Miracle-dz/UniFAR-FTUs huggingface dataset:
Evaluation of Illumination in 3D Scenes Based on Heat Maps Comparison

—The issues of assessing the quality of lighting computer 3D scenes using different lighting systems are considered. Quality lighting increases realism, immersion and improves the perception of shape, color and texture of objects in the image. Existing engineering professional lighting calculation programs are not well suited to the design, art solutions or gaming scenes. To obtain objective estimates of illumination, we propose to use metrics for evaluating the quality of rendering systems. Particular attention is paid to the use of such tools as heat maps. Their visual analysis by hue or intensity helps to compare and evaluate the quality of illumination of scenes. However, such a comparison does not give a cumulative score. A possible solution is to treat heat maps as images and use them as the basis for a generalized heat map to produce a single cumulative statistic. In order to create a generalized heat map, several ways of constructing a difference matrix based on normalization methods have been proposed. The proposed approach is implemented as a prototype application. Experiments were carried out on test scenes with different illumination systems. The generalized heat maps made it possible to obtain cumulative estimates of the comparison of different lighting approaches and to identify areas most sensitive to changes in illumination. According to the authors, the proposed approach to illuminance estimation for staged lighting can be used to improve the realism of visualization in 3D modeling.
Xi Xi's Playful Image-Texts: Ekphrasis, Parergon, and the Concept of Toy

What does the ludic have to do with Xi Xi’s writings and creative concerns? Since Jacques Ehrmann’s Game, Play, Literature (1968) and Warren Motte’s Playtexts (1995), critical discussions about play have expanded significantly beyond video game studies and child pedagogy to literature and aesthetics. Critics such as Espen Aarseth and Astrid Ensslin (2014) focus on how the reader becomes a player and argue for the importance of “ergodicity”, or “non-trivial” (Aarseth 1997: 1) effort that ludic literature demands from readers; Katherine Hayles (2007) discusses how intermediation in digital literature creates ludic effects in the dynamic switching between different interfaces and media; whereas Mihai Spariosu (1997: xv) identifies playful literary discourse as a “liminal mode of being”. These studies highlight text-reader interactivity and play as a destabilizing and self-justifying movement at work in literature and aesthetic experience. Nevertheless, they have – as well as most discussions of literary ludicity – focused on literature produced in Europe and North America. This essay thus aims to contribute to existing criticism by exploring how Xi Xi’s works offer us new articulations of play.
Twinned Teachers’ Mathematical Discourse Using Problem-Solving

Discussing and debating mathematical ideas through integrating natural and mathematical language is vital for conceptual understanding and ultimately for learner performance. In schools with low performance, it is likely that teaching mathematics follows an approach largely involving rote learning. In rural Limpopo where schools are isolated, professional development takes the form of twinning, where a well-functioning school twins with a school in need. In this study two teachers twinned to teach algebraic word problems to Grade 11 to improve learner performance through a problem-solving approach. A central aspect of the study was attention to discourse informed by the commognitive framework, where both natural language (learners home language and the language of instruction) and language of mathematics spoken by the teachers and encouraged in the learners, was the focus. This quasi-experimental design was implemented to examine the effect of the twinned teachers discourse in a class where English, the language of instruction, was a second language. In the study a pre-test and post-test were administered to the experimental group of 34 learners, and to a comparison group of 40 learners. The study aimed at testing the hypothesis that the twinned mathematics teachers’ discourse using a problem-solving approach informed by the commognitive framework has a significant effect on learner performance in algebraic word problems. In summary, using the commognitive framework in implementing problem-solving approach with the twinned teachers’ mathematical discourse had significant effect in improving learner performance of algebraic word problems in the target group.
The mathematical theory of communication

Scientific knowledge grows at a phenomenal pace--but few books have had as lasting an impact or played as important a role in our modern world as The Mathematical Theory of Communication, published originally as a paper on communication theory more than fifty years ago. Republished in book form shortly thereafter, it has since gone through four hardcover and sixteen paperback printings. It is a revolutionary work, astounding in its foresight and contemporaneity. The University of Illinois Press is pleased and honored to issue this commemorative reprinting of a classic.
Bile Acids and Short-Chain Fatty Acids Are Modulated after Onion and Apple Consumption in Obese Zucker Rats

Gut microorganisms are involved in the development and severity of different cardiovascular diseases, and increasing evidence has indicated that dietary fibre and polyphenols can interact with the intestinal microbiota. The study objective was to investigate the effect of onion and apple intake on the major types of microbial-derived molecules, such as short-chain fatty acids (SCFAs) and bile acids (BAs). Obese Zucker rats were randomly assigned (n = eight rats/group) to a standard diet (OC), a standard diet/10% onion (OO), or a standard diet/10% apple (OA). Lean Zucker rats fed a standard diet served as a lean control (LC) group. Faecal samples were collected at baseline, and 8 weeks later, the composition of the microbial community was measured, and BA and SCFA levels were determined using high-performance liquid chromatography–mass spectrometry (HPLC-MS) and gas chromatography–mass spectrometry (GC-MS), respectively. Rats fed onion- and apple-enriched diets had increased abundance of beneficial bacteria, such as Bifidobacterium spp. and Lactobacillus spp. , enhanced SCFAs (acetic, propionic, isobutyric, and valeric acids), decreased excretion of some BAs, mainly of the primary (CA, α-MCA, and β-MCA) and secondary type (ω-MCA, HDCA, NCA, DCA, and LCA), and increased amount of taurine- and glycine-conjugated BAs compared to the OC group. The contribution of specific bioactive compounds and their metabolites in the regulation of the microbiome and the pathways linked to SCFA and BA formation and their relationship with some diseases needs further research.
Nutritional Interpretation of Hospital Diets for Elderly Patients With Chronic Diseases and Analysis of Factors Influencing Actual Intakes

Background The provision of hospital meals is considered a therapeutic intervention, and a therapeutic diet consisting of a post-discharge meal sample is provided. For elderly patients who require long-term care, it is important to determine the significance of nutrition by taking into account hospital meals, including therapeutic meals for conditions such as diabetes. Therefore, it is important to identify the factors that influence this judgment. This study aimed to investigate the difference between the expected nutritional intake via nutritional interpretation and actual nutritional intake. Methods The study included 51 geriatric patients (77.7 ± 9.5 years; 36 males and 15 females) who could eat meals independently. The participants completed a dietary survey to determine the perceived nutritional intake obtained from hospital meal contents. Additionally, we investigated the amount of hospital meal leftovers from the medical records and the amount of nutrients from the menus to calculate the actual nutritional intake. We calculated the amount of calories, protein concentration, and non-protein/nitrogen ratio from the perceived and actual nutritional intake values. We then calculated the cosine similarity and conducted a qualitative analysis of factorial units to examine similarities between perceived and actual intake. Results Among factors that constituted the large cosine similarity group (gender, age, etc.), gender was found as a particularly significant factor, with a high number of female patients (P = 0.014). Conclusions Gender was found to influence the appropriate interpretation of the significance of hospital meals. The perception of such meals as samples for post-discharge dietary practice was more significant among female patients. This demonstrated that in elderly patients, it is important to consider gender differences when providing diet and convalescence guidance.
Estimation For The Cox Model With Various Types Of Censored Data

In survival analysis, the Cox model is one of the most widely used tools. However, up to now there has not been any published work on the Cox model with complicated types of censored data, such as doubly censored data, partly-interval censored data, etc., while these types of censored data have been encountered in important medical studies, such as cancer, heart disease, diabetes, etc. In this dissertation, we rst derive the bivariate nonparametric maximum likelihood estimator (BNPMLE) F̂n(t, z) for joint distribution function F0(t, z) of survival time T and covariate Z, where T is subject to right censoring, noting that such BNPMLE F̂n has not been studied in statistical literature. Then, based on this BNPMLE F̂n we derive empirical likelihood-based (Owen, 1988) con dence interval for the conditional survival probabilities, which is an important and di cult problem in statistical analysis, and also has not been studied in literature. Finally, with this BNPMLE F̂n as a starting point, we extend the weighted empirical likelihood method (Ren, 2001 and 2008a) to the multivariate case, and obtain a weighted empirical likelihood-based estimation method for the Cox model. Such estimation method is given in a uni ed form, and is applicable to various types of censored data aforementioned.
Second-generation protoplanetary discs around evolved binaries: A high-resolution polarimetric view with SPHERE/IRDIS

Binary post-asymptotic giant branch (post-AGB) stars are products of a poorly understood binary interaction process that occurs during the AGB phase. These systems comprise of a post-AGB primary star, a main-sequence secondary companion and a stable circumbinary disc. Studying the structure and properties of these circumbinary discs is crucial for gaining insight into the binary interaction process that governs post-AGB binaries as well as comprehending the disc’s creation, evolution, and its interaction with the post-AGB binary system. We aim to use near-infrared polarimetric imaging to investigate the morphology and potential substructures of circumbinary discs around eight representative post-AGB binary stars. To achieve this, we performed polarimetric differential imaging in H- and Y-bands using the high-angular resolution capabilities of the ESO-VLT/SPHERE-IRDIS instrument. We resolved the extended circumbinary disc structure for a diverse sample of eight post-AGB binary systems. Our analysis provided the first estimates of the disc scale-height for two of the systems: IW Car and IRAS 15469-5311. We also investigated the morphological differences between the full discs (with inner rim at the dust sublimation radius) and transition discs (which are expected to have larger inner cavities), as well as similarities to protoplanetary disks around young stellar objects. We found that the transition discs displayed a more intricate and asymmetric configuration. Surprisingly, no correlation was found between the over-resolved flux in near-IR interferometric data and the polarimetric observations, suggesting that scattering of light on the disc surface may not be the primary cause of the observed over-resolved flux component.
Multi-spectral quantitative phase imaging based on filtration of light via ultrasonic wave

A new digital holographic microscopy scheme for multi-spectral quantitative phase imaging is proposed and implemented. It is based on acousto-optic filtration of wide-band low-coherence light at the entrance of a Mach-Zehnder interferometer, recording and digital processing of interferograms. The key requirements for the acousto-optic filter are discussed. The effectiveness of the technique is demonstrated by calculating the phase maps of human red blood cells at multiple wavelengths in the range 770–810 nm. The scheme can be used for the measurement of dispersion of thin films and biological samples.
The Challenge EFL Teachers Face in Turkey: Burnout

Burnout is quite common in educational settings for a variety of reasons and may specifically affect the lives of teachers, especially English language teachers. Therefore, it needs to be analyzed in detail and resolved by policymakers in education. To reveal this significant drawback, this research aims to examine the research studies on the issue of burnout among English as foreign language teachers from primary schools to higher education that were carried out in the English language teaching context in Turkey between 2012 and 2022 through a systematic review. 19 research studies done in Turkey were obtained and the findings of the studies related to the burnout challenge of Turkish English language teachers were scrutinized. Based on the findings of the study, English teachers are the most prevalent demographic to have a variety of ailments due to burnout, which is caused by extended exposure to high levels of stress, chronic fatigue, unhappiness, and feelings of inefficacy. The unique finding of this study is that English teachers are mainly faced with challenging and stressful conditions in their daily teaching life as they are forced to adapt to changing student profiles and technological advancements as well as rising demands of society and as a result, they struggle with burnout even if they are still in their early years of teaching English. In the meanwhile, their commitment to in-service training and the support of their superiors are crucial and maintaining a healthy lifestyle is also important. Besides, a comprehensive strategy that includes regulatory modifications, encouraging work conditions, and professional development opportunities is required to address English teacher burnout in Turkish society and thus, by prioritizing teacher well-being, education policies can have a positive influence on the education sector by ensuring the availability of motivated and effective English instructors who can provide high-quality education to students and these policies could eradicate negative views and provide the respect for the teaching profession by fostering a resilient English teaching workforce while mitigating the risks of burnout.
VeerNet: Using Deep Neural Networks for Curve Classification and Digitization of Raster Well-Log Images

Raster logs are scanned representations of the analog data recorded in subsurface drilling. Geologists rely on these images to interpret well-log curves and deduce the physical properties of geological formations. Scanned images contain various artifacts, including hand-written texts, brightness variability, scan defects, etc. The manual effort involved in reading the data is substantial. To mitigate this, unsupervised computer vision techniques are employed to extract and interpret the curves digitally. Existing algorithms predominantly require manual intervention, resulting in slow processing times, and are erroneous. This research aims to address these challenges by proposing VeerNet, a deep neural network architecture designed to semantically segment the raster images from the background grid to classify and digitize (i.e., extracting the analytic formulation of the written curve) the well-log data. The proposed approach is based on a modified UNet-inspired architecture leveraging an attention-augmented read–process–write strategy to balance retaining key signals while dealing with the different input–output sizes. The reported results show that the proposed architecture efficiently classifies and digitizes the curves with an overall F1 score of 35% and Intersection over Union of 30%, achieving 97% recall and 0.11 Mean Absolute Error when compared with real data on binary segmentation of multiple curves. Finally, we analyzed VeerNet’s ability in predicting Gamma-ray values, achieving a Pearson coefficient score of 0.62 when compared to measured data.
A Comparison of One-Step and Three-Step Approaches for Including Covariates in the Shared Parameter Growth Mixture Model

The shared parameter growth mixture model (SPGMM) has been proposed as a method to handle missing not at random (MNAR) data in longitudinal studies. This Monte Carlo simulation study compared the one-step approach with a three-step approach for adding covariates into the SPGMM. The results showed that performances of one-step and three-step approaches did not differ, but the estimate of the coefficient of the covariate was biased in most conditions with MNAR data. However, means, variances, and covariance of the intercept and slope as well as their standard errors were estimated without bias in most conditions, except for some combinations of small class distances and MNAR dropout missingness that was not related to the underlying growth trajectory. Classification accuracy was similar with both one-step and three-step SPGMM.
A Shannon-Like Solution for the Fundamental Equation of Information Science

In a seminal paper published in the early 1980s titled “Information Technology and the Science of Information,” Bertram C. Brookes theorized that a Shannon-Hartley’s logarithmic-like measure could be applied to both information and recipient knowledge structure in order to satisfy his “Fundamental Equation of Information Science. ” To date, this idea has remained almost forgotten, but, in what follows, the authors introduce a novel quantitative approach that shows that a Shannon-Hartley’s log-like model can represent a feasible solution for the cognitive process of retention of information described by Brookes. They also show that if, and only if, the amount of information approaches 1 bit, the “Fundamental Equation” can be considered an equality in stricto sensu, as Brookes required.
Design of a compact ring for proton radiation applications

This paper presents the design of a compact proton synchrotron, including lattice structure, injection system and extraction system, for radiation applications. The lattice is based on a DBFO cell and shows good properties like small βmax and decent kick arm. Radiation applications require relative strong and continuous beam, so we propose strip injection and resonance extraction for the design. A phase space painting scheme is designed and simulated by ORBIT. The scheme achieves good uniformity in phase space. The extraction system is designed and optimized by multi-particle tracking.
Using LDA Topic Modeling to Understand Regrowth Factors of the Chinese Gaming Industry in the COVID-19 Era: Current Situation, Future and Predicament

The gaming industry, which was among the industries least affected by the COVID-19 outbreak, exhibited positive growth trends during the COVID-19 period. This paper explores the impact of COVID-19 on the gaming industry by analyzing news texts from 2020 to 2022 using text mining and LDA (latent Dirichlet allocation) topic classification, and visualizing charts. The study focuses on three themes, namely the current situation, the future, and possible problems of China’s game industry in the post-epidemic era. The findings of this study suggest that the development of the game industry during the COVID-19 outbreak prompted the government to regulate policies and promote the transformation of game companies, which had a positive impact on the development of China’s game industry. However, this study also found that due to the effects of COVID-19, society and the government have increased their focus on the time management of underage game users, which poses a significant challenge to the games industry. This paper recommends improvements from three perspectives, namely society, policy, and enterprise, with the aim of contributing to the long-term development of China’s game industry.
Bayesian Hidden Topic Markov Models

Bayesian Hidden Topic Markov Models by Kenneth Tyler Wilcox Master of Science in Applied Statistics Rochester Institute of Technology Associate Professor Ernest Fokoué, Chair Recent developments in topic modeling for text corpora have incorporated Markov models in the latent space to better learn contextual content. Known as the Hidden Topic Markov Model (HTMM), this natural extension of probabilistic mixture models relaxes the “bag-ofwords” assumption of the foundational latent Dirichlet allocation topic model by allowing the discrete latent variables, or topics, to follow a special first-order Markov process. Parameter estimation is performed using an expectation-maximization (EM) algorithm with fixed dimensionality of the topic space (Gruber, Rosen-Zvi, and Weiss 2007). I fully derive the state space and EM algorithm for the HTMM. I then extend the Hidden Topic Markov Model (HTMM) into a fully Bayesian framework using a Gibbs sampler. The necessary full conditional distributions are derived and a Gibbs sampling algorithm proposed. I implement both the HTMM EM algorithm (Gruber, Rosen-Zvi, and Weiss 2007) and the HTMM Gibbs sampling algorithm in the R and C++ programming languages. The performance of both inferential algorithms is evaluated on twelve simulated data sets and on a collection of proceedings from the Conference on Neural Information Processing Systems (NIPS). The results suggest that the Gibbs sampling algorithm provides better recovery of the topic space than a combination of the EM and Viterbi algorithms. Parameter estimation is comparable using
Hierarchical Multiobjective H-Infinity Robust Control Design for Wireless Power Transfer System Using Genetic Algorithm

In inductive wireless power transfer (IPT) system, parameter perturbation and disturbances not only cause power fluctuation but also worsen system performances. Thus, robust control methods are introduced for improving the performances of uncertain IPT system. In robust control design, robust performance is often considered first. However, the enhancement of robust performance may lead to inferior time-domain performance. To deal with this contradiction, the weighting functions in the robust control design structure shall be chosen wisely. Considering the complex mutual dependence of weighting parameters, the selection of weighting parameters will become a complicated and practically time-consuming problem. Therefore, this brief presents a hierarchical multiobjective optimization method to select weighting parameters of H-infinity controller automatically. The inner level designs the H-infinity controller and guarantees robust performance. The outer level improves the system’s time-domain performance and robust performance at the same time with a specially designed objective function using genetic algorithm. An experimental IPT prototype is established for the verification of the proposed optimization method. The optimization results show both good robust performance and fast time response about 5–8ms in different experiment conditions.
Are f(R) theories of gravity necessary for cosmology

The f(R) theories of gravity and their cosmological response over a space time manifold of real dimension N are studied. As seen that the f(R) theories are nothing more than cosmological models with exotic matter source and they are exactly equivalent to the Einstein’s theory with cosmological constant, that is R− 2Λ. PACS: 04.20. -q, 04.50. Kd