A total of 25 SSR primers were screened on 37 putative F₁s derived from the five different crosses. Identified cross specific highly informative SSRs primers, i.e., 14 for the first cross, 10 for the second, 12 for the third and 6 each for fourth and fifth crosses. For the first cross Bhagwa × Daru 17, four primers (HvSSRT_375, NRCP_SSR9, NRCP_SSR12 and NRCP_SSR92) were found to be highly informative with higher 100% hybrid purity index (HPI), PIC (~0.52), and observed heterozygosity (Ho, range 0.87–0.93) values, and two F₁s namely H₁ and H₂ were found to be highly heterotic with a heterozygosity index (HI) of 92.85%. Similarly, for Bhagwa × Nana, three primers (HvSSRT_375, HvSSRT_605 and NRCP_SSR19) had higher HPI (70%–100%), PIC (0.52–0.69), and Ho (0.75–0.33) values, and three F₁s H₁, H₂, and H₄ had 70% (HI). For Bhagwa × IC318712, four SSRs (HvSSRT_254, HvSSRT_348, HvSSRT_826 and NRCP_SSR95) had higher Ho (~0.83), HPI (100%) and PIC (~0.52) values, and four F₁s H₂, H₇, H₉, and H₁₀ showed 91.66% (HI). For Bhagwa × Nayana, HvSSRT_605, HvSSRT_826, and HvSSRT_432, and for Ganesh × Nayana, HVSSRT_375, HVSSRT_605, and HvSSRT_826 were found informative. These markers will be highly useful in developing maps of populations.

The design of effective flood risk mitigation strategies and their subsequent implementation is crucial for sustainable development in mountain areas. The assessment of the dynamic evolution of flood risk is the pillar of any subsequent planning process that is targeted at a reduction of the expected adverse consequences of the hazard impact. This study focuses on riverbed cities, aiming to analyze flood occurrences and their influencing factors. Through an extensive literature review, five key criteria commonly associated with flood events were identified: slope height, distance from rivers, topographic index, and runoff height. Utilizing the network analysis process within Super Decision software, these factors were weighted, and a final flood risk map was generated using the simple weighted sum method. 75% of the data was used for training, and 25% of it was used for testing. Additionally, vegetation changes were assessed using Landsat imagery from 2000 and 2022 and the normalized difference vegetation index (NDVI). The focus of this research is Qirokarzin city as a case study of riverbed cities, situated in Fars province, with Qir city serving as its central hub. Key rivers in Qirokarzin city include the Qara Aghaj River, traversing the plain from north to south; the primary Mubarak Abad River, originating from the east; and the Dutulghaz River, which enters the eastern part of the plain from the southwest of Qir, contributing to plain nourishment during flood events. The innovation of this paper is that along with the objective to produce a reliable delineation of hazard zones, a functional distinction between the loading and the response system (LS and RS, respectively) is made. Results indicate the topographic index as the most influential criterion, delineating Qirokarzin city into five flood risk zones: very low, low, moderate, high, and very high. Notably, a substantial portion of Qirokarzin city (1849.8 square kilometers, 8.54% of the area) falls within high- to very-high flood risk zones. Weighting analysis reveals that the topographic humidity index and runoff height are the most influential criteria, with weights of 0.27 and 0.229, respectively. Conversely, the height criterion carries the least weight at 0.122. Notably, 46.7% of the study area exhibits high flood intensity, potentially attributed to variations in elevation and runoff height. Flood potential findings show that the middle class covers 32.3%, indicating moderate flood risk due to changes in elevation and runoff height. The low-level risk is observed sporadically from the east to the west of the study area, comprising 12.4%. Analysis of vegetation changes revealed a significant decline in forest and pasture cover despite agricultural and horticultural development, exacerbating flood susceptibility. 

Urban areas are increasingly vulnerable to fire disasters due to high population density, sprawling infrastructure, and often inadequate safety measures. This study aims to analyze the capacity of the DKI Jakarta government in terms of human resource capabilities, asset readiness, and budget planning capabilities. Furthermore, it measures the government’s success as evidenced by the public response to the achievement of firefighter performance. This study uses qualitative analysis with a content analysis approach. Data sources come from annual performance report documents and the content of the DKI Jakarta Fire Department website containing city disaster information. Performance report and website data are analyzed and used as research data to support qualitative analysis. This research shows that command decisions are essential in the organizational structure of the fire brigade. Both laboratory services are carried out optimally as a concrete effort to map fire potential. The laboratory tests the safety and suitability of firefighting equipment. Available budgetary support provides broad operational powers for the fire service. The government’s strength in minimizing or overcoming fire problems has received a positive response from the public. The operational achievements of firefighting continue to be consistent and increase. Ultimately, this research provides scientific insight into disaster mitigation and reducing the fire risk in cities.

This study aims to examine the impact of an innovative self-directed professional development (SDPD) model on fostering teachers’ professional development and improving their ability to manage this development independently. A quantitative research method was adopted, involving 60 participants from Almaty State Humanitarian and Pedagogical College No. 2, Almaty, Kazakhstan. Descriptive and inferential statistics were used to assess the SDPD model’s effectiveness, specifically in promoting teacher engagement, adoption of new pedagogical techniques, and improvement in reflective practices. The study findings reveal that teachers, particularly in developing regions, often face challenges in accessing formal professional development programs. The implementation of the SDPD model addresses these barriers by providing teachers with the tools and strategies required for self-improvement, regardless of geographic or economic constraints. The study participants in the pilot phase showed increased engagement with new pedagogical methods, improved reflective practices, and greater adaptability to emerging educational technologies. The algorithmic aspect of the model streamlined the professional development process, while the activity-based approach ensured that learning remained practical and relevant to teachers’ everyday needs. By offering a clear framework for continuous improvement, the model addresses the gaps in formal training access and cultivates a culture of lifelong learning. These findings suggest that the SDPD model can contribute to elevating teaching standards globally, particularly in regions with limited professional development resources.

Under the background of engineering education certification, the traditional personnel training model can’t meet the requirements of high-quality personnel training under the new engineering background. Taking Surveying and mapping engineering major of Liaoning Institute of Science and Technology as an example, this paper explores the continuous improvement of the output-oriented talent training model through collaborative education of talents training objectives, curriculum system, practical teaching system, teacher team construction, enterprises and graduates. Over the years, the surveying and mapping engineering major of our school has achieved good results in personnel training. The major actively ADAPTS to the regional development of the local economy, closely connects with the needs of regional talents, and highlights its characteristics in serving the local economy.

The development of artificial intelligence (AI) and 5G network technology has changed the production and lifestyle of people. AI also has promoted the transformation of talent training mode under the integration of college industry and education. In the context of the current transformation of education, AI and 5G networks are increasingly used in the education industry. This paper optimizes and upgrades the training mode of skilled talents in higher vocational colleges by using its advanced methods and technologies of information display. This means is helpful to analyze and solve a series of objective problems such as the single training form of the current talent training mode. This paper utilizes the principles and laws of industry university research (IUR) collaboration for reference to construct and optimize the talent training mode based on the analysis of the requirements of talent training and the role of each subject in talent training. Then, the ecological talent training environment can be realized. In the analysis of talent training mode under the cooperation of production and education, the correlation coefficients of network construction, environment construction, scientific research funds, scientific research level, and policy support were 0.618, 0.576, 0.493, 0.785, and 0.451, respectively. This showed that the scientific research level had the greatest impact on talent training in the talent training mode of IUR collaboration, while policy support had less impact on talent training compared with other factors. The combination of AI and 5G network technology with the talent training mode of IUR cooperation can effectively analyze the influencing factors and problems of the talent training mode. The hybrid method is of great significance to the talent training strategy and fitting degree.