Miracle-dz/UniFAR-FTUs huggingface dataset:
Improving performance of catalysts for water electrolysis: The MnOx case

This Ph.D. thesis presents work on non-noble metal oxide catalysts for the oxygen evolution reaction, OER. This reaction is currently a bottleneck in electrolyzer technologies, which are promising for energy storage purposes. In particular, Polymer Electrolyte Membrane, PEM, cells are attractive for decentralised hydrogen stations. PEM electrolyzers rely on scarce noble metals to achieve high e ciency and durability, which limits the scalability of the technology. Finding new catalysts for OER is therefore a thriving research eld with new materials being reported frequently. However, many of these new reports include little information about stability, which is evaluated solely from short term electrochemical testing. The rst part of this project was therefore dedicated to designing a meaningful stability protocol. Manganese oxide thin lms were prepared with sputter deposition and the stability was evaluated with Electrochemical Quartz Crystal Microbalance measurements combined with Inductively Coupled Plasma Mass Spectrometry. The results showed that a stable electrochemical performance can be achieved, while a constant mass loss is occurring. The proposed protocol can guide future research e orts in evaluating novel materials for the OER. Unfortunately, most non-noble metal based OER catalysts reported to this date work in alkaline solutions, where cheap NiFe electrodes are already utilized in commercial systems. For acidic media, relevant for the acidic membrane in PEM electrolyzers, there is a lack of strategies aimed at designing catalysts without noble metals. It turns out that MnO2 is a stable material in the OER relevant potential range in acid. In this project, MnO2 thin lms were therefore prepared to evaluate their usefulness for PEM electrolyzers. Anodic dissolution of MnO2 was found to be an issue and a strategy is presented for stabilizing the surface. From density functional theory calculations it was found that titanium could segregate to surface sites prone to dissolution. Thus, MnO2 thin lms were modi ed with titanium using a reactive co-sputtering method and tested in acid. The results indicate that the stability could be improved with more
Data-Driven Modelling of Water Table Oscillations for a Porous Aquifer Occasionally Flowing under Pressure

Modelling of shallow porous aquifers in scenarios where boundary conditions change over time can be a difficult task. In particular, this is true when data modelling is pursued, i.e., models are directly constructed by measured data. In fact, data contain not only the information related to the physical phenomenon under investigation, but also the effects of time-varying boundary conditions, which work as a disturbance. This undesired component conditions the training of data-driven models, as they are fitted by models, which can produce predictions diverging from measured data. Here, a very shallow porous aquifer is modelled in terms of its response to water table to precipitation. The aquifer is characterized by the presence of a low permeability silty top layer covering the lower sandy strata, where the aquifer normally flows. Therefore, when the piezometric level increases up to the low permeability layer, the aquifer changes its behavior from phreatic to confined. This determines the changing boundary condition, which makes the response of the aquifer to rain precipitations complex, as it is related to a two-fold condition: confined or phreatic. The aquifer here is investigated by two machine learning approaches, the earlier based on an evolutionary modeling, and the latter based on artificial neural networks. Evolutionary modeling returned explicit equations with a fitness efficiency up to 0.8 for 1 month for predictions and 0.48 for simulations, while neural networks arrived at 0.85 and 0.28, respectively. The aim of this study is to get an explicit model of the response of the piezometric heights of the aquifer to the precipitations, which is useful for planning the use of groundwater resources.
Leader or party? Quantifying and exploring behavioral personalization 1996–2019

It has become almost a truism that parliamentary elections have become more personalized. However, evidence for this proposition among voters is relatively mixed and we lack a quantification of leader inspired voting. Using data from Comparative Study of Electoral Systems (CSES) project and consistent measures of leader and party popularity across 86 parliamentary elections in 31 polities between 1996 and 2019, we break new ground in the study of behavioral personalization in several respects. First, we provide a consistent and longitudinal test of leader inclined voting, separate from party evaluations, in the form of a vote-leader/party favorite alignment index. Our results show 6% of voters align their vote with their favorite leader solely, and one in five voters align their vote primarily with their favorite leader. While significant, more voters align their vote with their favorite party. Second, we find that leader motivated voting is most prevalent among non-partisans, older voters, and in elections where ideological polarization is low. Third, we demonstrate that voters solely motivated by leaders are most likely to switch their votes between elections. Our results have implications for our understanding of leaders’ impact on elections.
Structural relationships among transformational leadership, affective organizational commitment, and job performance: the mediating role of employee engagement

Purpose The purpose of this paper is to investigate the structural relationships among transformational leadership, affective organizational commitment and job performance, as well as the mediating effect of employee engagement on their relationships. Design/methodology/approach To examine the structural relationships among the research variables, structural equation modeling analysis and bootstrap estimates were performed using the data of 600 full-time employees working in Korean private organizations. Findings The results of the data analysis suggest that transformational leadership had a significant impact on employee affective organizational commitment and job performance through employee engagement as a mediator. Specifically, employee engagement partially mediated the mechanism in which transformational leadership affects employee affective organizational commitment, whereas there existed a full mediation of the association between transformational leadership and job performance. Practical implications The study finding suggested that transformational leadership was the key catalyst in both encouraging affective organizational commitment and task performance of employees throughout the mediator, employee engagement. Thus, organizations need to create a safe and positive environment that promotes employee engagement and should offer interventions for leaders to build skill sets of transformational leadership. Originality/value Because previous studies had explored the impacts of transformational leadership on employee positive attitude and job performance separately, there is little known about how these three constructs correlate. By investigating the impacts of transformational leadership on attitude and performance simultaneously in this study, this study expanded to the extant literature by providing better understanding of transformational leadership. Moreover, given that articles on transformational leadership have been limited in the HRD literature, findings of this study can offer trustworthy information for HRD practice and encourage HRD scholars to explore transformational leadership-related research.
Unprepared industry meet pandemic: COVID-19 and the South Africa construction industry

Purpose This paper aims to determine the responses of construction organisations to the Coronavirus (COVID-19) pandemic and its associated lockdown and the impact on the South African construction industry (SACI). Design/methodology/approach The study adopted a quantitative survey with responses sought from 825 contracting organisation’s representatives drawn from the database of the construction industry development board. The data gathered were analysed using percentage, mean item score and one-sample t-test. The reliability of the research instrument was also tested using the Cronbach alpha test. Findings Findings revealed that most construction organisations implemented a complete travel ban and halting all business operations on sites and offices in a bid to curb the spread of the virus. Furthermore, whilst most construction organisations envisage significant disruption in their project delivery, the problem of job losses was regarded as a short, medium and long-term impact of the pandemic. Loss of revenue, a decline in the economy and business interruption are also some of the potential impacts of the COVID-19 pandemic on the SACI. Originality/value The study’s findings give practical insights on the potential impact of the pandemic on the construction industry and the possible approach needed to help cushion the effect on the industry.
SKEW NORMAL AND SKEW STUDENT-T DISTRIBUTIONS ON GARCH(1,1) MODEL

The Generalized AutoRegressive Conditional Heteroskedasticity (GARCH) type models have become important tools in financial application since their ability to estimate the volatility of financial time series data. In the empirical financial literature, the presence of skewness and heavy-tails have impacts on how well the GARCH-type models able to capture the financial market volatility sufficiently. This study estimates the volatility of financial asset returns based on the GARCH(1,1) model assuming Skew Normal and Skew Student-t distributions for the returns errors. The models are applied to daily returns of FTSE100 and IBEX35 stock indices from January 2000 to December 2017. The model parameters are estimated by using the Generalized Reduced Gradient Non-Linear method in Excel’s Solver and also the Adaptive Random Walk Metropolis method implemented in Matlab. The estimation results from fitting the models to real data demonstrate that Excel’s Solver is a promising way for estimating the parameters of the GARCH(1,1) models with non-Normal distribution, indicated by the accuracy of the estimation of Excel’s Solver. The fitting performance of models is evaluated by using log-likelihood ratio test and it indicates that the GARCH(1,1) model with Skew Student-t distribution provides the best fitting, followed by Student-t, Skew-Normal, and Normal distributions.
Extent and distribution of surface soil acidity in the rainfed areas of Ethiopia

The soil acidity level is a key soil characteristic that determines soil nutrient availability, soil microbial activities, and crop growth. This study was carried out to predict the extent and severity of soil acidity based on 109,704 soil pH samples collected from soil laboratories and compiled from various studies. Rainfall, altitude, slope gradient, soil, and land cover were considered to generate multivariate interpolated soil pH surface. The performance of the co–kriging model was found to be satisfactory with a standard error of 0.77, root mean square error of 0.51, and R2 of 0.74. The model estimates showed that 47% of the Country's total area and 45% of the rainfed areas are acidic (pH < 6.5). Out of the total area of the Country, 3.7% (42,264 km2) is found to be extreme to strong acidic (pH < 5.5), 20.7% (236,724 km2) is moderate acidic (5.6 < pH < 6.0), and 22.5% (257,290 km2) is slight acidic (6.0 < pH < 6.5), whereas the respective coverage in the rainfed agricultural areas is found to be 12% (80,732 km2), 18% (120,500 km2), and 14.6% (97,202 km2). As informed by the model results, integrated acid soil management efforts should be given a priority to severe soil acidity areas of western, central, northwestern, and southern parts of the Country. Thus, appropriate integrated land management techniques that enable to reduce soil acidity and halt land degradation should be initiated, informed by the map produced. Regularly updating the extent and distribution of surface and sub‐surface soil acidity is recommended in future studies.
THE ROLE OF TRACHEOTOMY IN WEANING FROM MECHANICAL VENTILATION IN PATIENTS WITH COVID-19

Objective: Significant numbers of COVID-19 patients require invasive mechanical ventilation support during their treatment. Prolonged mechanical ventilation causes a tracheotomy need in some of those patients. The study aimed to assess the possible benefits of tracheotomy in patients with COVID-19 and its effect on clinical outcomes. Material and Method: Six patients with COVID-19 who underwent an open tracheotomy in our institution were retrospectively reviewed. Its effect on the prognosis, the effectiveness of the safety precautions, and personnel protective equipment (PPE) utilization during the tracheotomy procedures was evaluated. Results: Mean intubation period before a tracheotomy was 21 days (range,14-28). All patients were male with a mean age of 62. Five of them died postoperatively. One patient was discharged and decannulated. None of the airway team members were infected after the procedures. Conclusion: Tracheotomy in COVID-19 patients is a safe procedure when appropriate PPE measures are taken. Our data do not support the contribution of tracheotomy to accelerating ventilator weaning in patients with COVID-19.
Parallel computing efficiency of SWAN 40.91

Abstract. Effective and accurate ocean and coastal wave predictions are necessary for engineering, safety and recreational purposes. Refining predictive capabilities is increasingly critical to reduce the uncertainties faced with a changing global wave climatology. Simulating WAves in the Nearshore (SWAN) is a widely used spectral wave modelling tool employed by coastal engineers and scientists, including for operational wave forecasting purposes. Fore- and hindcasts can span hours to decades, and a detailed understanding of the computational efficiencies is required to design optimized operational protocols and hindcast scenarios. To date, there exists limited knowledge on the relationship between the size of a SWAN computational domain and the optimal amount of parallel computational threads/cores required to execute a simulation effectively. To test the scalability, a hindcast cluster of 28 computational threads/cores (1 node) was used to determine the computation efficiencies of a SWAN model configuration for southern Africa. The model extent and resolution emulate the current operational wave forecasting configuration developed by the South African Weather Service (SAWS). We implemented and compared both OpenMP and the Message Passing Interface (MPI) distributing memory architectures. Three sequential simulations (corresponding to typical grid cell numbers) were compared to various permutations of parallel computations using the speed-up ratio, time-saving ratio and efficiency tests. Generally, a computational node configuration of six threads/cores produced the most effective computational set-up based on wave hindcasts of 1-week duration. The use of more than 20 threads/cores resulted in a decrease in speed-up ratio for the smallest computation domain, owing to the increased sub-domain communication times for limited domain sizes.
Using Citizen Science to Track Population Trends in the American Horseshoe Crab (Limulus polyphemus) in Florida

We used citizen science to improve understanding of population trends and behavior in the American horseshoe crab (Limulus polyphemus) along the entire coast of Florida. First, we used 18 years of public sightings data, beginning in 2002, on horseshoe crab mating to determine which spawning locations were used most. Then, a subset of those locations was more rigorously surveyed through the Florida Horseshoe Crab Watch program. Florida Horseshoe Crab Watch, implemented in 2015 by a collaboration between the Florida Fish and Wildlife Conservation Commission (FWC), University of Florida Institute of Food and Agricultural Science (UF/IFAS), University of Florida Department of Biology (UF), and Florida Sea Grant (FSG), uses trained citizen volunteers to survey beaches with high spawning activity. Volunteers count, weigh, measure, and tag horseshoe crabs that are nesting on the shoreline. These data contribute to a nationwide mark–recapture program managed by the United States Fish and Wildlife Service (USFWS) and are used in Florida to inform species management decisions and to increase general understanding of the species. We developed and adapted both phases of the research by implementing modern technology, improving survey design, and expanding geographic coverage. The quality and accuracy of public reports have improved with technological advancements. The quality of the morphological data collected by Florida Horseshoe Crab Watch volunteers was comparable to that of data collected by professional scientists. Our design can serve as a model for programs regardless of region or taxon of interest and when funding is limited but public interest is high.
Psychometric Comparison of the English and Spanish Western-Hemisphere Versions of the Modified Checklist for Autism in Toddlers—Revised

This article has supplementary material on the web site: www.jdbp. org. ABSTRACT: Objectives: Parent-report screening tools for autism spectrum disorder (ASD) are widely used to promote early identification of children with or at risk for ASD. Most screening tools have been developed in English in the United States or United Kingdom; thus, translated versions are needed for use with culturally and linguistically diverse populations. Traditional translation methods include a forward translation, back translation, and review. However, when used in new cultural and linguistic contexts, this “forward-back” approach may have limitations, including differing psychometric properties compared with original instruments. This study presents a psychometric analysis of the forward-back translation methodology of an ASD screening tool. Methods: A retrospective chart review design was used to examine Modified Checklist for Autism in Toddlers—Revised (M-CHAT-R; Robins et al.) records from 2974 toddlers. Data were compared between caregivers who completed the original English M-CHAT-R and caregivers who completed its forward-back “Spanish-Western Hemisphere” translation to compare select psychometric properties of the 2 instruments. Results: Significant differences were observed between the 2 versions, including a higher overall risk score, higher initial screen-positive rate, and increased likelihood of leaving items blank among Spanish-speaking respondents. Conclusion: Traditional translation methods seemed to affect select psychometric properties between translations of the M-CHAT-R. A more rigorous cultural adaptation approach may be necessary to maintain equivalence with the original instrument. Until new rigorous translations are available, it is recommended that language-specific screening tools continue to be used, along with recommended follow-up interviews, to avoid exacerbating existing health disparities.
Facile synthesis of carbo- and heterocycles via Fe(III)-catalyzed alkene hydrofunctionalization

A facile synthesis of carbo- and heterocycles via Fe(III)-catalyzed alkene hydrofunctionalization has been developed. Various alkenes bearing a leaving group could convert to alkyl radicals through hydrogen atom transfer (HAT), and then serve as cyclization dipoles for accessing carbo- and heterocycles. The synthetic utility was further demonstrated by the synthesis of tetracyclic carbocycles from isopregol.
Chemotaxonomic Study of Four Subspecies of Pinus nigra Arn. Grown in Common Garden Based on Essential Oil Composition

The aim of this study was to investigate the chemical diversity of Pinus nigra Arn. essential oils. The research was carried out on the needles collected from eighteen provenances of black pine grown in common garden located in West-Northern Tunisia and belonging to four different subspecies (Pinus nigra subsp. nigra, Pinus nigra subsp. salzmannii, Pinus nigra subsp. pallasiana, and Pinus nigra subsp. laricio). Essential oil yields ranged from 0.19% to 0.68%. The obtained essential oils have been analyzed by GC-FID and GC-MS apparatus. Twenty-three constituents accounting about 98% of total essential oil composition were identified. The essential oil compositions appeared to be very different according to their origin. Thus, five main essential oil chemotypes were identified in Pinus nigra plants: caryophyllene oxide, camphene, ß-caryophyllene, α-amorphene, and germacrene D. The chemotaxonomic value of the essential oil compositions was discussed in relation to the results of the multivariate statistical test, including a detailed survey of the available literature data.
Effect of market information quality, sharing and utilisation on the innovation behaviour of smallholder pig producers

Abstract Although pig farming can accelerate Uganda’s economic development, the value chain is undeveloped with poorly organized informal markets. Buyers take advantage of farmers paying low prices, pointing to the poor quality of pigs and pork. Farmer innovation can remedy this situation by enabling farmers to reduce costs, improve pig productivity and quality of pigs and pork. Leveraging farmer innovation behaviour calls for appropriate agricultural information. However, the effect of market information quality, sharing, and utilization on the innovation behaviour of pig producing farmers is not fully known. This study sought to determine the effect of information quality, sharing, and utilisation on the innovation behaviour of pig producing farmers in Northern Uganda. A cross-section survey of 239 respondents selected through multiple stages of purposive and random sampling was done. Data were analysed by Structural Equation Modeling (SEM). The results show that information quality contributes significantly to innovation behaviour directly (β = 0.247; P < 0.01) as well as indirectly through the partial mediation of information utilization (β = 0.176; 95% CI = 0.040∼0.349). Therefore, interventions that seek to enhance smallholder farmer innovation should provide quality information and support farmers to utilise it.
Soft palate morphology in OSMF patients: Radiographic evaluation

Oral submucous fibrosis (OSMF) is a chronic progressive, scarring disorder of oral cavity, which includes buccal mucosa, tongue, lips, anterior faucial pillars, soft palate, and oropharynx. Changes in soft palate morphology will start even before the OSMF, present itself clinically. These changes can lead to sleep apnea, difficulty in speech, swallowing & respiration. Various radiographs are good diagnostic aid to assess the soft palate and its morphology or any changes in morphology. To evaluate and compare soft palate morphology and dimensions in various stages of OSMF with control by radiographic evaluation. : 60 patients were evaluated and compared for soft palate morphology, its length, width and angle by using lateral cephalogram and Cone beam computed tomography (CBCT). Most common type of soft palate was found to be type 1 (leaf shaped) in both groups as well as by both radiographic techniques. Significant decrease in length and increase in width with increasing grades of OSMF group. As per p value CBCT gave more precise result. As the OSMF progresses soft palate becomes stout and bulky and significant changes occur in soft palate dimensions and are better evaluated by CBCT. As involvement of the soft palate is the earliest change to be noticed, radiographs should be used as one of the diagnostic aids in OSMF patients.