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Elucidating the function of MgO precursors on the adsorptive removal and recovery of water phosphorus
Get PDFUnveiling the power of shared leadership in project realms : a synergy of planning, knowledge, cohesion, and trust
No full textOptimizing tibia implants : comparative study of lattice designs and material performance under gait cycles
Get PDFUnderstanding how older people with mild frailty engage with behaviour change to support their independence : a qualitative study
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An evaluation of the accuracy of existing empirical and semi-empirical methods for predicting the wing mass of large transport aircraft
No full textThis paper investigates and evaluates the accuracy of various empirical and semi-empirical methods for predicting aircraft wing-structure mass. Eight methods were selected and analysed using data from large passenger-transport aircraft. The required technical data variables and specifications associated with these methods of wing-mass estimation were identified. When data were unavailable, sound engineering assumptions and judgments were applied as a last resort. The root mean square percentage error (RMSPE) was employed as the comparative indicator of accuracy to compute the average discrepancy between the predicted and actual wing-mass values. The resulting RMSPE values were 10% for the Kundu method, 13% for the Torenbeek II method, 15% for the Basgall method, and 17% for the Howe and LTH methods. According to the findings, the Kundu and Torenbeek II methods achieved the highest accuracy, with nonsignificant differences in their RMSPE values. Predicted wing mass was within [−12.5%, +11.7%] of the actual wing mass in approximately 62% of the study cases, which is adequate for most conceptual and preliminary aircraft-design purposes. Predictions were within [−22.3%, +20.6%] for about 25% of cases and within [−39.0%, +29.7%] for about 13% of cases. Furthermore, more complex methods did not enhance accuracy, as essential variables for these methods are often unavailable during the early design stage, rendering their inclusion less practical. Based on the collected and analysed data, a new updated formula for estimating aircraft wing mass is introduced. In comparison to the methods previously discussed, the new formula yields a superior overall RMSPE of 11%, significantly improving the accuracy of wing-mass estimation. Specifically, the results show an RMSPE of 6.5% for aircraft with a maximum takeoff mass exceeding 300,000 kg and 13% for those with a maximum takeoff mass below 300,000 kg. The refined method proves effective for wings with an aspect ratio of up to 10, offering reasonable accuracy during the conceptual design phase. However, some discrepancies still arise when this method is applied to unconventional aircraft
Porous carbon nanospheres in situ doped KxFeyOz as novel magnetic nanocatalyst for biodiesel production
No full textWaste frying oils (WFO) are cheap and can be used as feedstocks for biodiesel production. Researchers are striving to develop a cost-effective and green heterogeneous catalyst for the transesterification of WFO to produce biodiesel. In this work, a new magnetic carbon nanospheres catalyst doped with KxFeyOz (K30PMCNS700) was synthesized via template-free hydrothermal carbonization (HTC) of glucose followed by in situ functionalization with Fe3O4 NPs, potassium activation, and calcination. The operating conditions for the transesterification process were optimized by response surface methodology RSM-CCD. It was found that the prepared K30PMCNS700 was thermally stable, possessed a specific surface area of 95.8 m2 g−1, was superparamagnetic with a saturation magnetization of 26.2 emu g−1, and featured a total basicity of 3584 µmol g−1. The new nanocatalyst was used to catalyse the transesterification reaction of WFO to produce biodiesel fuel. The results indicated that K30PMCNS700 converted 98.3 % of WFO into biodiesel in 80 min at 60 °C with a 9:1 MeOH:WFO ratio. The catalyst durability tests confirmed excellent reusability under optimum conditions, achieving 93.4 % WFO conversion and negligible rates of potassium leaching into the biodiesel (i.e. 3.5 µg L-1) at the 5th cycle. The biodiesel production reaction followed pseudo-first order kinetics (k = 0.1044 min−1), with an activation energy and Gibbs free energy of 70.46 and 255.14 kJ mol−1, respectively. A diesel engine running on BD25 blend (25 % biodiesel and 75 % petroleum diesel) consumed less fuel, generated more brake thermal energy, and produced lower gas emissions
Sustainable biowaste-derived carbon aerogel/MXene composite for mercury removal from water
No full textMercury is a major global health concern; it is widespread across all environmental media and it affects all forms of life. There is strong interest in materials that can effectively remove Hg from water. This study investigates a novel and sustainable approach for mercury removal that consist of macroporous aerogel composite derived from rice husk lignin and modified with MXene. The composite developed high specific surface area (320 m2/g) and remarkable potential for Hg2+ removal. Notably, 20 wt.% MXene modification increased the maximum adsorption capacity of the bare sorbent (lignin aerogel) from (82.4 mg Hg2+/g) to 135.8 mg Hg2+/g, which surpasses commercial adsorbents. The composite effectively removed Hg2+ even from tap water spiked with high metal concentrations (10 mg/L). These findings highlight the significance of lignin-MXene aerogels for real-world application in water purification and environmental remediation
An integrative model of perseverative thinking
No full textPeople spend most of their waking hours detached from external stimuli, remembering the past, foreseeing the future, imagining situations in which they did not attend or that have never existed, or, simply, thinking. Such a process is crucial for mental health. A common feature of many mental disorders is recurrent stress-related thoughts, the so-called ‘perseverative thinking’. In this review, we describe how perseverative thinking represents a dysfunctional self-regulatory strategy that maintains and increases the effects of mental suffering and arises from the maladaptive interplay between discrepancy monitoring, strategy selection, executive regulation, and information representation. We further argue that perseverative thinking can change how the mind represents the world through memory updating, resulting in an increased perceived need for regulation of the external and internal inputs. Lastly, we propose a new integrated model incorporating the different features of perseverative thinking, offering a more unified perspective on psychopathology
The classical model of type-token systems compared with items from the standardized project Gutenberg Corpus
No full textWe compare the “classical” equations of type-token systems, namely Zipf’s laws, Heaps’ law and the relationships between their indices, with data selected from the Standardized Project Gutenberg Corpus (SPGC). Selected items all exceed 100,000 word-tokens and are trimmed to 100,000 word-tokens each. With the most egregious anomalies removed, a dataset of 8432 items is examined in terms of the relationships between the Zipf and Heaps’ indices computed using the Maximum Likelihood algorithm. Zipf’s second (size) law indices suggest that the types vs. frequency distribution is log–log convex, with the high and low frequency indices showing weak but significant negative correlation. Under certain circumstances, the classical equations work tolerably well, though the level of agreement depends heavily on the type of literature and the language (Finnish being notably anomalous). The frequency vs. rank characteristics exhibit log–log linearity in the “middle range” (ranks 100–1000), as characterised by the Kolmogorov–Smirnov significance. For most items, the Heaps’ index correlates strongly with the low frequency Zipf index in a manner consistent with classical theory, while the high frequency indices are largely uncorrelated. This is consistent with a simple simulation