The purpose of this paper is to suggest some ways and mechanisms for creating long-term peace based on sustainable development of the world and the purpose of the work is to develop recommendations aimed at counteracting the emergence of dictatorial regimes that were legitimately established. Five common features of such dictators have been identified, namely: coming to power in a legitimate way, using manipulative technologies, openly declaring their aggressive intentions, gradually implementing their aggressive intentions, creating a military potential with the active participation of developed countries, including those with established democracies. The reasons for the creation of dictatorial regimes are substantiated, namely: the imperfection of electoral legislation, excessive conservatism of legislation, insufficient determination and timeliness of countering the strengthening of dictatorships, “national egoism”, the unscrupulousness of dictators in their foreign and domestic policies. It was determined that in order to actively oppose dictatorial regimes, it is necessary to: improve the system of elections to the highest positions and to the legislative bodies of the state, put a strong barrier against manipulative technologies and fakes, through the improvement and effective application of international legislation with the involvement of artificial intelligence, determine the strategy of relations with dictators in all directions in advance: economic, diplomatic, sports, scientific and technical, etc., establish the scope of relations in direct proportion to the index of democracy in a country with an authoritarian regime and, in order to prevent negative consequences on the economy and social condition of the society of one’s country, determine and carefully regulate import and export activities. It is proposed to start an indicator of the effectiveness of the head of state and an internal truth index of the head of state, as well as measures for moral stimulation of heads of state. As a result of the study, two root causes of threats to the existence of humanity were additionally identified, which directly affect the formation of dictatorial regimes. 1) The emergence on the basis of modern information technologies of a powerful system of manipulative technologies, the use of which leads to the power of future dictators. 2) Belated opposition of the democratic world to the formation of dictatorships. This is expressed in condescension to the initial illegal actions of future dictators, uncontrolled cooperation in the economic, political and humanitarian spheres. Two key mechanisms for achieving sustainable development and long-term peace are proposed.

Kampar Regency, as the largest pineapple producer in Riau Province, has yet to provide significant added value for the surrounding SMEs. The limitations in technology and innovation, infrastructure support, and market access have prevented this potential from being optimally utilized. A Technopark can provide the necessary facilities and infrastructure to enhance production efficiency, innovation, and product quality, thus driving local economic growth. The objective of this study is to identify and determine potential locations for the development of a pineapple-based Technopark in Kampar Regency. This study is crucial as a fundamental consideration in selecting the technopark location and assessing the effectiveness and success of the technopark area. The method used in this study is AHP-GIS to analyze relevant parameters in the site selection process for the technopark area. Parameters considered in this study include slope, land use, availability of raw materials, accessibility of roads, access to water resources, proximity to universities, market access, population density, and landfill. The analysis results indicate that the percentage of land highly suitable for the technopark location is 0.78%, covering an area of 8943 hectares. Based on the analysis, it is recommended that potential locations for the development of a pineapple SMEs-based technopark in Kampar Regency are dispersed in Tambang District, encompassing three villages: Rimbo Panjang, Kualu Nenas and Tarai Bangun. The findings of this study align with the spatial planning of Kampar Regency.

Previous studies support the direct relationship between outdoor physical activity and natural spaces in cities. The Active City and Nature concept explores the relationship between urban, green and active environments; it aims to demonstrate the scientific evidence for the need for action to be taken to increase participation in active living and sport, leading to healthier cities and communities. Our research seeks to analyse the city’s natural spaces as scenarios to encourage physical activity and sport, through a combined study of qualitative research techniques: the use of a digital webGIS platform, collaborative maps made by citizens, and surveys conducted with citizens and the local government. This methodology has been tested in the city of Malaga, the European City of Sport 2020. The study of the city’s main sport areas, the waterfront and natural green spaces provided data on the types of physical activity taking place in each of these areas and the physical activity needs of citizens. This research argues that it is important to know the criteria of local communities for physical activity and/or sport in natural environments, as well as the main demands expressed. This will provide valuable information to design and manage natural public spaces as a means of promoting physical activity and healthy habits.

In rural areas, land use activities around primary arterial roads influence the road section’s traffic characteristics. Regulations dictate the design of primary arterial roads to accommodate high speeds. Hence, there is a mix of traffic between high-speed vehicles and vulnerable road users (pedestrians, bicycles, and motorcycles) around the land. As a result, researchers have identified several arterial roads in Indonesia as accident-prone areas. Therefore, to improve the road user’s safety on primary arterial roads, it is necessary to develop models of the influence of various factors on road traffic accidents. This research uses binary logistic regression analysis. The independent variables are carelessness, disorderliness, high speed, horizontal alignment, road width, clear zone, road shoulder width, signs, markings, and land use. Meanwhile, the dependent variable is the frequency of accidents, where the frequency of accidents consists of multi-accident vehicles (MAV) and single-accident vehicles (SAV). This study collects data for a traffic accident prediction model based on collision frequency in accident-prone areas. The results, road shoulder width, and road sign factor all have an impact on the frequency of traffic accidents. According to a realistic risk analysis, MAV and SAV have no risk difference. After validation, this model shows a confidence level of 92%. This demonstrates that the model generates estimations that accurately reflect reality and are applicable to a wider population. This research has the potential to assist engineers in improving road safety on primary arterial roads. In addition, the model can help the government measure the impact of implemented policies and engage the public in traffic accident prevention efforts.

The proportion of national logistics costs to Gross Domestic Product (NLC/GDP) serve as a valuable indicator for estimating a country’s overall macro-level logistics costs. In some developing nations, policies aimed at reducing the NLC/GDP ratio have been elevated to the national agenda. Nevertheless, there is a paucity of research examining the variables that can determine this ratio. The purpose of this paper is to offer a scientific approach for investigating the primary determinants of the NLC/GDP and to advice policy for the reduction of macro-level logistics costs. This paper presents a systematic framework for identifying the essential criteria for lowering the NLC/GDP score and employs co-integration analysis and error correction models to evaluate the impact of industrial structure, logistics commodity value, and logistics supply scale on NLC/GDP using time series data from 1991 to 2022 in China. The findings suggest that the industrial structure is the primary factor influencing logistics demand and a significant determinant of the value of NLC/GDP. Whether assessing long-term or short-term effects, the industrial structure has a substantial impact on NLC/GDP compared to logistics supply scale and logistics commodity value. The research offers two policy implications: firstly, the goals of reducing NLC/GDP and boosting the logistics industry’s GDP are inherently incompatible; it is not feasible to simultaneously enhance the logistics industry’s GDP and decrease the macro logistics cost. Secondly, if China aims to lower its macro-level logistics costs, it must make corresponding adjustments to its industrial structure.

With the purpose of strengthening the knowledge and prevention of landslide disasters, this work develops a methodology that integrates geomorphological mapping with the elaboration of landslide susceptibility maps using geographic information systems (GIS) and the multiple logistic regression method (MLR). In Mexico, some isolated works have been carried out with GIS to evaluate slope stability. However, to date, no practical and standardized method has been developed to integrate geomorphological maps with landslide inventories using GIS. This paper shows the analysis carried out to develop a multitemporal landslide inventory together with the morphometric analysis and mapping technique for the El Estado River basin where, selected as the study area, is located on the southwestern slope of the Citlaltepetl or Pico de Orizaba volcano. The geological and geomorphological factors in combination with the high seasonal precipitation, the high degree of weathering and the steep slopes predispose its surfaces to landslides. To assess landslide susceptibility, a landslide inventory map was prepared using aerial photographs, followed by geomorphometric mapping (altimetry, slopes and geomorphology) and field work. With this information, landslide susceptibility was modeled using multiple logistic regression (MLR) within a GIS platform and the landslide susceptibility map was obtained.