This study delves into the evolving landscape of smart city development in Kazakhstan, a domain gaining increasing relevance in the context of urban modernization and digital transformation. The research is anchored in the quest to understand how specific technological factors influence the formation of smart cities within the region. To this end, the study adopts a Spatial Autoregressive Model (SAR) as its core analytical tool, leveraging data on server density, cloud service usage, and electronic invoicing practices across various Kazakhstani cities. The crux of the research revolves around assessing the impact of these selected technological variables on the smart city development process. The SAR model’s application facilitates a nuanced understanding of the spatial dynamics at play, offering insights into how these factors vary in influence across different urban areas. A key finding of this investigation is the significant positive correlation between the adoption of electronic invoicing and smart city development, a result that stands in contrast to the relatively insignificant impact of server density and cloud service usage. The conclusion drawn from these findings underscores the pivotal role of digital administrative processes, particularly electronic invoicing, in driving the smart city agenda in Kazakhstan. This insight not only contributes to the academic discourse on smart cities but also holds practical implications for policymakers and urban planners. It suggests a strategic shift towards prioritizing digital administrative innovations over mere infrastructural or technological upgrades. The study’s outcomes are poised to guide future smart city initiatives in Kazakhstan and offer a reference point for similar emerging economies embarking on their smart city journeys.

Every plant is significantly important in tackling climate change, including Makila (Litsea angulata BI) an endemic wood species found in the forest of Moluccas Provinces. Therefore, this research aimed to examine the role of the Makila plant in tackling climate change by measuring biomass content using constructing an allometric equation. The method used was a destructive sampling, where 40 units of Makila plant at the sampling level were felled, and sorted according to root, stem, branch, rating, and leaf segments. Each segment was weighed both at wet and after drying, followed by a classical assumption test in data processing, and the formulation of an allometric equation. The regression model was examined for normality and suitability in predicting independent variables, ensuring there were no issues with multicollinearity, heteroscedasticity, and autocorrelation. The results yielded a multiple linear regression, namely: Y = −1131.146 + 684.799X₁ + 4.276X₂, where Y is biomass, X₁ is the diameter, and X₂ is the tree height. Based on the results of the t-test: variable X₁ partially affected Y while variable X₂ partially had no effect on Y. The F-test indicated that variables X₁ and X₂ jointly affected Y with R Square: 0.919 or 91.9% and the rest was influenced by other unexplored factors. To simplify biomass prediction and field measurement, a regression equation that used only 1 independent variable, namely tree diameter, was used for the experiment. Allometric equation only used 1 variable, Y = −1,084,626 + 675,090X₁, where X₁ = tree diameter, Y = Total biomass with R = 0.957, and R² = 0.915. Considering the potential for time, cost, and energy savings, as well as ease of measurement in the field, the biomass of young Makila trees was simply predicted by measuring the tree diameter and avoiding the height. This method used the strong relationship between biomass, plant diameter, and height to facilitate the estimation of biomass content accurately by entering the results of field measurements.

[Objective]In order to explore the sustainable food security level in the Yangtze River Economic Belt, ensure food security and sustainable development of agricultural modernization, it is necessary to establish a scientific food security evaluation system to safeguard local food security.[Methods]This paper takes the food system of the Yangtze River Economic Belt in China as the research object, based on the food security research results at home and abroad, based on sustainable development thinking, combined with a new perspective of dynamic equilibrium research: Beginning with food normalcy, a comprehensive analysis of food production, food economy, social development, ecological security, and technical support for sustainable development is presented using the entropy-weighted TOPSIS model to build a food security evaluation system for sustainable development. [Conclusion]After systematic analysis, it is concluded that (1) the average value of food security score of the Yangtze River Economic Belt from 2008 to 2021 is 0.429, and the overall food in the Yangtze River Economic Belt is in general security level (0.400 ≤ Q1 ≤ 0.600), and the overall situation of food security is not optimistic, (2) from the segmentation of the Yangtze River Economic Belt, the high and low level of food security are divided into sections: midstream > downstream > upstream, and each province and city is slowly rising to different degrees. In this way, we propose general countermeasures to ensure local food security from the perspective of sustainable development.

Iran has one of the oldest civilizations in the world, and many elements of today’s urban planning and design have their origins in the country. However, mass country-city migration from the 1960s onwards brought enormous challenges for the country’s main cities in the provision of adequate housing and associated services, resulting in a range of sub-standard housing solutions, particularly in Tehran, the capital city. At the same time, and notably in the past decade, Iran’s main cities have had significant involvement in the smart city movement. The Smart Tehran Program is currently underway, attempting to transition the capital towards a smart city by 2025. This study adopts a qualitative, inductive approach based on secondary sources and interview evidence to explore the current housing problems in Tehran and their relationship with the Smart Tehran Program. It explores how housing has evolved in Tehran and identifies key aspects of the current provision, and then assesses the main components of the Smart Tehran Program and their potential contribution to remedying the housing problems in the city. The article concludes that although housing related issues are at least being raised via the new smart city technology infrastructure, any meaningful change in housing provision is hampered by the over centralized and bureaucratic political system, an out of date planning process, lack of integration of planning and housing initiatives, and the limited scope for real citizen participation.

In order to seek management alternatives for anthracnose caused by the fungus Colletotrichum gloeosporioides in blackberry (Rubus glaucus Benth.), at the Tibaitatá Research Center of the Colombian Agricultural Research Corporation AGROSAVIA (formerly CORPOICA), an experiment was conducted to evaluate the effect of the application of the major elements nitrogen (N), phosphorus (P), potassium (K) and calcium (Ca) on infections of the fungus C. gloeosporioides strain-52. For this purpose, a randomized complete block design was used with an arrangement of treatments in an orthogonal central composite design. To evaluate the relationship of fertilization levels and disease severity, an artificial inoculation was made on thorny blackberry stems using 0.5 cm mycelial discs at a concentration of 9.53 × 104 conidia. Observations consisted of: disease severity (S), incubation period (IP) and rate of development (r). Data analysis was done by the cluster method on the severity variable, a Pearson correlation analysis between variables, as well as a regression to estimate the effect of nutrients applied on the severity of C. gloeosporioides strain-52. The treatments were concentrated in four groups with the ranges (in parentheses) S (15.9% and 91.8%), PI (9 and 15.3) and Tr (0.0254 and 0.0468). A positive and significant correlation was observed between S and r (P < 0.001) and a negative correlation between PI with S and r (P < 0.001). By means of regression analysis, a linear model was generated that showed a reduction in disease severity with increasing N dose and an increase with the levels of P and Ca applied.

The contradiction between the ability of forestry that provides high-quality and abundant forestry products and good ecological services, and the demand for high-quality and diversified forestry products and service in order to meet the people’s rapid growing, has become the main contradiction faced by forestry development in new era. Since the area of forest resources in China is restricted by the expansion space, expanding the effective supply of forestry must mainly depends on the improvement of the quality and structure of forestry resources. Therefore, the focus of promoting forestry development is to comprehensively improve the level of forest management in the new era. Based on the analysis of the causes for the low level of forest management, it is proposed that forestry development in the new era should focus on the positively stimulating and strengthening the human capital development, etc., which come from the current following aspects: innovating forest management theory and model, clarifying the relationship between government and market.