This study intends to explore the idea of a vocational village strategy to foster sustainable rural development. Vocational villages, offering targeted skills training and economic opportunities, present a compelling soft approach to rural development, addressing the need for sustainable livelihoods and community empowerment. Drawing upon the collaborative governance (the penta-helix model); underpinning the social capital perspective; and highlighting the economic, institutional, cultural, environmental, technological, and institutional dimensions of sustainable development, a vocational village strategy is expected to level up village capacities and facilitate modernization. The research was narratively developed through a qualitative methodology using primary and secondary data sources. Primary empirical data was employed to analyze vocational village practices in Panggungharjo Village, Yogyakarta, Indonesia as a representative example. The PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-analyses) framework provided secondary data to present comparative literature on vocational village development. The findings determined a four-staged vocational village model includes initiation, training, business development, and independence. The success of this model is contingent upon political, bureaucratic, and sociocultural factors (social capital), as well as the effective collaboration of government, academia, industry, and community (penta-helix). This research contributes to the urgency of vocational village practices and models as a viable strategy for achieving equitable and sustainable rural development.

This study aims to examine whether banks are compliant with adopting sustainability regulations and guidelines, and how they disclose their sustainable finance activities in sustainability reporting by providing case of Indonesian banking. Previous research provided discussions on the role of governance in supporting many variables as quantitative studies, but failed to demonstrate on going practices of how banking industries implement sustainable finance governance. Hence, this study provides originality by analyzing the extend of disclosures in order to evaluate their commitments in responding to sustainability regulations and guidelines, through disclosures of economic, environment, social, and governance (EESG) information in annual and sustainability reports. The samples were undertaken by examining the contents of sustainability and annual reports published for the financial year 2016 to 30 June 2021, for the Indonesian banks listed in business category 4, business category 3, and international banks, with the total of 202 reports. The results indicate that the implementation of sustainable finance in EESG information increases annually with social performances are the highest information disclosed, while the governance and economic information received the lowest level of disclosure. Results of this study will benefit policymakers, banks, and related companies to understand sustainable finance governance, and reveal the importance the role of banking industries to support Sustainable Development Goals (SDGs). Providing the insights of the ongoing discussions are expected to suggest following actions for further policies to support the implementation of sustainable finance, in particular to establish sustainability governance as a foundation of commitments, beyond complying to regulations.

Although the problems created by exceeding Earth’s carrying capacity are real, a too-small population also creates problems. The convergence of a nation’s population into small areas (i.e., cities) via processes such as urbanization can accelerate the evolution of a more advanced economy by promoting new divisions of labor and the evolution of new industries. The degree to which population density contributes to this evolution remains unclear. To provide insights into whether an optimal “threshold” population exists, we quantified the relationships between population density and economic development using threshold regression model based on the panel data for 295 Chinese cities from 2007 to 2019. We found that when the population density of the whole city (urban and rural areas combined) exceeded 866 km⁻², the impact of industrial upgrading on the economy decreased; however, when the population density exceeded 15,131 km⁻² in the urban part of the cities, the impact of industrial upgrading increased. Moreover, it appears that different regions in China may have different population density thresholds. Our results provide important insights into urban economic evolution, while also supporting the development of more effective population policies.

English writing is an important output skill cultivated in college English courses. And in the age of informationization, college English writing teaching relies on the support of information technology. In order to cope with the solution of this dilemma, Production-Oriented Approach(POA) proposes Teacher-Student Collaborative Assessment (TSCA), which creates a new form of assessment. Through TSCA, teachers can not only alleviate the heavy teaching load, but also fully tap the network resources to efficiently use students' time before, during and after class to maximize and optimize the teaching effect. In this paper, the teaching concept of TSCA is used to conduct writing teaching experiments, to study and analyze the writing ability of students who write effectively, so as to provide insights for the practice of English writing teaching.

In this study, optical and microwave satellite observations are integrated to estimate soil moisture at the same spatial resolution as the optical sensors (5km here) and applied for drought analysis in the continental United States. A new refined model is proposed to include auxiliary data like soil texture, topography, surface types, accumulated precipitation, in addition to Normalized Difference Vegetation Index (NDVI) and Land Surface Temperature (LST) used in the traditional universal triangle method. It is found the new proposed soil moisture model using accumulated precipitation demonstrated close agreements with the U.S. Drought Monitor (USDM) spatial patterns. Currently, the USDM is providing a weekly map. Recently, “flash” drought concept appears. To obtain drought map on daily basis, LST is derived from microwave observations and downscaled to the same resolution as the thermal infrared LST product and used to fill the gaps due to clouds in optical LST data. With the integrated daily LST available under nearly all weather conditions, daily soil moisture can be estimated at relatively higher spatial resolution than those traditionally derived from passive microwave sensors, thus drought maps based on soil moisture anomalies can be obtained on daily basis and made the flash drought analysis and monitoring become possible.