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Recognising the growing importance of environmental and sustainable activities and the role of communication strategies in soliciting their financing, this work investigates the influence of message framing, green emphasis and quantitative information on the probability of green crowdfunding campaigns' success.

This analysis is based on crowdfunding campaigns published between 2015 and 2020 on the Indiegogo platform in the category “Community projects – Environment”. The study develops an in-depth qualitative content analysis of the projects before performing an empirical examination to determine funding causes.

Communication strategies (message framing, green emphasis and quantitative goals) affect funding success. However, project category moderates the impact of message framing and green emphasis on campaign success. While positive framing increases agri-food campaign success, negative framing is more effective for clean energy and climate preservation projects. Moreover, indication of a quantitative goal and a marked green emphasis in a project's presentation increase campaign success, but a too marked green emphasis is only effective for agri-food projects.

Green entrepreneurs and campaign managers must work carefully on their projects' communication, accounting for the type of product proposed, emphasising green components in its description and utilising quantitative information to present future goals. These strategies maximise backers' responses and enable entrepreneurs to obtain funding. The authors’ findings may be extended to other contexts, including the banking sector, to craft effective communication strategies for green financial products.

By applying framing theory in a new context (i.e. the online financing of green entrepreneurs), this study identifies new campaign success determinants and provides evidence for the moderating role of project category. Furthermore, the study highlights the need to develop different communication strategies for social and environmental-oriented projects.

The purpose of this paper is to consider the climatic variables and evaluate the role of non-climatic factors that delicately influence agriculture. This study has come across various adaptation strategies such as modification in cultivation practices such as shifting planting dates, water-saving techniques and strategic nutrient management. Meanwhile, we are trying to forget the ground reality that a majority of the farmers are not aware of climate-resilient production technologies. However, farmers modify themselves in this climate change scenario for sustainable production. The practise of these adaptation strategies helps to reduce vulnerability to improve their “socio-economic status” and the “quality of life”.

The present study was attempted to document all the indigenous practices, which are practised by paddy-growers over time for confronting the climate crisis in the Hyderabad-Karnataka region of Karnataka state, India. A cross-sectional and questionnaire-based survey was conducted to collect primary data. The pre-tested interviewing questionnaire consisted of 7 sections with 51 questions. A total of 90 paddy-growing farmers of the region was selected as respondents for the survey. The descriptive statistics was used to analyse the collected data.

In respect of adopted strategies, the vast majority (96.67%) of the farmers had used crops as livestock fodder as they fall back in case of failure, followed by the majority (72.22%) of the selected appropriate varieties. Cent per cent of the farmers adopted the construction of waterways along the slope for safe disposal of rainwater. An overwhelming portion of the farmers adopted levelling of the land in between the bunds (96.67%) and construction of bunds to conserve moisture (95.56%). The majority (76.67%) of the farmers intensified agricultural activities on irrigated land. Nearly half of them (47.78%) paddy growers were practising zero tillage to save time and money.

The current study was carried out in a few districts of Karnataka. Hence, any policy framed based on the outcomes of this study may not conform to the policy specification needs in general to other parts of the country. The farmers did not maintain record books for updating various records. Therefore, the accuracy of data depends on the memory of the respondents. However, the researcher had made every possible effort to make sure that the data collected are the best of the knowledge of the respondents and bear minimal distortions.

The major constraints to applying agricultural adaptation strategies in the study area have been a general lack of knowledge, expertise and data on climate change issues; a lack of specific climate change institutions to take on climate change work and the need for a better institutional framework in which to implement adaptation. Actions to address these gaps include, namely, training programmes for local government officials, dedicated research activities and post-graduate courses and the initiation of specific institutional frameworks for climate change. Furthermore, improving and strengthening human capital, through education, outreach and extension services, improves decision-making capacity at every level and increases the collective capacity to adapt.

Hyderabad-Karnataka is already under pressure from climate stresses, which increases vulnerability to further climate change and reduces adaptive capacity. The adverse effects of climate change have a devastating effect particularly on paddy cultivation, which is the mainstay of most Hyderabad-Karnataka Region. This has affected food production with its resultant effect on widespread poverty. Farmers in the study area have developed traditional agricultural adaptation strategies to cope with climate variability and extreme events. Experience with these strategies needs to be shared among communities.

Though the many literatures were available on the adaptation strategies for climate change this research is one of the few studies to document the farmer led adaptation strategies. This study provides a better understanding of the importance of farmer led adaptation strategies which in turn helps to develop or modify the existing adaptation technologies to cope up with climate change. The authors have come across various adaptation strategies such as modification in cultivation practices such as shifting planting dates, water-saving techniques and strategic nutrient management. Meanwhile, we are trying to forget the ground reality that the majority of the farmers are not aware of climate-resilient production technologies. However, farmers modify themselves in this climate change scenario for sustainable production. The practise of these adaptation strategies helps to reduce vulnerability to improve their “socio-economic status” and the “quality of life”. Therefore, farmer-led adaptation strategies to confront with a change in climate require to be recorded.

In the developing field of nano-materials synthesis, copper oxide nanoparticles (NPs) are deemed to be one of the most significant transition metal oxides because of their intriguing characteristics. Its synthesis employing green chemistry principles has become a key source for next-generation antibiotics attributed to its features such as environmental friendliness, ease of use and affordability. Because they are more environmentally benign, plants have been employed to create metallic NPs. These plant extracts serve as capping, stabilising or hydrolytic agents and enable a regulated synthesis as well.

Organic chemical solvents are harmful and entail intense conditions during nanoparticle synthesis. The copper oxide NPs (CuO-NPs) synthesised by employing the green chemistry principle showed potential antitumor properties. Green synthesised CuO-NPs are regarded to be a strong contender for applications in the pharmacological, biomedical and environmental fields.

The aim of this study is to evaluate the anticancer potential of CuO-NPs plant extracts to isolate and characterise the active anticancer principles as well as to yield more effective, affordable, and safer cancer therapies.

This review article highlights the copper oxide nanoparticle's biomedical applications such as anticancer, antimicrobial, dental and drug delivery properties, future research perspectives and direction are also discussed.

The density peak clustering algorithm (DP) is proposed to identify cluster centers by two parameters, i.e. ρ value (local density) and δ value (the distance between a point and another point with a higher ρ value). According to the center-identifying principle of the DP, the potential cluster centers should have a higher ρ value and a higher δ value than other points. However, this principle may limit the DP from identifying some categories with multi-centers or the centers in lower-density regions. In addition, the improper assignment strategy of the DP could cause a wrong assignment result for the non-center points. This paper aims to address the aforementioned issues and improve the clustering performance of the DP.

First, to identify as many potential cluster centers as possible, the authors construct a point-domain by introducing the pinhole imaging strategy to extend the searching range of the potential cluster centers. Second, they design different novel calculation methods for calculating the domain distance, point-domain density and domain similarity. Third, they adopt domain similarity to achieve the domain merging process and optimize the final clustering results.

The experimental results on analyzing 12 synthetic data sets and 12 real-world data sets show that two-stage density peak clustering based on multi-strategy optimization (TMsDP) outperforms the DP and other state-of-the-art algorithms.

The authors propose a novel DP-based clustering method, i.e. TMsDP, and transform the relationship between points into that between domains to ultimately further optimize the clustering performance of the DP.

Household food insecurity and poor well-being have increased during the coronavirus disease 2019 (COVID-19) pandemic and resulting lockdown measures. Home food growing has been associated with improved food access and well-being, but it is unknown what role it plays during food supply crises and lockdown. It is also unclear how home food growing and social restrictions may affect opinions about growing food in urban areas (i.e. urban agriculture; UA).

A cross-sectional online survey was conducted during the UK national lockdown in March-April 2020 to measure home food growing, perceived food insecurity, well-being, and opinions of UA. The participants were 477 UK-based adults (369 female, mean age 39.57 years ± 13.36); 152 participants were engaged in home food growing prior to the pandemic. Responses were compared to data collected from a separate sample of participants before the pandemic (N=583) to explore potential shifts in opinions about UA.

Participants who engaged in home food growing had lower levels of food insecurity (U_­=19894.50, z=−3.649, p<0.001, r=−0.167) and higher well-being (U=19566.50, z=−3.666, p<0.001, r=−0.168) than those not engaged in home food growing. Perceived food insecurity partially mediated the relationship between home food growing and well-being; home food growing was associated with less food insecurity, which in turn was associated with better well-being. There were no differences in opinions of UA compared to the sample of participants from before the pandemic.

Home food growing may have had a protective effect over perceived food security and well-being in the early stages the pandemic. Opinions of UA were positive and unchanged compared to data collected pre-pandemic. Policies that support home food growing and access to suitable growing spaces and resources may be beneficial for food system resilience and well-being.

The present study aims to construct ensemble machine learning (EML) algorithms for groundwater potentiality mapping (GPM) in the Teesta River basin of Bangladesh, including random forest (RF) and random subspace (RSS).

The RF and RSS models have been implemented for integrating 14 selected groundwater condition parametres with groundwater inventories for generating GPMs. The GPM were then validated using the empirical and bionormal receiver operating characteristics (ROC) curve.

The very high (831–1200 km²) and high groundwater potential areas (521–680 km²) were predicted using EML algorithms. The RSS (AUC-0.892) model outperformed RF model based on ROC's area under curve (AUC).

Two new EML models have been constructed for GPM. These findings will aid in proposing sustainable water resource management plans.