence a company’s overall Environmental, Social, and Governance (ESG) performance. The study aims to identify the Small and Medium-sized Enterprises’ (SME) practices in the field of ESG and recognise whether they are ready to report on their ESG activities. A quantitative method was used to obtain a general picture of the approach to ESG practices. The study was conducted among 300 Polish companies. The study results show that about half of the surveyed small and medium-sized enterprises conduct ESG activities and monitor ESG indicators. More than half demonstrate basic or good readiness for ESG reporting following the adopted criterion. This study’s contribution is twofold. First, it enriches the current state of knowledge by adding original insights into the ESG practices of SMEs, while most existing studies focus on the ESG activities of large enterprises. Second, the study’s novelty is its attempt to assess the readiness for ESG reporting at the corporate and country levels
Geoinformation wildfire mapping of Ukraine: analyzing FIRMS data for effective fire management
Get PDFSustainable growth in Earth remote sensing data necessitates the advancement of interpretation methods to address a wide array of economic challenges. This research paper proposes the development of a methodology to automate the assessment of fire-affected areas using GIS software such as ArcGIS and QGIS. Data on fire localization from NASA/NOAA Suomi NPP and NOAA-20 and MODIS (M6) satellites, sourced from NASA’s Fire Information for Resource Management System (FIRMS), as well as annual land use/land cover data from ESA WorldCover 2021, are utilized for this study. The series of maps obtained from the aggregation and generalization of fire distribution data for individual years across the administrative regions of Ukraine from 2021 to 2023 allows for the assessment of fire density, their correlation with different land cover types, and spatio-temporal changes. Graphs showing the distribution of fires based on land cover types in Ukraine for 2021–2023 have been generated. Additionally, the dynamics of fire occurrences in 2023 compared to 2022 are presented