In most studies on hydroclimatic variability and trend, the notion of change point detection analysis of time series data has not been considered. Understanding the system is crucial for managing water resources sustainably in the future since it denotes a change in the status quo. If this happened, it is difficult to distinguish the time series data’s rising or falling tendencies in various areas when we look at the trend analysis alone. This study’s primary goal was to describe, quantify, and confirm the homogeneity and change point detection of hydroclimatic variables, including mean annual, seasonal, and monthly rainfall, air temperature, and streamflow. The method was employed using the four-homogeneity test, i.e., Pettitt’s test, Buishand’s test, standard normal homogeneity test, and von Neumann ratio test at 5% significance level. In order to choose the homogenous stations, the test outputs were divided into three categories: “useful”, “doubtful”, and “suspect”. The results showed that most of the stations for annual rainfall and air temperature were homogenous. It is found that 68.8% and 56.2% of the air temperature and rainfall stations respectively, were classified as useful. Whereas, the streamflow stations were classified 100% as useful. Overall, the change point detection analyses timings were found at monthly, seasonal, and annual time scales. In the rainfall time series, no annual change points were detected. In the air temperature time series except at Edagahamus station, all stations experienced an increasing change point while the streamflow time series experienced a decreasing change point except at Agulai and Genfel hydro stations. While alterations in streamflow time series without a noticeable change in rainfall time series recommend the change is caused by variables besides rainfall. Most probably the observed abrupt alterations in streamflow could result from alterations in catchment characteristics like the subbasin’s land use and cover. These research findings offered important details on the homogeneity and change point detection of the research area’s air temperature, rainfall, and streamflow necessary for the planers, decision-makers, hydrologists, and engineers for a better water allocation strategy, impact assessment and trend analyses.

This study aims to determine the effects of monosodium glutamate (MSG) dosage on the yield of long beans (Vigna sinensis L.) of the Peleton variety. The use of MSG as a food ingredient has been a topic of debate, but research on its impact on plant growth is still limited, especially regarding long beans. Therefore, this research is important for providing further understanding of the influence of MSG on long beans plants. The study was conducted from July to October 2023 in Mata Air Village, Central Kupang District, Kupang Regency, East Nusa Tenggara Province. The research method used was a Randomized Complete Block Design (RCBD) with 9 treatments and 3 replications. The treatments included: No MSG, MSG at doses of 2.5 g/plant, 5 g/plant, 7.5 g/plant, 10 g/plant, 12.5 g/plant, 15 g/plant, 17.5 g/plant, and 20 g/plant. Parameters observed included flowering age (days), number of pods (pieces), pod length (cm), and pod weight (g). Based on the results and discussion, it can be concluded that MSG application had a significant effect on the number, length, and weight of pods, but had a non-significant effect on flowering age. The treatment of 15 g/plant was identified as the optimal MSG dosage for the plants, resulting in the highest number of pods (16.2), longest pod length (60.4 cm), and highest pod weight (256.4 g/plant). This research is innovative in exploring the potential use of monosodium glutamate (MSG) on long beans plants, particularly the Peleton variety. The focus on MSG application as a growth stimulant is an innovative step that has been less studied previously. The discovery of the optimal MSG dosage (15 g/plant) for achieving the best results provides valuable information for farmers to enhance productivity efficiently, sustainably, and environmentally friendly. Information about MSG’s potential as a plant stimulant can serve as a starting point for more sustainable agricultural strategies aimed at optimizing available resources.

The augmentation of firm performance via customer concentration is particularly indispensable for organizational evolution. Both trade credit financing and financing constraints play pivotal roles in the nexus between customer concentration and performance. This research constructs a moderated mediation model to rigorously investigate the impact of customer concentration on firm performance, positing trade credit financing as the mediating variable and financing constraints as the moderating variable. The relevant hypotheses are evaluated empirically using panel data compiled from listed manufacturing firms in China over the period 2013–2020, yielding 8 firm-year observations. The empirical outcomes denote that customer concentration exerts a positive influence on firm performance, albeit having a negative impact on trade credit financing. Trade credit financing serves as a partial mediator in the relationship between customer concentration and manufacturing firm performance. Financing constraints are found to positively moderate the mediating role of trade credit financing in the relationship between customer concentration and firm performance. This research broadens the understanding of the implications of customer relationships on trade credit financing and performance, thereby enriching the knowledge base for managing a firm’s financing channels more effectively.

In the context of ecological and social challenges in global food systems, this study investigates the potential of agri-food districts to foster balanced territorial development. A multi-step approach to developing sustainable agri-food districts is outlined. How these districts, as integrated systems and meso-level organizational forms, can enhance sustainability through governance is then assessed. This research uses a context-driven analysis pathway involving stakeholder participation and needs identification. The theoretical background, the Italian regulatory framework, and a case study from Lombardy are presented. Needs are identified through participatory approaches and actions are prioritized using desk research and a narrative SWOT analysis combined with key stakeholder discussions (focus group). A total of eighteen needs are identified and categorized into 3 dimensions of sustainability: economic, environmental, and socio-institutional. Findings indicate that agri-food district organization has great potential to help achieve local and regional policy goals in line with the shift to sustainable approaches in the Common Agricultural Policy (CAP). The paper proposes actions to strengthen district capacity-building, focusing on internal governance and sustainable production chains. Additionally, initiatives to attract young people to rural areas and agreements for ecosystem services in agri-food districts are suggested. These actions aim to promote sustainability and competitiveness while addressing challenges related to governance, innovation, branding, demographics, and environment. In conclusion, the study prompts critical inquiry into governance models and system dynamics. The innovative aspects of this study lie in its methodological approach, integration of theory and practice, holistic perspective, policy relevance, and critical inquiry, which collectively contribute to advancing knowledge and understanding in the field of sustainable agriculture and territorial development.

Entrepreneurship education plays a crucial role in improving college students' entrepreneurial skills. With the significant momentum gained by digital entrepreneurship, there is an urgent need for digital transformation in entrepreneurship education. However, entrepreneurship education digital transformation (EEDT) is developing in a rapid but fragmented manner, which requires more systematic guidance. This study aims to assess the current research themes and formulate a framework for entrepreneurship education digital transformation. The research employs a systematic literature review and a theory triangulation method. According to the review’s outcome, which focused on 56 articles published between 2018 and 2023, the researcher constructed a conceptual framework for entrepreneurship education digital transformation. To test the construct validity of the framework, the researcher modified it twice through theory triangulation, following the guidelines of the entrepreneurship education ecosystem theory and the education digital transformation framework. This study offers recommendations for research and practice in digital transformation of entrepreneurship education, encompassing a holistic strategy, new educational approaches, novel curriculum designs, and the enhancement of digital literacy among entrepreneurship teachers.

Surface-enhanced Raman scattering (SERS) spectrum has the characteristics of fast-detection, high-sensitivity and low-requirements for sample pretreatment. It plays a more and more important role in the detection of organic pollutants. In this study, MIL-101 and Au nanoparticles were prepared by hydrothermal method and aqueous solution reduction method respectively, and MIL-101/Au composite nanoparticles were prepared by electrostatic interaction. The SERS properties of the composite substrate were optimized by adjusting the size of Au nanoparticles and the surface distribution density of MIL-101 nanoparticles. The detection limit of Rhodamine 6G (R6G) for the composite substrate with the optimal ratio was investigated, which was as low as 10^–11 M. It is proved that MIL-101/Au composite nanoparticles have high sensitivity to probe molecules. When they are applied to the detection of persistent organic pollutants, the detection limit for fluoranthene can reach 10^–9 M and for 3,3’,4,4’-tetrachlorobiphenyl (PCB-77) can reach 10^–5 M.