PROTOCOL: Non-pharmacological interventions for older people with a diagnosis of depression: An evidence and gap map.

This is the protocol for an evidence and gap map. The objectives are as follows: To map available randomized control trials, economic evaluations, and systematic reviews that assess the effectiveness and cost-effectiveness of non-pharmacological interventions for older people with a diagnosis of depression and identify any existing gaps in the evidence that can inform future research.

Probabilistic assessment of drought stress vulnerability in grasslands of Xinjiang, China.

In the process of climate warming, drought has increased the vulnerability of ecosystems. Due to the extreme sensitivity of grasslands to drought, grassland drought stress vulnerability assessment has become a current issue to be addressed. First, correlation analysis was used to determine the characteristics of the normalized precipitation evapotranspiration index (SPEI) response of the grassland normalized difference vegetation index (NDVI) to multiscale drought stress (SPEI-1 ~ SPEI-24) in the study area. Then, the response of grassland vegetation to drought stress at different growth periods was modeled using conjugate function analysis. Conditional probabilities were used to explore the probability of NDVI decline to the lower percentile in grasslands under different levels of drought stress (moderate, severe and extreme drought) and to further analyze the differences in drought vulnerability across climate zones and grassland types. Finally, the main influencing factors of drought stress in grassland at different periods were identified. The results of the study showed that the spatial pattern of drought response time of grassland in Xinjiang had obvious seasonality, with an increasing trend from January to March and November to December in the nongrowing season and a decreasing trend from June to October in the growing season. August was the most vulnerable period for grassland drought stress, with the highest probability of grassland loss. When the grasslands experience a certain degree of loss, they develop strategies to mitigate the effects of drought stress, thereby decreasing the probability of falling into the lower percentile. Among them, the highest probability of drought vulnerability was found in semiarid grasslands, as well as in plains grasslands and alpine subalpine grasslands. In addition, the primary drivers of April and August were temperature, whereas for September, the most significant influencing factor was evapotranspiration. The results of the study will not only deepen our understanding of the dynamics of drought stress in grasslands under climate change but also provide a scientific basis for the management of grassland ecosystems in response to drought and the allocation of water in the future.

The response of green finance toward the sustainable environment: the role of renewable energy development and institutional quality.

The problem for developed and developing economies is achieving sustainable development and cleaner production. Income, institutional regulations, institutional quality, and international trade are the primary factors of environmental externalities. This research looks at 29 provinces in China between 2000 and 2020 to determine the effect of green finance, environmental regulations, income, urbanization, and waste management on renewable energy generation. Similarly, the current study uses the CUP-FM and CUP-BC for the empirical estimation. More precisely, the study shows the positive influences of environmental taxes, green finance index, income, urbanization, and waste management in renewable energy investment. However, the different measures of green finance, such as financial depth, financial stability, and financial efficiency, also positively contribute to renewable energy investment. Therefore, it can be considered the best solution to environmental sustainability. However, imperative policy implications are given to attain the peak of renewable energy investment.

Data-Driven Eco-Efficiency Analysis and Improvement in the Logistics Industry in Anhui.

The ecological efficiency (eco-efficiency) of a regional logistics industry (RLI) is widely regarded as a key factor affecting sustainability of economic development, environmental protection, and resources utilization. This study applied a data-driven method to evaluate and increase the eco-efficiency of an RLI. Based on RLI-related data, which were converted into proper dimensionless indices, data envelopment analysis (DEA), which assumes that the decision-making units (DMUs) are in the situation of variable returns to scale, the Banker, Charnes, and Cooper (BCC) model, and Malmquist index model were used to assess the eco-efficiency of the RLI from both static and dynamic viewpoints. Then, a Tobit regression model was built to explore the factors that influence eco-efficiency. The effectiveness of this approach was verified by its application to an example from Anhui Province. This study has theoretical and practical value for the assessment and promotion of the ecological eco-efficiency of the RLI. We believe that our approach offers a powerful tool to assist logistics enterprises and local governments in coordinating the relationship between the RLI economy and the ecological environment, facilitating the drive to carbon neutrality.

Evaluating low-carbon economic peer effects of green finance and ICT for sustainable development: a Chinese perspective.

With the adoption of the United Nations Sustainable Development Goals and the Paris Climate Agreement, ADB's involvement should not be ignored. The Global Environment Facility (GEF) and ADB have teamed up to provide climate change financing for developing countries. Included in this is climate protection finance, the financing method that offers cash to assist the region in achieving ecological responsibility. Using a systematic framework, the researchers in this study examined the rationale for building a cohort result of green management in China in the new phase of the country's development. As part of a multiplicative framework, the long-term correlation between variables is quantified using the dynamic common correlated effect (D-CCE) and interactive fixed effect. According to the findings, renewable energy and green financing are good environmental indicators. Environmental degradation is negatively affected by green governance. Some people are concerned about how to dispose of ICT, yet on the other side, ICT can help cut carbon emissions with new clean technologies. Moreover, the findings show that urbanization and per capita income increase carbon emissions. The results suggest that Chinese officials need to support reducing carbon emissions through the development of ICT infrastructure, green financing, and renewable energy.

Data-driven evaluation and optimization of the sustainable development of the logistics industry: case study of the Yangtze River Delta in China.

In this study, a data-driven way is proposed to evaluate and optimize the sustainable development of the logistics industry (LI). Based on a comprehensive consideration of economic, societal, and environmental factors, an evaluation index system was established for the sustainable development of the logistics industry (LISD). Logistics industry-related data were collected from the Yangtze River Delta (YRD) from 2011 to 2020. The anti-entropy method was used to determine the index weight and process the data. Furthermore, the coupling harmonization degree and barrier degree models were used to analyze the coordinated development of each subsystem and identify key obstacles. Our results indicate that there are significant temporal and spatial differences in the level of LISD in YRD, with Shanghai (score 0.4834) being the best and Anhui (score 0.4553) the worst, showing a wave-like evolution in time. The coupling and coordination states among the subsystems are significantly different, with that of environmental benefits and other subsystems being poor. Moreover, innovation ability and environmental benefits are the main obstacle factors of this system. Based on the results of this study, targeted optimization countermeasures are put forward and evaluation indicators and research methods are suggested, which will provide the government and practitioners decision support, as well as provide theoretical and methodological support for LISD.

Modelling and assessment of plasticizer migration and structure changes in hydrophobic starch-based films.

The structures of starch and starch-based materials determine additives migration from material matrix. Propionylated starch derived from waxy, normal, G50 and G80 starch were selected as the matrix, the amylose effect on plasticizer (triacetin) migration as well as structural changes in hydrophobic starch-based films were discussed. The constant (k1) of first-order rate and initial release rate (V0) of triacetin migration were consistent with the increment of amylose content. Meanwhile, diffusion model disclosed that Fick's second law was apposite to characterize the short-term migration of triacetin, and larger diffusion coefficient (D) values of short- and long-term migration were also found in films with higher amylose content, indicating that amylose-formed structures were in favor of triacetin migration. In comparison of propionylated amylopectin, Van der Waals's interactions between propionylated amylose and triacetin were easier to be weakened with the migration of triacetin, which promoted the decrease of wavenumber of C-O-C, and enlarged the inter-planner spacing of crystalline structures, promoting the formation of amorphous structures and wrinkles and embossments in films with higher amylose content. This work confirmed that regulating the structures of starch were effective to control the migration behavior of additives from starch-based films.