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The concept of donation crowdfunding has been drawing enormous attention as it connects donors worldwide in a shorter time at a relatively lower cost. This paper aims to integrate two unified theories, namely, behavioral finance and unified theory of acceptance and use of technology model, to investigate on the motivators and deterrents that influence prospective donors to adopt and use donation crowdfunding. The study also substantiates the significance of donors’ behavioral biases through the moderating effect in the crowdfunding adoption process.

The study used survey method for data collection and the data set was obtained from the sample of respondents belonging to India and Bangladesh. The proposed structural equation modeling is tested using SPSS 23.0 and AMOS 23.0.

The study reveals that performance expectancy, effort expectancy, facilitating conditions and trust significantly enhance the intention to adopt donation crowdfunding. Also, biases including overconfidence bias, herding bias and regret aversion bias are found to have significant moderating effects on the relationship between the behavioral intention to adopt donation crowdfunding and use behavior.

By investigating motivators and deterrents of the adoption of donation crowdfunding, the study renders lucrative insights for the donation crowdfunders in devising a donation fundraising campaign that motivates the prospective donors to provide financial contribution.

The study establishes its novelty in explaining the adoption behavior of donation crowdfunding with behavioral bias moderators as a theoretical paradigm. Furthermore, the unified theory of acceptance and use of technology model is extended by introducing, the variable “trust,” while studying the adoption behavior of donation crowdfunding.

The purpose of this paper is to examine how upstream social marketing can benefit from using social media commentary to identify cognitive biases. Using reactions to leading media/news publications/articles related to climate and energy policy in Australia, this paper aims to understand underlying community cognitive biases and their reasonings.

Social listening was used to gather community commentary about climate and energy policy in Australia. This allowed the coding of natural language data to determine underlying cognitive biases inherent in the community. In all, 2,700 Facebook comments were collected from 27 news articles dated between January 2018 and March 2020 using exportcomments.com. Team coding was used to ensure consistency in interpretation.

Nine key cognitive bias were noted, including, pessimism, just-world, confirmation, optimum, curse of knowledge, Dunning–Kruger, self-serving, concision and converge biases. Additionally, the authors report on the interactive nature of these biases. Right-leaning audiences are perceived to be willfully uninformed and motivated by self-interest; centric audiences want solutions based on common-sense for the common good; and left-leaning supporters of progressive climate change policy are typically pessimistic about the future of climate and energy policy in Australia. Impacts of powerful media organization shaping biases are also explored.

Through a greater understanding of the types of cognitive biases, policy-makers are able to better design and execute influential upstream social marketing campaigns.

The study demonstrates that observing cognitive biases through social listening can assist upstream social marketing understand community biases and underlying reasonings towards climate and energy policy.

The US Department of Agriculture (USDA), Soil Conservation Services (SCS) rainfall-runoff model has been applied worldwide since 1954 and adopted by Malaysian government agencies. Malaysia does not have regional specific curve numbers (CN) available for the use in rainfall-runoff modelling, and therefore a SCS-CN practitioner has no option but to adopt its guideline and handbook values which are specific to the US region. The selection of CN to represent a watershed becomes subjective and even inconsistent to represent similar land cover area. In recent decades, hydrologists argue about the accuracy of the predicted runoff results from the model and challenge the validity of the key parameter, initial abstraction ratio coefficient (λ) and the use of CN. Unlike the conventional SCS-CN technique, the proposed calibration methodology in this chapter discarded the use of CN as input to the SCS model and derived statistically significant CN value of a specific region through rainfall-runoff events directly under the guide of inferential statistics. Between July and October of 2004, the derived λ was 0.015, while λ = 0.20 was rejected at alpha = 0.01 level at Melana watershed in Johor, Malaysia. Optimum CN of 88.9 was derived from the 99% confidence interval range from 87.4 to 96.6 at Melana watershed. Residual sum of square (RSS) was reduced by 79% while the runoff model of Nash–Sutcliffe was improved by 233%. The SCS rainfall-runoff model can be calibrated quickly to address urban runoff prediction challenge under rapid land use and land cover changes.

The paper takes a behavioral approach by making use of the prospect theory to unveil the impact of salience on short-term and long-term investment decisions. This paper aims to investigate the group differences for two types of investors’ groups, i.e. individual investors and professional investors.

The study uses partial least square-based structural equation modeling technique, measurement invariance test and multigroup analysis test on a unique data set of 277 active equity traders which included professional money managers and individual investors.

Results showed that salience has a significant positive impact on both short-term and long-term investment decisions. The impact was almost 1.5 times higher for long-term investment decision as compared to short-term decision. Furthermore, multigroup analysis revealed that the two groups (individual investors and professional investors) were statistically significantly different from each other.

The study has implications for financial regulators, money managers and individual investors as it was found that individual investors suffer more with salience heuristic and may end up with sub-optimal portfolios due to inefficient diversification. Thus, investors should be cautious in fully relying on salience and avoid such bias to improve investment returns.

The study concludes with a discussion of policy and regulatory implications on how to minimize salience bias to achieve optimum and diversified portfolios.

The study has significantly contributed to the growing body of applied behavioral research in the discipline of finance.

The purpose of this study is to establish a friction coefficient prediction model using texture parameters and then using the optimal texture parameters to obtain the minimum friction coefficient.

Based on texture technology and the cavitation phenomenon conditions, a test scheme based on two-factor and five-level texture parameters is designed using central composite design and then the response surface methodology and hybrid back-propagation genetic algorithm (BP-GA) models are used to establish a friction coefficient prediction model and optimize the friction coefficient.

The result indicates that the values predicted using two methodologies agree well with the experimental data, but the hybrid BP-GA model is superior to the response surface methodology model in both prediction and optimization.

Two methodologies are used to study the influence of the texture parameters on the friction coefficient under the cavitation condition. It is expected that the result can be used to obtain optimum texture parameters to reduce the friction coefficient.

Maximising real efficiency benefit (REB) is currently being replaced with access to private finance as core public–private partnership (PPP) adoption motive. This later choice focusses on short-term performance, compromising REB and the procurement of infrastructure that meets the need of the present and future generations, which the former accomplishes. The paper aims to review these observed changes to understand the rationales and significance behind such switch.

Secondary data powered exploratory study. Deployed X-inefficiency theory to triangulate and reduce bias and select country cases to provide the proper foundation for the descriptive “what happened?” question, such as “what was the failure concerns with a particular adoption choice?”

The shift to accessing private finance adoption motive against REB failed to improve PPP project performance or meet efficiency and sustainability. Instead, it allows the private sector to assume financial risk without synergistic monitoring from the government to determine their contractual and commitment trust level, which would help achieve the five-dimensional sustainable performance measurement system for PPP. This led to the struggles of PPP projects in Portugal and Spain, where cost overruns and high demand forecast led to project failures. A recommendation, blended finance with its technical assistance additionality, is considered pivotal to addressing access to private finance motive shortcomings.

This study improves best practices for new and existing adopters by systematically establishing that adoption ideology is a cardinal variable that influences PPP project success. When not correctly adopted, it can make the most successful structured projects face complexities and uncertainty.

This study aims to simulate and test the performance of a transmitting and receiving capacitive micro-machined ultrasonic transducer (CMUT). Aimed at detecting demand of the CMUT, a matched integrated adjustment circuit was designed through analyzing processing methods of transducer’s weak echo signal.

Based on the analysis of CMUT array structure and work principle, the CMUT units are designed and the dynamic performance analysis of SIMULINK is given according to the demand of underwater detecting. A transceiver isolation circuit is used to make transmission mode and receiving mode separate. A detection circuit is designed based on the transimpedance amplifier to achieve extraction of high-frequency and weak signal.

Through experimentation, the effectiveness of the CMUT performance simulation and the transceiver integrated adjustment circuit were verified. In addition, the test showed that CMUT with 400 kHz frequency has wider bandwidth and better dynamic characteristics than other similar transducers.

This paper provides a theoretical basis and design reference for the development and application of CMUT technology.

New varieties of paddy are constantly being developed in India in order to sustain yield gains in the face of biotic and abiotic stresses. In this study, the authors attempt to identify the drivers for adoption of new varieties of paddy in India; the authors also estimate the impact on yield of the adoption of new paddy varieties.

Survey data consisted of the reported information from approximately 20,000 paddy farmers in India. The study employs Cragg's double-hurdle model to study the probability and intensity of adoption of new varieties; we use regression discontinuity design to estimate the change in yield due to adoption of new varieties.

The authors’ findings indicate that the adoption of new varieties of paddy in India varies significantly within and between regions; further, the adoption of new varieties is affected by a number of socioeconomic and demographic factors; the authors also find that the adoption of new varieties increases yield significantly.

These are observational data and not based on the experiments. The authors relied on farmers' memory to recall the information.

The authors suggest the formulation of strategic policies that can cater to the needs of regions and states that are lagging behind in the adoption of new paddy varieties.

Recent developments in microwave GaAs technology are yielding devices with higher power capabilities and increased levels of integration. The mechanical and thermal properties of GaAs and other microwave materials play a key role in the design and assembly of microwave power circuits. Thermal management is a critical element of microwave power circuit design. Thermal properties of microwave materials are discussed and compared with standard microelectronic materials. Material selection criteria are described. Assembly and packaging techniques also affect the overall performance of the GaAs power circuit. The high operating frequencies of microwave circuits make ordinary circuit elements, such as wire bonds and printed conductors, reactive. In addition, electrical performance criteria, such as high current or low impedance, create unique assembly demands. The successful development of a GaAs‐based microwave product is dependent on careful attention to the material properties and precise assembly methods. Techniques of automated assembly and processing are discussed, with ah eye towards maintaining high quality and reliability.

This paper aims to focus on the steps necessary to bolster marketability of ISFET‐based sensors, keeping in view the present technological status of ISFET and its limitations.

Technical problems inhibiting commercialization of ISFET‐based sensors are highlighted. The problems considered include sensitivity, drift, cleaning, disposability, reference systems, chip structural designs, packaging, light, temperature, hysteresis and body effects, and instability of biosensors. Available solutions are prescribed, discussing both direct and indirect ways of addressing the problems of ISFET sensors.

The history of progress of ISFET (Ion‐sensitive Field‐Effect Transistor) is synonymous with the ways and means devised by different researchers for surmounting (direct approach) or acclimatizing to the shortcomings of this device (indirect approach). Signal conditioning hardware and software considerably help in obviating issues such as drift, hysteresis and thermal effects.

Reliable on‐chip reference electrodes and ISFET packaging for continuous online applications are interesting research areas.

Where a plausible solution exists, it should be readily availed; otherwise the device limitation should be understood and ingeniously bypassed. Compromising solutions targeted on the specific applications pave the way towards widespread utilization of these sensors in industrial, biomedical, food and environmental sectors.

The study helps in understanding the problems besetting utilization of ISFETs, calling attention to essential remedies for ISFET‐based products. It provides information of value to those involved in ISFET measurements.