Miracle-dz/UniFAR-FTUs huggingface dataset:
Consensus Model Driven by Interpretable Rules in Large-Scale Group Decision Making With Optimal Allocation of Information Granularity

In group decision making (GDM), consensus level is regarded as a critical criterion to measure the effectiveness and availability of the final group decision solution. Consensus model is aimed at conducting the decision group to reach agreement through the process of group negotiation, advice feedback, and opinion modification, which is time-consuming and rests with the willingness and behavior of individual decision makers. Thus, to guide the shift in the opinions of decision makers within a limited time, it is essential to design an effective, interpretable, and fair consensus mechanism in GDM, which is particularly vital when a mass of decision makers (e.g., more than 30) are involved in the decision process, viz., we encounter a large-scale GDM (LSGDM). With the involvement of information granulation, this study presents a rule-based consensus model in LSGDM by optimally allocating the level of information granularity to each decision maker. The opinions of decision makers in LSGDM are divided into different clusters by engaging the fuzzy $C$ -means method. Inspired by a generic fuzzy rule-based model, the radius of the individual preference granule (PG) is calculated by a weighted linear combination of the granularity levels allocated to the clusters. Then, a consensus model with the optimal allocation of information granularity (CMOIG) is built to determine the granularity level for each cluster by minimizing the sum of radii of individual PG. An interactive consensus reaching process is proposed with the proposed CMOIG and fuzzy modification rules. The CMOIG and fuzzy modification rules simultaneously guarantees high efficiency and interpretability, and the generation method of PGs leads to high fairness due to low discrepancy among the decision group. Finally, numerical and comparative experiments are conducted in detail to verify the validity and superiority of the presented models in terms of the efficiency, interpretability, and fairness.
Effects of Using Technology to Engage Students in Learning English at a Secondary school

In recent years, more and more teachers are applying technology to improve teaching quality and help students learn more actively. This study investigates the impact of technology on engaging students to learn English and explores students' attitudes towards the use of technology in the classroom. This study aims to develop useful suggestions for educators, students, and teachers in secondary schools to engage students in learning English, thereby improving the quality of education. Besides, it encourages teachers to use technology in the classroom to enhance students’ interests. This study was conducted at a Secondary School in Kien Giang province, with 45 students responding to the questionnaire with items about their attitudes towards technology used in the classroom. Additionally, the involvement of 6 English teachers in interviews also helped to deepen the understanding of teachers' beliefs about using technology to attract students to learn English. The findings of the study show that technology had a significant impact on students’ engagement.
Niche differentiation along multiple functional‐trait dimensions contributes to high local diversity of Euphorbiaceae in a tropical tree assemblage

Understanding the mechanisms that drive community assembly in species‐rich tropical forest remains a fundamental challenge in ecology. Here, we integrated multivariate functional trait dimensions, phylogeny and metabolomics to test fundamental predictions concerning the role of differentiation with respect to abiotic and biotic niche axes in the maintenance of high local diversity of woody plants in the Euphorbiaceae. We measured 40 functional traits related to resource acquisition, photosynthetic capacity, hydraulic efficiency and secondary‐metabolite profiles generated using untargeted metabolomics in all 26 Euphorbiaceae species in a 20‐ha forest dynamics plot in tropical southwestern China. We examined the correlation structure of 40 traits using a trait networking approach. We coupled these traits with variation in soil nutrients, light environment, soil water content and herbivore pressure within the plot to assess niche differentiation in space. We compared phylogenetic signal among multivariate trait dimensions and secondary metabolites to assess niche differentiation in evolutionary time. Network analysis revealed that a small number of traits with high network centrality reflected variation in ecological strategy among the Euphorbiaceae. Using these high‐centrality traits, we observed significant functional turnover along environmental gradients defined by light, soil moisture, soil nutrients and leaf herbivory, respectively. Most resource utilization traits showed significant phylogenetic signal, whereas almost all defensive traits lacked phylogenetic signal, including species similarity with respect to plant secondary metabolites. Synthesis. Our results suggest that resource‐utilization traits and the habitat associations play a significant role in the niche segregation of co‐occurring woody plants in the Euphorbiaceae. Secondary metabolites, however, may enhance diversity at a finer spatial scale by allowing closely related species with similar functional traits to partition biotic niche space within shared habitats in tropical rainforest.
An Analysis of Barriers to the Implementation of an ISO Certified Quality Management System for National Meteorological and Hydrological Services in the Anglophone Caribbean

Aeronautical Meteorological Offices under National Meteorological and Hydrological Service provide critical meteorological, hydrological, ocean and climatological information that sustain air navigation safety, efficiency, and regularity. Thus, to quality assure the information, the International Civil Aviation Organization recommended in 2002 that Aeronautical Meteorological Offices should implement ISO 9001 quality management system, which was subsequently standardized and became effective on 15 November 2012. There has been a slow movement towards adoption due to a number of barriers. In July 2019, 52% of Aeronautical Meteorological Offices commenced transition to the fifth iteration, ISO 9001:2015. A range of studies have investigated the barriers to successful quality management system implementation and certification within various organizations. However, only one study examined the Aeronautical Meteorological Offices and none of them covered the Anglophone Caribbean. Hence, the demography of the sample for this study is unique and this paper will contribute to filling the gaps in the literature. This exploratory study aims to identify the barriers, investigate their impacts, and propose recommendations to assist the Aeronautical Meteorological Offices to fully implement the ISO standard. Trinidad and Tobago Meteorological Service was selected as a case study due to its progress in the quality management system implementation and the scope of its operations. The study used and triangulated data collected from secondary sources (desktop research) and primary sources (survey and interviews). Seventeen barriers were identified and formed the new empirical framework for the Aeronautical Meteorological Offices in the Anglophone Caribbean. Most barriers were in the category of resources. The findings have significant implications for the policymakers, especially executive management, to address the barriers that are risks to sustainable quality management system.
The three-dimensional art gallery problem and its solutions

This thesis addressed the three-dimensional Art Gallery Problem (3D-AGP), a version of the art gallery problem, which aims to determine the number of guards required to cover the interior of a pseudo-polyhedron as well as the placement of these guards. This study exclusively focused on the version of the 3D-AGP in which the art gallery is modelled by an orthogonal pseudo-polyhedron, instead of a pseudo-polyhedron. An orthogonal pseudopolyhedron provides a simple yet effective model for an art gallery because of the fact that most real-life buildings and art galleries are largely orthogonal in shape. Thus far, the existing solutions to the 3D-AGP employ mobile guards, in which each mobile guard is allowed to roam over an entire interior face or edge of a simple orthogonal polyhedron. In many realword applications including the monitoring an art gallery, mobile guards are not always adequate. For instance, surveillance cameras are usually installed at fixed locations. The guard placement method proposed in this thesis addresses such limitations. It uses fixedpoint guards inside an orthogonal pseudo-polyhedron. This formulation of the art gallery problem is closer to that of the classical art gallery problem. The use of fixed-point guards also makes our method applicable to wider application areas. Furthermore, unlike the existing solutions which are only applicable to simple orthogonal polyhedra, our solution applies to orthogonal pseudo-polyhedra, which is a super-class of simple orthogonal polyhedron. In this thesis, a general solution to the guard placement problem for 3D-AGP on any orthogonal pseudo-polyhedron has been presented. This method is the first solution known so far to fixed-point guard placement for orthogonal pseudo-polyhedron. Furthermore, it has been shown that the upper bound for the number of fixed-point guards required for covering any orthogonal polyhedron having n vertices is (n3/2), which is the lowest upper bound known so far for the number of fixed-point guards for any orthogonal polyhedron. This thesis also provides a new way to characterise the type of a vertex in any orthogonal pseudo-polyhedron and has conjectured a quantitative relationship between the numbers of vertices with different vertex configurations in any orthogonal pseudo-polyhedron. This conjecture, if proved to be true, will be useful for gaining insight into the structure of any orthogonal pseudo-polyhedron involved in many 3-dimensional computational geometrical problems. Finally the thesis has also described a new method for splitting orthogonal polygon iv using a polyline and a new method for splitting an orthogonal polyhedron using a polyplane. These algorithms are useful in applications such as metal fabrication.
Multi-Order Hypergraph Convolutional Neural Network for Dynamic Social Recommendation System

Recently, online social networks have enriched the users’ lives greatly and social recommendation systems make it easier for users to discover more information that they are interested in. The most advanced graph neural network based social recommendation methods start to utilize the higher-order social relations, e.g. the friends of friends, to reveal users’ preferences. However, existing high-order methods ignore the implicit social relations among users and the users’ interests changing dynamically over time. In this paper, we propose a Multi-Order Hypergraph Convolutional Neural Network (MOHCN) for dynamic social recommendation system to improve the recommendation task, which models the users’ dynamic interest evolution at the session level. To compensate for the lack of social information of some users, we combine the implicit social relations obtained from user-item interaction graph with the explicit social relations from user-user social graph through hypergraph modeling. Extensive experimental results on three real-world datasets demonstrate the effectiveness of our proposed MOHCN compared with the state-of-the-art methods.
Retrofitting Sustainable Urban Drainage Systems (SuDS): A Cost-Benefit Analysis Appraisal

Sustainable Urban Drainage Systems (SuDS) are known to help mitigate flooding whilst simultaneously delivering other positive outcomes, such as the provision of environmental, economic, educational, and business benefits. Despite this, there has been a relatively low uptake of SuDS in new developments and even less of an uptake in the opportunities for retrofitting SuDS in existing buildings. A major barrier to uptake has been a lack of understanding regarding the value of the benefits provided by SuDS. This study presents an appraisal of the costs and benefits derived from the retrofitting of SuDS in existing buildings and reveals some of the key decision-making considerations during the design and installation of such schemes. A qualitative research approach that included a number of case studies of successfully retrofitted SuDS schemes within public buildings was conducted. A novel feature of the research was the use of the Willingness to Pay (WTP) approach to value the tangible and intangible benefits provided by the various schemes from the perspectives of the property owners. The findings revealed that the retrofit provided a net value to the client of over £100,000 over 10 years, a mean CBA ratio of 5.3/10, and a return on investment (ROI) that would be achieved in less than 3 years. The importance of stakeholder engagement during the decision-making process was highlighted in helping to overcome many of the design, installation, and maintenance challenges. The findings demonstrate a significant ROI for these SuDs retrofit schemes and highlight useful approaches to overcoming the barriers in valuing the importance of the intangible benefits. In supporting the uptake of the retrofitting of SuDS, it is recommended that these benefits are given full consideration by property owners, urban planners, and architects during the design of retrofit schemes and throughout the decision-making stage.
A Series-Parallel-Form Switch-Linear Hybrid Envelope Tracking Power Supply With Two Multilevel Converters Sharing a Voltage-Level Provider

Series-parallel-form switch-linear hybrid envelope tracking power supply is composed of a voltage-controlled linear amplifier (VLA), a voltage-controlled switched-mode converter (VSC) and a current-controlled switched-mode converter. When the VLA adopts a class AB linear amplifier, an additional VSC can be added to be in series with the bottom transistor of the VLA to reduce its voltage drop. In order to reduce the system complexity, this article proposes to employ multiple bidirectional converters to implement the voltage-level provider, for being shared by the two VSCs, which are implemented with multilevel converters. Then, the loss model of the system is established, and based on which, an optimized design of the voltage-level number and voltage-level values of the multilevel converters is presented for improving the overall system efficiency. Finally, a prototype is fabricated aiming for tracking the envelope signal with 10-MHz bandwidth, 9.6–26.4-V output voltage, and 20-W average output power. The measured system efficiency is 78.79%, an improvement by 2.58% with the additional VSC.
A 60 GHz Rhombic Patch Array Antenna With High Gain, Low Sidelobe Level, and Reduced Array Area

This work designs a 60 GHz rhombic patch array antenna with high gain, low sidelobe level (SLL), and reduced array area. This antenna consists of eight linear serial arrays with varying number of patches. A slot-coupled center-fed structure of substrate-integrated waveguide (SIW) is designed to simplify the complex feed network required for direct excitation of planar arrays and reduce insertion loss. The rhombic configuration utilizes the quantity ratio of patches for equivalent taper excitation to reduce SLL, rather than the use of tapered width as in traditional designs, which can achieve high gain and avoid cumbersome resizing of patches and connecting lines. An array factor analysis method is proposed to predict the SLL of the antenna. To form a planar array and further reduce the H-plane SLL, a −25-dB Dolph-Chebyshev SIW feed network is constructed. The measured gain of the rhombic array antenna is 18.2 dBi, and the E-plane and H-plane SLLs are less than −20 dB and −25 dB, respectively. This work also simulates a reference uniformly excited high-gain 8 $\times $ 10 array antenna. Compared to this reference antenna, the proposed rhombic array antenna has similar simulated gain but much lower SLL and 23% smaller array area.
Qinbaohong Zhike Oral Liquid Attenuates LPS-Induced Acute Lung Injury in Immature Rats by Inhibiting OLFM4

Acute respiratory infections (ARIs) are a common public safety threat with high morbidity and mortality in pediatric patients worldwide. Qinbaohong Zhike oral liquid (QBH), a marketed traditional Chinese medicine product, has been widely used to cure respiratory diseases. QBH is reported to have antitussive, expectorant, and antiasthmatic properties. However, its treatment effect against ARIs is not elucidated. This study aimed to explore the therapeutic efficacy of QBH in the treatment of ARIs-induced pneumonia. Network pharmacology was used to predict the possible targets of QBH against ARIs. Next, the tracheal lipopolysaccharide (LPS-)-induced acute lung injury (ALI) immature rat model was constructed to evaluate the therapeutic effect of QBH. Tandem mass tag (TMT-)-based quantitative proteomics was then used to screen the in-depth disease targets of QBH. QBH exerted a protective effect against LPS-induced ALI by inhibiting pulmonary pathological damage. QBH also reduced the levels of interleukin (IL)-6, tumor necrosis factor (TNF)-α, interferon (IFN)-γ, and granulocyte macrophage colony-stimulating factor (GM-CSF) in the serum and IL-1β, IL-6, IL-8, TNF-α, IFN-γ, and GM-CSF in the lung tissue. Based on proteomic data, olfactomedin 4 (OLFM4) related to immunity and inflammation was selected as a potential target. Western blot analysis further confirmed the moderating effect of QBH downregulation on OLFM4 in the lung tissue. Our findings demonstrated that QBH alleviated lung tissue damage and inflammatory reaction via inhibiting OLFM4 expression in LPS-challenged immature rats. Our research indicates that QBH may have therapeutic potential for treating ARIs-related ALI in pediatric patients, which also serves as a candidate target for drug therapy of ALI by intervening OLFM-related signaling pathways.
Bloom Filter With Noisy Coding Framework for Multi-Set Membership Testing

This article is on designing a compact data structure for multi-set membership testing that allows fast set querying. Multi-set membership testing is a fundamental operation for computing systems. Most existing schemes for multi-set membership testing are built upon Bloom filter and fall short in either storage space cost or query speed. To address this issue, we propose Noisy Bloom Filter (NBF), Error Corrected Noisy Bloom Filter (NBF-E), and Data-driven Noisy Bloom Filter (NBF-D) in this paper. We optimize their misclassification and false positive rates by theoretical analysis and present criteria for selection between NBF, NBF-E, and NBF-D. The key novelty of the three schemes is to store set ID information in a compact but noisy way that allows fast recording and querying and use a denoising method for querying. Especially, NBF-E incorporates asymmetric error-correcting coding techniques into NBF, and NBF-D encodes set ID basedt membership testing. on their cardinality. To evaluate NBF, NBF-E, and NBF-D in comparison with the prior art, we conducted experiments using real-world network traces. The results show that NBF, NBF-E, and NBF-D significantly advance the state-of-the-art on multi-se
Commuting, working, attending and performing: the changing route to academic attainment andprogression during the first year

Introduction In recent years there have been significant changes in the profile of students entering university. Following the “massification” agenda (Trow, 1973, cited in Morgan, 2012) and the expansion of neo-liberal policies framing higher education (Meuleman et al., 2015), a new type of student has emerged whose university experience is at odds with the going away to university model. Holdsworth (2008) describes a two-tier divide between those who follow the traditional path and can ‘afford to go to university’ (pg. 1849) and those that by necessity stay local.
Improving the robustness of an MPC-based obstacle avoidance algorithm to parametric uncertainty using worst-case scenarios

ABSTRACT Previous work by the authors focused on obstacle avoidance in large, high-speed autonomous ground vehicles within unknown and unstructured environments. This work resulted in a nonlinear model predictive control based algorithm that simultaneously optimises both the speed and steering commands. The algorithm can exploit the dynamic limits of the vehicle to navigate it to a target position as quickly as possible without compromising safety. In the algorithm, a model of the vehicle is used explicitly to predict and optimise future actions, but in practice the model parameter values are not known exactly. Thus, in this paper, the robustness of the algorithm to parametric uncertainty is evaluated. It is first demonstrated that using nominal parameter values in the algorithm leads to safety issues in 24% of the evaluated scenarios with the considered parametric uncertainty distributions. To improve the algorithm's robustness, a novel double-worst-case formulation is developed that simultaneously accounts for the robust satisfaction of the two safety requirements of high-speed obstacle avoidance: collision-free and no-wheel-lift-off. Results from simulations with stratified random scenarios and worst-case scenarios show that the double-worst-case formulation renders the algorithm robust to all uncertainty realisations tested. The trade-off between robustness and the task completion performance is also quantified.
A Differentiable Hydrology Approach for Modeling With Time‐Varying Parameters

In the analysis of observational data with mathematical models, it is often desirable to let one or more model parameters vary with time to account for changing environmental conditions or to offer more flexibility. A standard approach for dynamic models is to allow for the number of parameters to grow as a function of time, leading to a high‐dimensional inference problem for long data records. We propose using Hamiltonian Monte Carlo, a gradient‐based Markov chain Monte Carlo (MCMC) method, to perform Bayesian inference for time‐varying parameters (TVP) in hydrology models. As derivatives of model error functions with regard to parameters are not available in closed form, we implemented the GR4J rainfall‐runoff models in Theano/PyMC3, and Jax/NumPyro, allowing for the application of automatic differentiation techniques. A simulation experiment assessing the viability of these methods for recovering underlying temporal variation in parameters indicates that a discrete Gaussian random walk‐based prior appears to be best suited across a range of scenarios while the continuous‐time Gaussian process compares relatively poorly. In an analysis of 20 years of daily real‐world streamflow records from the Model Parameter Estimation Experiment (MOPEX) hydrology data set with increasing data sparsity and at multiple temporal resolutions, we find that TVP inference with gradient‐based MCMC is a flexible and reliable approach for analyzing hydrology models with dynamic parameter sets.