Miracle-dz/UniFAR-FTUs huggingface dataset:
Higher education choices of secondary school graduates with a Science, Technology, Engineering or Mathematics (STEM) background

Abstract Recently, there has been an increase in the Higher Education (HE) options (in terms of both courses and institutions) available to students in the UK. Given that the choice of institution and field of study are crucial for students’ future careers, we investigated how attributes of the institutions and courses determine students’ choices, and how they interact with student characteristics. Data on graduates with a STEM background, who started a course in 2010/11 in an English HE institution, was analysed using a conditional logit model. The research demonstrated that an institution’s prestige, degree subject area and distance from home play an important role in students’ choices. Furthermore, distance from home to the HE institution is a potential barrier to fair access, as socio-economically deprived students may have less choice if they are not able to travel as far.
Practical Tests for Comparing Two Proportions with Incomplete Data

Six simple procedures and the likelihood ratio criterion for testing the equality of two binomial proportions with partially incomplete paired data are examined using Monte Carlo methods. The results suggest that the size of each test is more or less satisfactory for nominal sample sizes. Tests which discard some of the observations are seen to have inferior power in comparison to those utilizing all observations. Recommendations are made for the various situations.
A numerical study on determination of volume averaged thermal transport properties of metal foam structures using X-ray microtomography technique

Abstract Volume averaged thermal transport properties of two metal foams with 10 and 20 PPI are obtained by using microtomography technique. The digital 3D structures of samples are generated in computer environment. The governing equations are solved for the entire domain and the volume averaged technique is used to determine interfacial heat transfer coefficient, longitudinal and transverse thermal dispersion conductivity. The study is performed for the pore scale Reynolds number from 100 to 600. The obtained results are within the ranges of the suggested correlations in literature. The present study supports the correlations suggested by Calmidi and Mahajan (2000) and Zhang et al. (2016).
The dual nature of American partisan affect: Examining the impact of inparty affinity and outparty animosity on unique forms of political behavior

Much recent work has focused on Americans’ positive and negative feelings toward their own and opposing political parties. However, there is neither a consensus on how to model such partisan affect, nor a detailed understanding of its consequences for political participation. This work addressed these two gaps by first, empirically examining how many dimensions best characterize American partisan affect. Study 1A used contemporary, categorical approaches to factor analyses across an extensive set of partisan affect items from the Pew American Trends Panel to test two competing hypotheses: that (1A-1) partisan affect is one-dimensional, or that (1A-2) partisan affect is two-dimensional. Results suggested support for Hypothesis 1A-2; two dimensions of partisan affect covered inparty affinity and outparty animosity. Second, Study 1B investigated the predictive validity of different aspects of partisan affect in terms of discrete forms of political participation. Study 1B had three competing hypotheses implied by prior partisan affect literature: that (1B-1) outparty animosity (but not inparty affinity) would predict most forms of behavior, that (1B-2) outparty animosity would predict higher-cost forms of behavior, and inparty affinity would predict lower-cost forms of behavior, or that (1B-3) the combination/interaction of outparty animosity and inparty affinity would predict most forms of behavior. Results of logistic regressions suggested partial support for Hypothesis 1B-1 and direct support for Hypothesis 1B-2. Outparty animosity predicted more medium-cost forms of political participation, whereas inparty affinity predicted lower-cost forms of political participation. Implications are discussed for theory, the measurement of partisan affect, and the prediction of political participation.
Stability Region and Transmission Control of Multi-Cell Aloha Networks

As one of the most representative random-access schemes, slotted Aloha has been adopted in various wireless communication networks. A multi-cell Aloha network may easily become unstable as the inter-cell interference grows if the traffic input rates and transmission probabilities of nodes are not properly regulated. Yet how to stabilize a multi-cell Aloha network has remained largely unknown. To address the above open issue, an analytical framework is proposed in this paper for multi-cell Aloha networks to characterize the stability region of traffic input rates and operating region of transmission probabilities of nodes for achieving network stability. Specifically, the inter-cell interference level is captured by the overlapping ratio of each cell, and shown to be a key factor that determines the stability performance. For a two-cell Aloha network, the stability region of input rates and complete operating regions of transmission probabilities are obtained as functions of the overlapping ratios of cells. For the general $M$ -cell case, a transmission control algorithm is further proposed to stabilize the network only based on the local information exchange between neighboring cells, with effectiveness demonstrated through simulations.
General Properties of Landscapes: Vacuum Structure, Dynamics and Statistics

Even the simplest extra-dimensional theory, when compactified, can lead to a vast and complex landscape. To make progress, it is useful to focus on generic features of landscapes and compactifications. In this work we will explore universal features and consequences of (i) vacuum structure, (ii) dynamics resulting from symmetry breaking, and (iii) statistical predictions for low-energy parameters and observations. First, we focus on deriving general properties of the vacuum structure of a theory independent of the details of the geometry. We refine the procedure for performing compactifications by proposing a general gauge-invariant method to obtain the full set of Kaluza-Klein towers of fields for any internal geometry. Next, we study dynamics in a toy model for flux compactifications. We show that the model exhibits symmetry-breaking instabilities for the geometry to develop lumps, and suggest that similar dynamical effects may occur generically in other landscapes. The questions of the observed arrow of time as well as the observed value of the neutrino mass lead us to consider statistics within a landscape, and we verify that our observations are in fact typical given the correct vacuum structure and (in the case of the arrow of time) initial conditions. Finally, we address the question of subregion duality in AdS/CFT, arguing for a criterion for a bulk region to be reconstructable from a given boundary subregion by local operators. While of less direct relevance to cosmological space-times, this work provides an improved understanding of the UV/IR correspondence, a principle that underlies the construction of many holographically-inspired measures used to make statistical predictions in landscapes.
LIQUIDITY RISK IMPACT ON STOCK RETURNS

This study investigates the impact of liquidity risk on stock returns in the Malaysian stock exchange using the LCAPM model of Acharya and Pedersen. This research employed firm-level equity data involving 419 continuously listed firms in Bursa Malaysia from January 2000 to December 2018. The study employed LCAPM asset pricing model tested using Fama-Macbeth two-stage cross-sectional regression. The findings suggest that the covariance between stock illiquidity and the market return is not priced in the Malaysian stock market. While, the other explanatory variables are significant in explaining the cross-sectional variations of stock returns, but only two variables; the commonality in liquidity and net liquidity risks are correctly signed. The evidence is limited to Malaysian corporations listed in the Main Market of Bursa Malaysia. These findings show some new evidence on the application of the LCAPM model in the emerging markets by using the closing per cent quoted spread impact (CPQS Impact) of Chung and Zhang (2014) as a measure of illiquidity. This research provides new insights on LCAPM application in the Malaysian stock market.
Homogenization for a Parabolic Partial Differential Equation with Two-scaled Advection

: Advection-diffusion equations are frequently encountered in many ﬁelds and have become a very active research area. However, in most cases, these equations concern different time and space scales, which make it impossible to derive explicit solutions to these equations. To overcome this difﬁculty, the theory of homogenization aims to approximate the original differential equation with rapidly oscillating coefﬁcients by an effective homogenized equation with constant or slowly varying coefﬁcients. The homogenized equation is often quite suitable for theoretical analysis or numerical methods. This paper investigates the homogenization principle of an advection-diffusion partial differential equation. The novelty of the parabolic partial differential equation we consider is that the advection term in the equation is two-scaled, which is rarely considered by others for the homogenization of advection-diffusion equation. Under certain proper assumptions on the coefﬁcient functions of the original advection-diffusion partial differential equation, which ensure the variable elimination, we derive the homogenized equation, which is also an advection-diffusion equation, by the technique of multi-scale expansion. It is shown that the coefﬁcient functions of the original two-scaled equation have different inﬂuence on the coefﬁcient functions of the homogenized equation
Consensus of Multi-Agent Systems With Heterogeneous Input Saturation Levels

In this brief, a consensus problem is investigated for a class of multi-agent systems with input saturation, in which the common assumption in existing related literature that each agent has the same input saturation level is removed. Furthermore, the communication graphs are general directed graphs. New kinds of fully distributed control protocols, depending on only the relative state information, are successfully designed to achieve global state consensus among the agents. Specifically, neither the saturation levels of the neighboring agents nor the information about the global communication topology is involved in the controller design. Both leaderless consensus and leader-following consensus with a dynamic leader are studied. Simulation examples are finally provided to illustrate the theoretical results.
All optical active high decoder using integrated 2D square lattice photonic crystals

The paper introduces a novel all optical active high 2 × 4 decoder based on 2D photonic crystals (PhC) of silicon rods with permittivity of ε = 10.1 × 10−11 farad/m. The main structure of optical decoder is designed using a combination of five nonlinear photonic crystal ring resonator, set of T-type waveguide, and line defect of Y and T branch splitters. The proposed structure has two logic input ports, four output ports, and one bias input port. The total size of the proposed 2 × 4 decoder is equal to 40 μm × 38 μm. The PhC structure has a square lattice of silicon rod with refractive index of 3.39 in air. The overall design and the results are discussed through the realization and the numerically simulation to confirm its operation and feasibility.
Grouping of Twitter users according to contents of their tweets

In today’s world most of the people use social networking sites such as Twitter. They share their opinions and their views. through these media. Grouping these users will help us in different ways such as product recommendation, opinion mining, characterization of users based on their way of expressing their feelings. In this work, we present a technique to group the users based on the textual contents of the tweets. This technique is based on an unsupervised approach of machine learning that is clustering. A method is presented for representing the users using vector space model and TF-IDF weight scheme. K-means algorithm is employed for grouping the users using cosine distance as a distance measure. For the evaluation of this method, we construct a Twitter user dataset by using the Twitter application programming interface (API). A new technique is also proposed for characterization of the clusters formed. The experimental results are promising and from the study, it is found that the users in the clusters formed could be well defined by using the proposed cluster characterization technique.
Noise Estimation and Quality Assessment of Gaussian Noise Corrupted Images

Evaluating the exact quantity of noise present in an image and quality of an image in the absence of reference image is a challenging task. We propose a near perfect noise estimation method and a no reference image quality assessment method for images corrupted by Gaussian noise. The proposed methods obtain initial estimate of noise standard deviation present in an image using the median of wavelet transform coefficients and then obtains a near to exact estimate using curve fitting. The proposed noise estimation method provides the estimate of noise within average error of +/-4%. For quality assessment, this noise estimate is mapped to fit the Differential Mean Opinion Score (DMOS) using a nonlinear function. The proposed methods require minimum training and yields the noise estimate and image quality score. Images from Laboratory for image and Video Processing (LIVE) database and Computational Perception and Image Quality (CSIQ) database are used for validation of the proposed quality assessment method. Experimental results show that the performance of proposed quality assessment method is at par with the existing no reference image quality assessment metric for Gaussian noise corrupted images.
An extensive review of face powders: Functional uses and formulations

The face powder was demanded by many nations in the world in the beginning AD and in Asia white skin was believed to be the sign of aristocratism, membership of the elite, and yet, white color is the pure symbol of the internal beauty and nobility. In addition, some face powders are sold in varying specialty shades to suit different skin needs; for example, a face powder with a greenish tinge will minimize the appearance of redness, while a purple-tinted powder may help the appearance of sallow or yellow skin. There is a legitimate reason to use face powder, and the pharmacopeias prescribe them in the treatment of many skin affections. At all events the proper use of powder is beneficial, it lightly covers and unifies a complexion, hiding the ravages of time, improving even the beautiful face. Face powder comes in different shades to match varying skin tones, and it is a good idea to choose the skin tone that most closely matches the natural skin. This will help the makeup appear more natural; it should be virtually unnoticeable. It may be necessary to use different face powders for summer and winter, as the skin may become tanner in the summer, or drier and in need of extra moisture in the winter. They are of benefit in acne, freckles, sunburn and red nose. Beneath their attractive aspect and odor, face powders should be made by the perfumer to combine the qualities of an elegant cosmetic and therapeutic agent; they must primarily possess adherence, lightness and be transparent; secondly, they should be detergent and delicately absorbent in order to aid the natural functions of the skin, taking up the fatty matters not easily dislodged by water; they should also tend to increase the natural elasticity and regular functions of the skin.
Learning Objectives for Treatment Effect Estimation

We develop a general class of two-step algorithms for heterogeneous treatment effect estimation in observational studies. We first estimate marginal effects and treatment propensities to form an objective function that isolates the heterogeneous treatment effects, and then optimize the learned objective. This approach has several advantages over existing methods. From a practical perspective, our method is very flexible and easy to use: In both steps, we can use any method of our choice, e.g., penalized regression, a deep net, or boosting; moreover, these methods can be fine-tuned by cross-validating on the learned objective. Meanwhile, in the case of penalized kernel regression, we show that our method has a quasi-oracle property, whereby even if our pilot estimates for marginal effects and treatment propensities are not particularly accurate, we achieve the same regret bounds as an oracle who has a-priori knowledge of these nuisance components. We implement variants of our method based on both penalized regression and convolutional neural networks, and find promising performance relative to existing baselines.
An extension of the general nanoindentation equation regarding cylindrical—shaped samples and a simplified model for the contact ellipse determination

The mechanical properties of biomaterials and biological samples at the nanoscale can be determined using the AFM nanoindentation method. Typical biological samples are the fibrous proteins which can be modelled as cylindrical—shaped samples. However, the nanoindentation method for such samples is a challenging procedure due to the fact that the projected contact area between a spherical indenter and the sample is elliptical and as a result advanced mathematical analysis is required. Several approximations are commonly used to avoid the complexity, which, however, result in significant errors in the analysis. The purpose of this paper is to present a new simplified technique which extends the applicability of the general nanoindentation equation for cases that concern cylindrical—shaped samples. The proposed analysis results in the accurate calculation of the projected contact area and can be generally applied when biological samples and biomaterials with cylindrical symmetry are being tested using spherical indenters.
Some applications of invexity and generalized invexity ti Pareto optimization problems

We consider three applications of invexity and generalized invexity to a multiobjective (Pareto) optimization problem: i) It is shown that in a Pareto optimization problem involving generalized pseudolinear functions, every efficient solution is a properly efficient solution under some boundedness condition. ii) Some remarks are made on semilocally preinvex functions, their generalizations and on applications. iii) We recall the definition of a class of generalized invex functions by means of K-dimensional derivatives; then we apply this class of functions to a Pareto optimization problem.
ICT students' perceptions towards ChatGPT: An experimental reflective lab analysis

This study explores the use of the Generative artificial intelligence (GenAI) tool ChatGPT in higher education. Amidst the potential benefits and the risk of misuse, this research investigates the tool's role as a classroom aid and its impact on learning outcomes and experiences. Three case studies involving undergraduate and postgraduate ICT students were conducted. Findings revealed a positive perception of ChatGPT as a useful and enjoyable learning resource. Most students indicated a willingness to use such AI tools in the future. Additionally, the study suggested improved performance in functionality, user flow, and content comprehension among students using ChatGPT, compared to those relying solely on traditional search engines.
Covering the 2020 Tokyo Olympics as the Recovery Olympics After Fukushima

This article examines how major Japanese national newspapers - the Asahi Shimbun, the Mainichi Shimbun, the Yomiuri Shimbun, the Nihon Keizai Shimbun, and the Sankei Shimbun - discussed the 2020 Tokyo Olympics as the “Recovery Olympics” in relation to radioactive materials as a key post-Fukushima environmental contamination issue. Although many scholars have critically examined the concept of the Recovery Olympics in the context of the Great East Japan Earthquake, Tsunami, and Fukushima Daiichi nuclear disaster, this study employs Beck’s risk society and Boykoff’s celebration capitalism theories to distinguish between the recovery discourses of the earthquake and tsunami versus the Fukushima disaster. It then explores the media’s depiction of the Recovery Olympics in relation to radioactive contamination. Using Fairclough’s dialectical-relational approch to critical discourse analysis, this study demonstrates that the leading Japanese national newspapers localized the issue of post-Fukushima environmental contamination within Fukushima Prefecture, thereby obscuring broader impacts for the Olympics. Additionally, it uncovers how these newspapers emphasized safety standards, transforming post-Fukushima environmental contamination below such standards into a symbol legitimizing the Recovery Olympics.
Michelson and Morley Experiment Does not Validate Length Contraction

The theory of length contraction was initially proposed to uphold the existence of aether after the surprise null result from Michelson and Morley (M&M) experiment. The theory claimed that any physical object shrinks in the direction of its movement through aether. The theory is accepted by special relativity. It is, however, redefined as the shortening of any physical object in the direction of its movement relative to an observer. This article shows that M&M experiment does not support length contraction, and time dilation, as the theory was not based on all-inclusive analysis of the experiment. In fact, the distance traveled by the half-silvered mirror was not examined in the experiment to find out it does not agree with length contraction. Subsequently, the constancy of the speed of light becomes uncorroborated by the experiment.
On the inverse problem of the calculus of variations for ordinary differential equations

Summary. Lepagean 2-form as a globally defined, closed counterpart of higher-order variational equations on fibered manifolds over one-dimensional bases is introduced, and elementary proofs of the basic theorems concerning the inverse problem of the calculus of variations, based on the notion of Lepagean 2-form and its properties, are given.
Digital Signal Processing UD Method and its Statistical Characteristics

Mathematical model for UD (Up and Down) procedure of digital signal processing was formulated as a simple homogeneous Markov chain. For such Markov chains were investigated transition probability distributions by step numbers sufficient for practically stationary process. Conditions were analysed under which infinite Markov chain may be replaced by a finite Markov chain practically equivalent to the infinite chain, i.e. difference between variances of both processes is negligible. It was shown how these variances depend on UD procedure step length and step number parity. Bibl. 7 (in English; summaries in English, Russian and Lithuanian).