Miracle-dz/UniFAR-FTUs huggingface dataset:
Bayes Linear Strategies for the Approximation of Complex Numerical Calculations Arising in Sequential Design and Physical Modelling Problems.

In a range of different scientific fields, deterministic calculations for which there is no analytic solution must be approximated numerically. The use of numerical approximations is necessary, but introduces a discrepancy between the true solution and the numerical solution that is generated. Bayesian methods are used to account for uncertainties introduced through numerical approximation in a variety of situations. \\ To solve problems in Bayesian sequential experimental design, a sequence of complex integration and optimisation steps must be performed; for most problems, these calculations have no closed-form solution. An approximating framework is developed which tracks numerical uncertainty about the result of each calculation through each step of the design procedure. This framework is illustrated through application to a simple linear model, and to a more complex problem in atmospheric dispersion modelling. The approximating framework is also adapted to allow for the situation where beliefs about a model may change at certain points in the future. \\ Where ordinary or partial differential equation (ODE or PDE) systems are used to represent a real-world system, it is rare that these can be solved directly. A wide variety of different approximation strategies have been developed for such problems; the approximate solution that is generated will differ from the true solution in some unknown way. A Bayesian framework which accounts for the uncertainty induced through numerical approximation is developed, and Bayes linear graphical analysis is used to efficiently update beliefs about model components using observations on the real system. In the ODE case, the framework is illustrated through application to a Lagrangian mechanical model for the interaction between a set of ringing bells and the tower in which they are hung; in the PDE case, the framework is illustrated through application to the heat equation in one spatial dimension.
Diversity and foraging behaviour of insect pollinators in Cauliflower

Cauliflower is a cross-pollinated crop and honey bees play an important role in its pollination. In the current study, we studied we studied diversity and foraging behavior of floral visitors to floral visitors along with their visitation rate, frequency during 2019 and 2020. The data were collected at 0800–1000 hours (early morning foraging activity), 1000-1200 hours (late morning foraging activity), 1200-1400 hours (Noon foraging activity) and 1400-1600 hours (afternoon foraging activity). The results revealed that seven species of bees, five flies and three wasp species on the flowers of cauliflower. Apis mellifera, Apis dorsata and Apis florea were the dominant pollinator species with 162-214, 126-164, and 82-136 individuals, respectively in both years. The maximum foraging activity of the dominant pollinators was observed at 14:00 hrs followed by 12:00 hrs whereas the minimum foraging activity was recorded in the early morning hours 08:00. Floral visitors differed significantly in term of visitation frequency with A. mellifera as the most frequent visitor (14.00–15.37 visits/flower/5 min) followed by A. dorsata (7.50–8.90 visits/flower/5 min) and A. florea (9.80–10.63 visits/ flower/5 min) in both years. Similarly, A. mellifera had statistically highest visitation rate (26.93–27.40 flowers visited/min) followed by A. dorsata (12.62–15.13 flowers visited/min) and A. florea (15.93-16.00 flowers visited/min). The results suggested A. mellifera, A. dorsata and A. florea could be effective pollinators of cauliflower. Therefore, these three species can be effectively used on a commercial scale to increase crop yield.
Intrinsic vacancy in 2D defective semiconductor In2S3 for artificial photonic nociceptor

It is crucial to develop an advanced artificially intelligent optoelectronic information system that accurately simulates photonic nociceptors like the activation process of a human visual nociceptive pathway. Visible light reaches the retina for human visual perception, but its excessive exposure can damage nearby tissues. However, there are relatively few reports on visible light–triggered nociceptors. Here, we introduce a two-dimensional natural defective III–VI semiconductor β-In2S3 and utilize its broad spectral response, including visible light brought by intrinsic defects, for visible light–triggered artificial photonic nociceptors. The response mode of the device, under visible light excitation, is very similar to that of the human eye. It perfectly reproduces the pain perception characteristics of the human visual system, such as ‘threshold,’ ‘relaxation,’ ‘no adaptation’, and ‘sensitization’. Its working principle is attributed to the mechanism of charge trapping associated with the intrinsic vacancies in In2S3 nanosheets. This work provides an attractive material system (intrinsic defective semiconductors) for broadband artificial photonic nociceptors.
Approximation Algorithms for Single-Minded Pricing and Unique Coverage on Graphs and Geometric Objects

In this thesis we study the Single-Minded Pricing, Unique Coverage, and Uniform-Budget SingleMinded Pricing problems on graphs and on geometric objects. In Single Minded Pricing, we are given a set U of items and a collection D of subsets of U , called demands. For each demand d ∈ D, we are also given a budget B(d) ∈ R. If each item u ∈ U is priced at p(u) ∈ R, the revenue from demand d ∈ D will be ∑
Potential vorticity redistribution by localised transient forcing in the shallow-water model

This study is motivated by the need to develop stochastic parameterisations for representing the effects of mesoscale oceanic eddies in non-eddy-resolving and eddy-permitting ocean circulation models. A necessary logical step on the way to such parameterisations is the understanding of flow responses to spatially stationary and localised, time-dependent ‘plunger’ forcings intended to represent transient eddy flux divergences. Specifically, this study develops an understanding of the plunger-induced convergence of potential vorticity (PV) fluxes using the linearised single-layer shallow-water model. Time-periodic solutions are obtained and the ‘footprint’, defined as the time-mean, quasi-linear PV flux convergence, quantifies the cumulative PV redistribution induced by the plunger. Using the footprint, the equivalent eddy flux (EEF) is defined such that it succinctly quantifies the extent of the PV redistribution, and its dependencies on the forcing latitude and the background flow are examined in detail. For a uniform background flow the EEF is positive for all forcing latitudes, corresponding to net-poleward PV flux convergence, as expected by current theory of $\unicode[STIX]{x1D6FD}$ -plane Rossby waves. The EEF also has a robust dependence on the direction and magnitude of a uniform background flow, which is a useful quality for the EEF to provide a basis for a parameterisation of eddy PV fluxes. We also examine the PV redistribution due to forcing on top of a Gaussian jet background flow and find that forcing proximity to the jet core is the primary factor in determining whether the jet is sharpened or broadened.
Enhanced Prepare2Excel: Its Effect on the Board Licensure Examination for Professional Teachers Reviewees

This study tested the effectiveness of the college-developed online review facility, Prepare2Excel. Primarily, it purported to provide enhanced learning-tool both for Board Licensure Examination for Professional Teachers (BLEPT) reviewers and facilitators; customize review programs based on the current reviewers’ needs; extend the reach of the review facilities beyond RSU premises; and achieve 100% rate of BLEPT passers. Reviewers’ scores in diagnostic, pre-board, and actual BLEPT test results were compared. The intervention was done through a series of sessions, and participants took the tests at the scheduled time as set by the college. Paired sample t-test was employed to test for significant differences between the three conditions. Interview was also conducted to supplement the quantitative data gathered. Based on the findings, the intervention was found to be helpful for the participants’ performance in BLEPT. With that, it is highly recommended for the BLEPT takers for the succeeding years. Most importantly, since this is technology-based, it is expected that data from each phase of the program can be secured well and organized for future reference, hence an ideal way for an effective data management system, which includes database management systems, data warehouses, data integration tools, analytics, and more.
Mammogram classification scheme using 2D-discrete wavelet and local binary pattern for detection of breast cancer

In this paper, we propose a new mammogram classification scheme to classify the breast tissues as normal or abnormal. Feature matrix is generated using Local Binary Pattern to all the detailed coefficients from 2D-DWT of the region of interest (ROI) of a mammogram. Feature selection is done by selecting the relevant features that affect the classification. Feature selection is used to reduce the dimensionality of data and features that are not relevant, in this paper the F-test and Ttest will be performed to the results of the feature extraction dataset to reduce and select the relevant feature. The best features are used in a Neural Network classifier for classification. In this research we use MIAS and DDSM database. In addition to the suggested scheme, the competent schemes are also simulated for comparative analysis. It is observed that the proposed scheme has a better say with respect to accuracy, specificity and sensitivity. Based on experiments, the performance of the proposed scheme can produce high accuracy that is 92.71%, while the lowest accuracy obtained is 77.08%.
A Generalized Circuit Model Development Approach With Short Open Thru (SOT) De-Embedding Technique and Its Applications

A short-open-thru (SOT) numerical de-embedding technique is proposed and studied in this work. In particular, a generalized methodology for circuit model development is derived for the extraction of accurate circuit parameters over a wide range of frequency. The entire de-embedding process is described, and the circuit model development strategy is explained step-by-step. A variety of electrically small planar circuit elements, such as microstrip line (MSL) gap discontinuities, step discontinuities, and via-holes in two-layered substrate discontinuities, are numerically de-embedded and extracted conventional circuit model parameters are compared with results generated by a recently published short-open-load (SOL) technique. In addition, the circuit parameters extracted by the proposed generalized decomposition technique are comparatively studied through both SOT and SOL methods. The outcomes confirm that the circuit parameters extracted by the proposed circuit model has better model behavior over a wide range of frequency as opposed to those coming out of its conventional counterpart. Furthermore, the SOT technique-based circuit parametrization provides better stability as compared to the SOL scheme. Numerical convergence over a wide range of frequency is demonstrated for each example. Finally, a third-order Chebyshev end-coupled filter is designed by the proposed technique. Its equivalent circuit model, full-wave electromagnetic (EM) $S$ -parameters simulation, and measured results have validated the approach.
Acceptance of WhatsApp social media platform for learning in Nigeria: A test of unified theory of acceptance and use of technology

The study tested the efficacy of unified theory of acceptance and use of technology (UTAUT) for explaining the rationale for the acceptance of WhatsApp social media platform for learning among students of public and private universities in Nigeria. To achieve the goal of the study, a cross-sectional survey research method was employed. A questionnaire was deployed for data collection. The sample for the study was drawn from undergraduate students from two different universities. The data gathered for the study was subjected to structural equation modeling analysis using AMOS statistical package. Prior to that, series of analysis, such as descriptive analysis, (mean and standard deviation), inferential analysis such as factor analysis to ascertain the dimensionality of the factor of the study was computed. The study also established construct, content, discriminant and convergent validity. It also determined the internal consistency of all the variables of the study. All hypotheses generated for the study was analyzed by checking the effect size of the independent on the dependent variable of the study. The findings from the model of the study showed that the data fit the model of the study. The total variance explained of the model was 61% and almost all the independent variables statistically and directly influence acceptance process of WhatsApp media for learning with exception of effort expectancy that showed a negative effect on student behavioral intention towards use of WhatsApp for learning. The findings of the study have implication for students, teachers and administrators of higher institution of learning Furthermore, the finding of the study equally provide evident for the empirical strength of UTAUT for explaining rationale for adoption of social media for teaching 21st century learners.
Comparative Analysis on the Performance of Block Matching Motion Estimation Algorithm

: The essential requirement of multimedia communication is to achieve high processing speed and a low Computing time simultaneously without loses in video quality. So, the video compression has become an Important for efficient storage and transmission of digital signal in multimedia. It involves video coding exploits the high temporal correlation between successive frames to improve coding efficiency, which is usually achieved by using motion estimation (ME) and motion compensation techniques. Block Matching Motion Estimation is one of the ME technique that has been widely used in various video coding standard. Here this paper presents comparative study of four block matching motion estimation algorithms, namely Exhaustive Search (ES), New Three Step Search (NTSS), Four Step Search (4SS) and Diamond Search (DS) algorithms. All four algorithms are compared based on average number of search points per macro block and their PSNR performance.
Isotopic Tracing of Nucleotide Sugar Metabolism in Human Pluripotent Stem Cells

Metabolism not only produces energy necessary for the cell but is also a key regulator of several cellular functions, including pluripotency and self-renewal. Nucleotide sugars (NSs) are activated sugars that link glucose metabolism with cellular functions via protein N-glycosylation and O-GlcNAcylation. Thus, understanding how different metabolic pathways converge in the synthesis of NSs is critical to explore new opportunities for metabolic interference and modulation of stem cell functions. Tracer-based metabolomics is suited for this challenge, however chemically-defined, customizable media for stem cell culture in which nutrients can be replaced with isotopically labeled analogs are scarcely available. Here, we established a customizable flux-conditioned E8 (FC-E8) medium that enables stem cell culture with stable isotopes for metabolic tracing, and a dedicated liquid chromatography mass-spectrometry (LC-MS/MS) method targeting metabolic pathways converging in NS biosynthesis. By 13C6-glucose feeding, we successfully traced the time-course of carbon incorporation into NSs directly via glucose, and indirectly via other pathways, such as glycolysis and pentose phosphate pathways, in induced pluripotent stem cells (hiPSCs) and embryonic stem cells. Then, we applied these tools to investigate the NS biosynthesis in hiPSC lines from a patient affected by deficiency of phosphoglucomutase 1 (PGM1), an enzyme regulating the synthesis of the two most abundant NSs, UDP-glucose and UDP-galactose.
Innovative Strategies for Observations in the Arctic Atmospheric Boundary Layer (ISOBAR)—The Hailuoto 2017 Campaign

The aim of the research project “Innovative Strategies for Observations in the Arctic Atmospheric Boundary Layer (ISOBAR)” is to substantially increase the understanding of the stable atmospheric boundary layer (SBL) through a combination of well-established and innovative observation methods as well as by models of different complexity. During three weeks in February 2017, a first field campaign was carried out over the sea ice of the Bothnian Bay in the vicinity of the Finnish island of Hailuoto. Observations were based on ground-based eddy-covariance (EC), automatic weather stations (AWS) and remote-sensing instrumentation as well as more than 150 flight missions by several different Unmanned Aerial Vehicles (UAVs) during mostly stable and very stable boundary layer conditions. The structure of the atmospheric boundary layer (ABL) and above could be resolved at a very high vertical resolution, especially close to the ground, by combining surface-based measurements with UAV observations, i.e., multicopter and fixed-wing profiles up to 200 m agl and 1800 m agl, respectively. Repeated multicopter profiles provided detailed information on the evolution of the SBL, in addition to the continuous SODAR and LIDAR wind measurements. The paper describes the campaign and the potential of the collected data set for future SBL research and focuses on both the UAV operations and the benefits of complementing established measurement methods by UAV measurements to enable SBL observations at an unprecedented spatial and temporal resolution.
WORKING UNDER PRESSURE: HOW ARE HEAD TEACHERS INHIBITED AND CHALLENGED WHILE PURSUING THE HEADSHIP IN SECONDARY SCHOOLS?

This study explored what experiences head teachers had while pursuing secondary school headship when they were inhibited by various pressure groups inside and outside of the school. The study aimed at understanding, describing, and interpreting how do secondary school head teachers manage their headship role, and what are the storied experiences that they had while working as head teachers. The participants of the present study were head teachers (n=13) with a minimum of five years’ headship experience in public sector secondary schools within Sahiwal Division, Province of Punjab, Pakistan. By using of a narrative qualitative inquiry approach, data were collected from participants through semi-structured interviews who were selected purposively. Two main themes were identified after the data were recorded, transcribed and analyzed. The key findings pointed out that the head teachers of Public Secondary Schools continuously faced obstacles from pressure groups during their routine work. These pressure groups comprise of both internal and external pressure groups. The results of the study affirm the need to address these issues to enable the head teachers to work freely to foster quality education in the schools.
Hole Mobility Enhancement Mechanism of Wurtzite GaN/AlN Heterojunction Quantum Well Under Tensile and Compressive Stresses

The hole mobility enhancement mechanism of wurtzite (0001)-oriented gallium nitride (GaN)/AlN heterojunction quantum well (QW) under stress engineering is investigated to overcome the low hole mobility, which is considered to be the fundamental obstacle toward the realization of GaN-based complementary electronics. The hole mobility model is obtained by the six-band stress-dependent ${k} \times {p}$ Hamiltonian and the Kubo–Greenwood formula, taking the scattering rates of acoustic phonon, polar optical phonon, and surface roughness into account. Using these methods, the microscopic relationship between stress and hole mobility can be predicted according to the variation of 2-D valence subband dispersion. We demonstrate that the biaxial tensile stress is not a desirable way in the hole mobility enhancement because a large compressive strain induced by the pseudomorphic GaN/AlN heterointerface has to be overcome. We also find that due to the efficient achievements in both effective mass reduction and hole scattering suppression, the uniaxial compressive stress along the current channel and the uniaxial tensile stress perpendicular to the current channel can increase the hole mobility significantly. Under the combined effect of these two 8 GPa non-exclusive mechanisms, a sevenfold mobility enhancement can be obtained, up to the theoretical value of 190 cm2/Vs at room temperature.
Non-stochastic interval factor method-based FEA for structural stress responses with uncertainty

The goal of this study is to evaluate behavior uncertainties of structures by using interval finite element analysis based on interval factor method as a specific non-stochastic tool. The interval finite element method, i.e., interval FEM, is a finite element method that uses interval parameters in situations where it is not possible to get reliable probabilistic characteristics of the structure. The present method solves the uncertainty problems of a 2D solid structure, in which structural characteristics are assumed to be represented as interval parameters. An interval analysis method using interval factors is applied to obtain the solution. Numerical applications verify the intuitive effectiveness of the present method to investigate structural uncertainties such as displacement and stress without the application of probability theory.