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Post-harvest losses are becoming a huge issue globally and predominantly severe in developing countries. Food losses decrease farm income by 15% for about 480m small-scale farming households. With technology adoption, particularly, Information and Communication Technology (ICT) usage, minimising post-harvest losses will be more effective, because of its ability to build households’ human development by bridging the information gap.

This study empirically examines the impact of ICT usage on post-harvest losses in Nigeria, utilising Wave 4 (2018/2019) of the Living Standards Measurement Studies (LSMS), Integrated Survey on Agriculture (ISA). The study engages the Logit regression and Propensity Score Matching (PSM) to analyse the data.

The findings show that post-harvest losses constitute about 38% of household agricultural production. In addition, it shows that the influence of ICT is statistically significant and positive in reducing post-harvest losses.

It implies that access to mobile phones and the Internet by households helps in developing their human capital through information access, for example, by linking them to the market and enhancing value chain participation. In addition, the implication is that mobile phone and Internet access contribute 1.87% and 2.68%, respectively, to reducing post-harvest losses. The findings suggest that there is a need for the government to improve support mechanisms for ICT usage among farming households.

The study contributes to the society by examining how the well-being of farmers can be improved upon in order to increase their productivity.

The study on the contribution of ICT to post-harvest losses is relatively sparse in the extant literature. Therefore, this study is among the very few to empirically examine the impact of different ICT indicators, using the LSMS-ISA (2019) data and engaging propensity matching, while focusing on the household heads.

Post-harvest losses are becoming a huge issue worldwide and are predominantly severe in developing countries. Seeking ways to control post-harvest losses is important because losses decrease farm income by more than 15% for approximately 480 million small-scale farmers.

The study engaged Wave 4 (2018/2019) of the Living Standards Measurement Studies–Integrated Survey on Agriculture, to examine the impact of soil technology such as fertilisers, herbicides, pesticides and certified crops on post-harvest losses in Nigeria. The study engaged descriptive statistics, logit regression and propensity score matching (PSM) to analyse the data.

The study found that approximately 38% of the household harvest was lost along the value chain. In addition, the results showed that among the indicators of soil technology, crop certification has a significant impact on the reduction of post-harvest losses. The implication is that from the nearest neighbour and kernel-based matching, the use of certified crops by households contributed to 1.62 and 1.36% reduction in post-harvest losses, respectively. In contrast, pesticide, herbicide and fertiliser use had no significant impact on post-harvest losses.

One of the limitations is that this study applied the PSM, the model did not account for endogeneity. Therefore, in examining this concept, further studies should consider applying other impact model such as the difference-in-difference to account for endogeneity.

While previous studies have examined how ICT adoption, storage mechanisms and value chain among others help to minimise post-harvest losses, the aspect of how soil technology can reduce post-harvest losses has been a subject of exclusion in the extant literature. This study empirically examines the impact of soil technology adoption on post-harvest losses in Nigeria.

This paper aims to highlight the corruption mode of village funds in Indonesia and provide recommendations to reduce such crime.

This paper uses Diamond Fraud theory to explain why the mode of corruption continues, using secondary data from journal articles, research reports and websites.

Corruption mode is carried out through fund misuse, cover-up, fictional reports, fictitious activities and projects and budget markup.

Prevention and detection of fraud can be more effective when considering pressure, opportunities, rationalization and individual abilities.

The novelty of this paper is to provide a more comprehensive view of the factors that can lead to fraud or corruption using the Fraud Diamond Theory.

The education of deaf and hard of hearing (d/DHH) students is largely dependent on the preferred mode of communication. Historically, the mode of communication for d/DHH students was determined by society rather than by students and families. This resulted in divisiveness between the Deaf culture and proponents of oral communication. The adoption of IDEA allowed family participation in the decision-making process. Advances in technology increased student access to sound, resulting in more educational placement options. Despite the positive changes, the complex nature of hearing loss and the wide variety in cultural considerations have made it difficult to determine the best approach to deaf education. Thus, educators and providers are left in a conundrum of which version of “traditional” deaf education is best for students.

This study aims to critically evaluate the competitiveness of Transformer-based models in financial forecasting, specifically in the context of stock realized volatility forecasting. It seeks to challenge and extend upon the assertions of Zeng et al. (2023) regarding the purported limitations of these models in handling temporal information in financial time series.

Employing a robust methodological framework, the study systematically compares a range of Transformer models, including first-generation and advanced iterations like Informer, Autoformer, and PatchTST, against benchmark models (HAR, NBEATSx, NHITS, and TimesNet). The evaluation encompasses 80 different stocks, four error metrics, four statistical tests, and three robustness tests designed to reflect diverse market conditions and data availability scenarios.

The research uncovers that while first-generation Transformer models, like TFT, underperform in financial forecasting, second-generation models like Informer, Autoformer, and PatchTST demonstrate remarkable efficacy, especially in scenarios characterized by limited historical data and market volatility. The study also highlights the nuanced performance of these models across different forecasting horizons and error metrics, showcasing their potential as robust tools in financial forecasting, which contradicts the findings of Zeng et al. (2023)

This paper contributes to the financial forecasting literature by providing a comprehensive analysis of the applicability of Transformer-based models in this domain. It offers new insights into the capabilities of these models, especially their adaptability to different market conditions and forecasting requirements, challenging the existing skepticism created by Zeng et al. (2023) about their utility in financial forecasting.

The purpose of this study is to compare the thermal performance of two flow configurations in corrugated plate heat exchanger (CPHE): vertical flow configuration (CPHE_vert.) and diagonal flow configuration (CPHE_diag.). The study aims to determine the differences between these configurations and evaluate their respective thermal performance based on metrics such as heat transfer rates, pressure drop values and flow distribution.

The study compares the thermal performance of two flow arrangements of CPHE using identical geometrical dimensions and test conditions. Computational fluid dynamics (CFD) is employed, and a validated numerical model is used for the investigation. The comparison is based on analyzing the rate of heat transfer and pressure drop data between the two flow arrangements.

The findings indicate that the diagonal flow configuration in CPHEs offers improved flow distribution, enhanced heat transfer performance and lower pressure drop compared to the vertical flow configuration. However, the differences in general in the thermal performance of CPHE_vert. and CPHE_diag. are found to be minimal.

To the best of the author’s knowledge, this study represents the first attempt to investigate the impact of vertical and diagonal flow configurations on the thermal performance of the CPHE.

The case was developed from secondary sources. This descriptive case was classroom tested in undergraduate organizational behavior courses.

The 94th Academy Awards ceremony, which honored movies released in 2021, was held on March 27, 2022, at the Dolby Theater in Hollywood. Prior to Chris Rock announcing the winner in the category of best documentary film, Rock was assaulted on stage by Will Smith. On April 8, 2022, the Academy’s board of governors met to discuss disciplinary actions for Smith’s behavior. The Academy’s board decided to ban Smith from all Academy events for the next 10 years. Theories of individual behaviors and social processes can provide explanations for behaviors of Chris Rock, Will Smith, the producers and the Academy.

This descriptive case is most appropriate for undergraduate-level organizational behavior courses. The primary topics in this case align well with individual behaviors relative to emotional intelligence (EI) and motivation. The secondary topics in this case align well with social processes relative to decision-making, conflict and culture.

This chapter advances understandings of emotion work by examining how “doing gender” and “doing health” are implicated in the pursuit of emotional tranquility. The study examines the role of hair loss in women’s illness narratives of cancer using in-depth interviews with 16 white women in the US Northwest who vary in age, marital status, diagnoses, and treatments. The absence of women’s hair presents an appearance of illness that prevents them from doing femininity, which calls into question their health status because of Western beauty standards. To overcome this barrier, the women use emotion work to manage the effects of their appearance through necessarily co-occurring bodily, cognitive, and expressive strategies (Hochschild, 1979). The required emotion work during women’s hair loss makes explicit the symbolic linking of the healthy body with the feminine body through women’s head hair. Pursuing treatment for cancer is often seen as a “fight” or a “battle” against the disease and the bodily assaults of such treatments, including unwanted visible bodily changes. A substantial body of empirical work has established the complex web of social psychological problems associated with breasts and breast cancer, but less attention has been given to the side effect of hair loss that is common across cancer types and treatments.

The purpose of this study is to compare the prediction models for half-cell potential (HCP) of RCC slabs cathodically protected using pure magnesium anodes and subjected to chloride ingress.The models for HCP using 1,134 data set values based on experimentation are developed and compared using ANFIS, artificial neural network (ANN) and integrated ANN-GA algorithms.

In this study, RCC slabs, 1000 mm × 1000 mm × 100 mm were cast. Five slabs were cast with 3.5% NaCl by weight of cement, and five more were cast without NaCl. The distance of the point under consideration from the anode in the x- and y-axes, temperature, relative humidity and age of the slab in days were the input parameters, while the HCP values with reference to the Standard Calomel Electrode were the output. Experimental values consisting of 80 HCP values per slab per day were collected for 270 days and were averaged for both cases to generate the prediction model.

In this study, the premise and consequent parameters are trained, validated and tested using ANFIS, ANN and by using ANN as fitness function of GA. The MAPE, RMSE and MAE of the ANFIS model were 24.57, 1702.601 and 871.762, respectively. Amongst the ANN algorithms, Levenberg−Marquardt (LM) algorithm outperforms the other methods, with an overall R-value of 0.983. GA with ANN as the objective function proves to be the best means for the development of prediction model.

Based on the original experimental values, the performance of ANFIS, ANN and GA with ANN as objective function provides excellent results.