Miracle-dz/UniFAR-FTUs huggingface dataset:
Empirical Analysis of Government Agricultural Spending and Agricultural Output in Nigeria

This study examined the relationship between government agricultural spending and agricultural output in Nigeria using annual time series data from 1981 to 2019. This study used descriptive and analytical techniques such as descriptive statistics, Augmented Dickey-Fuller test, VEC Granger Causality/Block Exogeneity Wald test, Johansen co-integration test, vector error correction test, impulse response, and variance decomposition. The study found that all variables were not stationary at level but became stationary at first difference. The study also revealed that there is a positive effect of government agricultural spending on agricultural output in Nigeria, though, significant in the long-run only. The study also showed that there is a bidirectional relationship between government agricultural spending and agricultural output in Nigeria at 10% level of significance and that agricultural output would respond positively to shocks in government agricultural spending in Nigeria during the forecast period. Therefore, the study recommends that government expenditure on agriculture should be improved upon the funds allocated to the sector and should be made available to real farmers through the provision of fertilizers, improved seedlings and grant aiding to farmers through farmers cooperatives while farmers in Nigeria should form farmers’ cooperatives to be able to easily access credit facilities from banks as well as Original Research Article Mile et al.; AJEBA, 21(7): 7-23, 2021; Article no.AJEBA. 64631 8 enhancing their easy access to farm inputs provided by the government. More so, the Nigerian government should also increase the budgetary allocation to the agricultural sector to boost food production, alleviate poverty as well as meet up with the international standard.
Informal learning of Cantonese operatic singing in Hong Kong: an autoethnographic study

ABSTRACT A revised abstract is as follows: Cantonese operatic singing is widespread in Hong Kong with numerous amateurs learning in community club settings. However, limited research has been taken on how amateurs learn in the community. This article reports on an autoethnographic study of a community music club catering to Cantonese operatic singing in Hong Kong. The author joined the club for six years as a full member and attended weekly gatherings to identify the features characterising informal learning with participant observations and informal conversations as research methods. Trustworthiness of the study was built on developed rapport with three members and lengthy period of data collection. Influenced by Chinese traditional culture and beliefs, a proactive learning attitude with industry, a competency of self-learning, and the development of positive inter-personal relationships were keys to earning the respect of senior members for access of learning. This study implies a need to balance between informal learning and a systematic pedagogy.
Coordinated Operation of Electricity and Natural Gas Networks with Consideration of Congestion and Demand Response

This work presents a new coordinated operation (CO) framework for electricity and natural gas networks, considering network congestions and demand response. Credit rank (CR) indicator of coupling units is introduced, and gas consumption constraints information of natural gas fired units (NGFUs) is given. Natural gas network operator (GNO) will deliver this information to an electricity network operator (ENO). A major advantage of this operation framework is that no frequent information interaction between GNO and ENO is needed. The entire framework contains two participants and three optimization problems, namely, GNO optimization sub-problem-A, GNO optimization sub-problem-B, and ENO optimization sub-problem. Decision sequence changed from traditional ENO-GNO-ENO to GNO-ENO-GNO in this novel framework. Second-order cone (SOC) relaxation is applied to ENO optimization sub-problem. The original problem is reformulated as a mixed-integer second-order cone programming (MISOCP) problem. For GNO optimization sub-problem, an improved sequential cone programming (SCP) method is applied based on SOC relaxation and the original sub-problem is converted to MISOCP problem. A benchmark 6-node natural gas system and 6-bus electricity system is used to illustrate the effectiveness of the proposed framework. Considering pipeline congestion, CO, with demand response, can reduce the total cost of an electricity network by 1.19%, as compared to −0.48% using traditional decentralized operation with demand response.
Mood Profiling for Sustainable Mental Health among Athletes

Mood responses are a well-established mental health indicator. Gauging mental health status over time often involves periodic mood assessment using a standardized measure, a process referred to as mood profiling. Comparison of observed mood scores against relevant normative data is central to effective mood profiling. The primary purpose of our study was to improve existing norms for the Brunel Mood Scale (BRUMS) using a large internet sample. The secondary purpose was to discuss how mood profiling can be used to promote sustainable mental health primarily among athletes but also with relevance to non-athletes. The BRUMS was completed via the In The Mood website by 15,692 participants. Significant differences between observed mean scores and existing normative data were evident for all six mood dimensions, prompting norm refinement. Specific group norms were generated to address sex differences in mood responses and differences by athlete/nonathlete status. The revised tables of normative data for the BRUMS should be used by researchers in future investigations of mood responses and by applied practitioners seeking to monitor mood responses as an indicator of mental health status. Applications of mood profiling with elite athletes are exemplified, along with recommendations for using mood profiling in the pursuit of sustainable mental health.
An Ignored Culprit of Harmonic Oscillation in LCL-Type Grid-Connected Inverter: Resonant Pole Cancelation

Resonant pole cancelation is usually adopted in the current control or active damping to tackle the filter resonance in the LCL-type grid-connected inverter. However, its potential impact on the system stability has not been adequately assessed. This article provides a comprehensive investigation on three typical control schemes that utilize resonant pole cancelation. An important finding is drawn that the resonant pole cancelation violates the so-called internal stability, which can give rise to the undesired harmonic oscillation in grid current. From the physical insights, it is revealed that the resonant pole cancelation does not essentially eliminate the LCL resonance but merely “hide” it in the system, which can still be triggered and, thereby, turns into the culprit of the harmonic oscillation. The theoretical expectation is validated by the simulation and experimental results.
X-ray Irradiation-Induced Abnormal Development and DNA Damage in Phthorimaea operculella (Lepidoptera: Gelechiidae)

The potato tuber moth, Phthorimaea operculella (Zeller), is a destructive pest of Solanaceous crops. This study investigated the effects of X-ray irradiation on development, DNA damage and recovery in P. operculella. Eggs, larvae (*3rd and 5th), pupae, and adults were irradiated with various doses of X-ray irradiation. Egg hatching was inhibited at 70 Gy, and the pupation and adult emergence of 3rd-instar larvae were inhibited at 150 Gy and 70 Gy, respectively. Some 5th-instar larvae pupated at 150 Gy but failed to emerge as adults at 150 Gy. The adult emergence of pupae that spawned at 150 Gy, but egg hatching of F1 generation was completely inhibited. In addition, the adult emergence of irradiated-pupae was completely inhibited at 200 Gy. Adults spawned at 150 Gy, but the hatching of the F1 generation was completely suppressed. The levels of DNA damage and repair in P. operculella adults were investigated using the alkaline comet assay. The results indicated that X-ray irradiation increased DNA damage in a dose-dependent manner and showed that DNA damage was repaired in a time-dependent manner. However, damage from a high radiation doses was not completely repaired. This result suggests that at least 150 Gy radiation should be used for the control P. operculella.
Tree Canopies Reflect Mycorrhizal Composition

Mycorrhizae alter global patterns of CO2 fertilization, carbon storage, and elemental cycling, yet knowledge of their global distributions is currently limited by the availability of forest inventory data. Here, we show that maps of tree‐mycorrhizal associations (hereafter “mycorrhizal maps”) can be improved by the novel technology of imaging spectroscopy because mycorrhizal signatures propagate up from plant roots to impact forest canopy chemistry. We analyzed measurements from 143 airborne imaging spectroscopy surveys over 112,975 individual trees collected across 13 years. Results show remarkable accuracy in capturing ground truth observations of mycorrhizal associations from canopy signals across disparate landscapes (R2 = 0.92, p < 0.01). Upcoming imaging spectroscopy satellite missions can reveal new insights into landscape‐scale variations in water, nitrogen, phosphorus, carotenoid/anthocyanin, and cellulose/lignin composition. Applied globally, this approach could improve the spatial precision of mycorrhizal distributions by a factor of roughly 104 and facilitate the incorporation of dynamic shifts in forest composition into Earth system models.
A Review on Improved Design Techniques for High Performance Planar Waveguide Slot Arrays

Planar waveguide slot arrays (WSAs) have been used since 1940 and are currently used as performing antennas for high frequencies, especially in applications such as communication and RADAR systems. We present in this work a review of the most typical waveguide slot array configurations proposed in the literature, describing their main limitations and drawbacks along with possible effective countermeasures. Our attention has been focused mainly on the improved available design techniques to obtain high performance WSAs. In particular, the addressed topics have been reported in the following. Partially filled WSAs, or WSAs covered with single or multilayer dielectric slabs, are discussed. The most prominent second-order effects in the planar array feeding network are introduced and accurately modeled. The attention is focused on the T-junction feeding the array, on the effect of interaction between each slot coupler of the feeding network and the radiating slots nearest to this coupler, and on the waveguide bends. All these effects can critically increase the first sidelobes if compared to the ideal case, causing a sensible worsening in the performance of the array.
SUPPLIER SEGMENTATION: A CASE STUDY OF MOZAMBICAN CASSAVA FARMERS

CITATION: Matshabaphala, N. S. & Grobler, J. 2021. Supplier segmentation : a case study of Mozambican cassava farmers. South African Journal of Industrial Engineering, 32(1):196-209, doi:10.7166/32-1-2459.
The Bayesian Confidence Interval for Coefficient of Variation of Zero-inflated Poisson Distribution with Application to Daily COVID-19 Deaths in Thailand

Coronavirus disease 2019 (COVID-19) has spread rapidly throughout the world and has caused millions of deaths. However, the number of daily COVID-19 deaths in Thailand has been low with most daily records showing zero deaths, thereby making them fit a Zero-Inflated Poisson (ZIP) distribution. Herein, confidence intervals for the Coefficient Of Variation (CV) of a ZIP distribution are derived using four methods: the standard bootstrap (SB), percentile bootstrap (PB), Markov Chain Monte Carlo (MCMC), and the Bayesian-based highest posterior density (HPD), for which using the variance of the CV is unnecessary. We applied the methods to both simulated data and data on the number of daily COVID-19 deaths in Thailand. Both sets of results show that the SB, MCMC, and HPD methods performed better than PB for most cases in terms of coverage probability and average length. Overall, the HPD method is recommended for constructing the confidence interval for the CV of a ZIP distribution. Doi: 10.28991/esj-2021-SPER-05 Full Text: PDF
Women in higher education: A brief report on stress during COVID-19

Higher education institutions have evolved into a more stressful environment. Women have been experiencing higher levels of stress than their male counterparts. With higher education adopting to the onset of the pandemic, this brief report studied women’s perceived stress in relation to perceived organizational and supervisory support, and age during times of crisis. In an era of social distancing, quarantines, and lockdowns, the findings suggest that women’s perceived stress is negatively related to age, perceived organizational support, and perceived supervisory support. Society as we once knew it pre-pandemic will never be the same. Higher education is inevitably going to have to manage the aftermath, a new normal that can only be as effective as the employees that help keep the organization running.
Patient and Public Involvement (PPI) in preclinical research: A scoping review protocol

Introduction: Patient and public involvement (PPI) aims to improve the quality, relevance, and appropriateness of research and ensure that it meets the needs and expectations of those affected by particular conditions to the greatest possible degree. The evidence base for the positive impact of PPI on clinical research continues to grow, but the role of PPI in preclinical research (an umbrella term encompassing ‘basic’, ‘fundamental’, ‘translational’ or ‘lab-based’ research) remains limited. As funding bodies and policymakers continue to increase emphasis on the relevance of PPI to preclinical research, it is timely to map the PPI literature to support preclinical researchers involving the public, patients, or other service users in their research. Therefore, the aim of this scoping review is to explore the literature on patient and public involvement in preclinical research from any discipline. Methods: This scoping review will search the literature in Medline (PubMed), Embase, CINAHL, PsycINFO, Web of Science Core Collection, Scopus, and OpenGrey.net to explore the application of PPI in preclinical research. This review will follow the Joanna Briggs Institute (JBI) guidelines for scoping reviews. It will be reported according to the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR). Two reviewers will independently review articles for inclusion in the final review. Data extraction will be guided by the research questions. The PPI advisory panel will then collaboratively identify themes in the extracted data. Discussion: This scoping review will provide a map of current evidence surrounding preclinical PPI, and identify the body of literature on this topic, which has not been comprehensively reviewed to date. Findings will inform ongoing work of the research team, support the work of other preclinical researchers aiming to include PPI in their own research, and identify knowledge and practice gaps. Areas for future research will be identified.
A Review of Usage and Applications of Social Media Analytics

This paper presents the report of a social media analytics (SMA) review. The review conducted to find out the methods and tools used in social media analytics, types of social media platforms which the SMA are performed and the field which SMA has been performed. Social media contains a lot of user uploaded data in different formats like text, images, photos, video etc. These large volumes of data are converted in meaningful information which can be understood using different methods and tools which are called social media analytics. A literature review of articles published between 2010-2020 has been conducted using articles obtained from reputable databases IEEE Xplore, ACM digital, Emerald insight, Springer Link and Science direct. A number of 44 articles have been selected for review from 110 retrieved papers. The paper has been reviewed according to the study objectives. The study found that SMA tools and techniques which have been used are sentiment analysis, youtube analytics, visible intelligence, IBM Watson tool and predictive models. The social media platforms which were mostly used are twitter, facebook, youtube, trip advisor and blogs. SMA has been observed in different fields like agriculture, politics, health, social and business sector.
Topological-Based Measures with Flow Attributes to Identify Critical Links in a Transportation Network

An important part of transportation network vulnerability analysis is identifying critical links where failure may lead to severe consequences, and the potential of such incidents cannot be considered negligible. Existing transportation network vulnerability assessment can be categorized as topological, or traffic based. Topological-based assessment identifies the most critical components in the network by considering network structure and connectivity. Traffic-based assessment identifies the most critical components in the network by full-scan analysis and takes into consideration effects of link failures to traffic flow assignment. The former approach does not consider traffic flow dynamics and fails to capture the non-linearity performance function of transport systems while the latter, even though accurate and robust, requires significant computational power and time and may not always be feasible for real life size networks. The primary objective of this paper is to propose new link criticality measures and evaluate their accuracy for transportation network vulnerability assessment. These measures combine characteristics of traffic equilibrium and network topology to balance accuracy and computational complexity. Nine measures are proposed, and their accuracy is compared with three existing traffic-based measures using three case study transportation networks from the literature. Results indicate that three of the proposed measures show strong correlation to the three traffic-based measures while requiring significantly less computational power and time.
Economic Development Based on a Mathematical Model: An Optimal Solution Method for the Fuel Supply of International Road Transport Activity

Due to globalization and increased market competition, forwarding companies must focus on the optimization of their international transport activities and on cost reduction. The minimization of the amount and cost of fuel results in increased competition and profitability of the companies as well as the reduction of environmental damage. Nowadays, these aspects are particularly important. This research aims to develop a new optimization method for road freight transport costs in order to reduce the fuel costs and determine optimal fueling stations and to calculate the optimal quantity of fuel to refill. The mathematical method developed in this research has two phases. In the first phase the optimal, most cost-effective fuel station is determined based on the potential fuel stations. The specific fuel prices differ per fuel station, and the stations are located at different distances from the main transport way. The method developed in this study supports drivers’ decision-making regarding whether to refuel at a farther but cheaper fuel station or at a nearer but more expensive fuel station based on the more economical choice. Thereafter, it is necessary to determine the optimal fuel volume, i.e., the exact volume required including a safe amount to cover stochastic incidents (e.g., road closures). This aspect of the optimization method supports drivers’ optimal decision-making regarding optimal fuel stations and how much fuel to obtain in order to reduce the fuel cost. Therefore, the application of this new method instead of the recently applied ad-hoc individual decision-making of the drivers results in significant fuel cost savings. A case study confirmed the efficiency of the proposed method.
A Short-Term Intervention to Reduce Stress Levels in Workplace for Office Worker at UEFA—The Union of European Football Associations in Nyon/Switzerland

Background: Today, according to the WHO, workplace stress is particularly common. Several medical and scientific studies have shown that workplace stress can have a serious impact on overall health, a triggering or aggravating factor for many diseases and pathological conditions. This study was conducted to investigate the effects of a stress-reducing eight-week workshop and online messages campaign on office workers. Methods: To collect data of this quasi-experimental study with pre- and post-test, DASS-21 (Depression Anxiety Stress Scale) was used (only part stress; 14 items). For eligible samples, stress-reducing workshops and online messages were held for 8 weeks by a specialist. Data were analyzed using SPSS version 20. Results: Of the 68 participants at the beginning, 43 participants were able to follow up on the 8-week campaign. The drop of participants must be explained by the sudden Covid-19 situation and the postponement of the UEFA EURO 2020 football activities. Overall, 13 of 14 items of stress perception had a decreased score number from pre-test to the post-test results in participants. The test results revealed that there was a significant difference mean of stress score before and after the participants got the campaign with the p-value less than 0.001. The mean difference was 4.18. It meant that after the campaign the mean of the stress score decrease was 4.18. Conclusion: The intervention at the workplace of office employees at UEFA, the United European Football Association, has shown that simple specific lifestyle behaviors, wrapped up in weekly workshops and online messages over a period of eight weeks, significantly reduced stress and stress-related conditions in office employees and improved positive dimensions of mental health and stress-related behavior. This campaign can be applicable to office workers of any type of organization or company.
A computed tomography signs quantization analysis method for pulmonary nodules malignancy grading

In order to improve the accuracy of pulmonary nodules malignancy grading, we propose a method to implement quantitative analysis for lung nodules using computed tomography (CT) signs. Firstly, we construct feature sets of CT signs by combing the radiomics features with the higher‐order features extracted from a convolutional neural network. Secondly, on the basis of the mixed feature set, an evolutionary ensemble learning mechanism is used to generate a classifier to get the quantitative scores for seven lung nodule CT signs. Finally, the scores of seven CT signs are input into a multiclassifier optimized by the differential evolution algorithm to acquire the grade of malignancy. In the experimental study, 2000 lung nodule samples from the LIDC‐IDRI dataset were used to train and test the evolutionary ensemble learner and malignancy classifier. The results show that the recognition accuracy of seven CT signs can reach more than 0.964. Comparison with many typical algorithms, the proposed method not only gets higher accuracy in pulmonary nodules malignancy grading but also can make the result more interpretable.