Miracle-dz/UniFAR-FTUs huggingface dataset:
E-Learning Games Enjoyment to Pupils’ Learning Behaviors in Mathematics Classroom

One of the hardest courses for students to grasp is mathematics, yet it's a crucial ability to have. In order to figure out why students behave in a certain way when studying mathematics, researchers must look for the factors that influence their behaviors. This study helped by presenting the Grade 6 students' learning behaviors in mathematics and their enjoyment of e-learning games. With thirty (30) grade six students as respondents to the adapted-modified survey questionnaire, the study's objectives for the academic year 2021–2022 were successfully met through the descriptive-correlational research design and purposive sampling technique. The findings demonstrate a positive significant relationship between interest, confidence, motivation, and usefulness that is consistent with students' learning behavior in mathematics and the enjoyment of e-learning games in terms of concentration, goal clarity, feedback, challenge, autonomy, immersion, social interaction, and knowledge improvement. Findings showed that e-learning games were helpful at increasing students’ interest in the subject. This means that using e-learning games as a good teaching tool can help to enhance and enhance students' learning behavior. Taking into account the limitations on a specific subject, the study suggests further scrutiny on the enjoyment of e-Learning games as applied in other disciplines.
Domain-Adaptive Mean Teacher for Category-Level Object Pose Estimation

Category-level object pose estimation aims at predicting 6-DoF object poses for previously unseen objects. Current methods mostly rely on ground-truth labels such as object poses and CAD models. However, annotating these labels manually is time-consuming and error-prone in the real-world scenario. Hence, we propose a novel method to solve unsupervised domain adaptation (UDA) for category-level object pose estimation. We adopt a teacher-student framework to utilize both labeled synthetic data and unlabeled real-world data. The student and the teacher are trained to make consistent predictions under different perturbations. Furthermore, we introduce domain adversarial training to bridge the domain gap between synthetic and real-world data. To prevent false feature alignment between domains, we adopt multiple discriminators instead of a single one and perform category-aware alignments. Extensive experiments show that our method achieves state-of-the-art performance on the REAL275 dataset. Through ablation studies, we also demonstrate that our method is not restricted to certain network architecture and can serve as a general UDA method for category-level object pose estimation.
Open-Vocabulary Segmentation Approach for Transformer-Based Food Nutrient Estimation

Nutrition plays a vital role in overall health and well-being. With a highly accurate nutrient estimation model, we develop a tool that displays nutritional values from food images, thereby reducing the labor-intensiveness of dietary assessment. We propose a method that uses depth data with RGB images and incorporates an open-vocabulary segmentation process that separates food from non-food instances, coupled with two-stage self-attention Transformer decoder. Our model outperforms the current state-of-the-art method, with an average percent MAE of 17.2% on Nutrition5k, an RGB-D food image dataset with calories, mass, and three macronutrients annotated. Our study also focuses on the significance of the food and background regions for calorie, mass, and nutrient estimation. We analyze the impact of non-food regions on each estimation task, with results suggesting that background information is crucial for calorie, mass, and carbohydrate estimation but not as essential for protein and fat estimation. The qualitative results also show that the model attends to regions with a high corresponding nutritional value. Implementation codes and pre-trained models are provided at https://github.com/Oatsty/nutrition5k.
Summer habitat use and activity patterns of domestic sheep on coniferous forest range in southern Norway.

Eight domestic sheep (r poorer forest types were used more in the evening and at night. As the season progressed, use of the meadow/old-field habitat type declined in favor of the forest types. Activity peaks were at mid-morning and late evening. Animals camped in groups at midday and at night, always further upslope at night than during the day. Sheep were less active in cold, wet weather. Habitat selection and activity patterns observed in this study were similar to those of both wild and domestic sheep studied elsewhere.
Prognostic relevance of correlated co-expression of coding and noncoding RNAs in cervical cancers

Human papillomavirus (HPV) drives cervical cancer (CaCx) pathogenesis and viral oncoproteins jeopardize global gene expression in such cancers. We aimed to identify differentially expressed coding (DEcGs) and long noncoding (sense intronic and Natural Antisense Transcripts) RNA genes (DElncGs) in HPV16-positive CaCx patients (N=44) compared to HPV-negative normal individuals (N=34). Thereby, employing strand-specific RNA-seq, we determined the relationships between DEcGs and DElncGs and their clinical implications. Gene set enrichment and protein-protein interaction analyses of DEcGs revealed enrichment of processes crucial for abortive virus life cycle and cancer progression. The DEcGs formed 16 gene clusters, portraying cancer-related functions. We recorded significantly correlated co-expression of 79 DElncGs with DEcGs at proximal genomic loci, and 24 such pairs portrayed significantly altered correlation coefficients among patients, compared to normal individuals. Of these, 6 DEcGs belonged to 5 gene clusters, one of which was survival-associated. Out of the 24 correlated DEcG: DElncG pairs, 3 pairs were identified, where expression of both members was significantly associated with patient overall survival. Besides being prognostically relevant, disruption of the significant correlative relationships of such gene pairs in CaCx bears immense potential for patient-targeted therapy. Graphical Abstract: A schematic representation of the analyses undertaken to draw insights on the biological relevance of joint analysis of co-expressed and significantly correlated DElncGs and DEcGs considering the ncNATs and sense intronic DElncGs, in HPV16-positive CaCx patients compared with HPV-negative normal individuals.
Competition for resources during development drives allometric patterns in the grass Setaria

Grasses grow a series of phytomers during development. The distance between successive leaves is determined by internode lengths. Grasses exhibit genetic, developmental, and environmental variability in phytomer number, but how this affects internode length, biomass, and height is unknown. We hypothesized that a generalized mathematical model of phytomer development wherein between-phytomer competition influences internode length distributions would be sufficient to explain internode length patterns in two Setaria genotypes: weedy A10 and domesticated B100. Our model takes a novel approach that includes the vegetative growth of leaf blade, sheath, and internode at the individual phytomer level, and the shift to reproductive growth. To validate and test our mathematical model, we carried out a greenhouse experiment. We found that the rate of leaf emergence is consistent for both genotypes across development, and that the length of time spent elongating for the leaf and internode can be described as the ratio between the time of phytomer emergence and the elongation completion time. The validated model was simulated across all possible parameter values to predict the influence of phytomer number on internode length. This analysis predicts that different internode length distributions across different numbers of total phytomers are an emergent property, rather than a genotype-specific property requiring genotype-specific models. We applied the model to internode length only field data of S. italica accession B100, grown under both well-watered and drought conditions. The model predicts that droughted plants reduce leaf elongation time, reduce resource allocation to the internodes, and overall experience slower growth. Together, model and data suggest that allometric patterns are driven by competition for resources among phytomer and the shift to reproductive growth in Setaria. The resulting model enables us to predict growth dynamics and final allometries at the phytomer level.
Cross-Species Variability in Lobular Geometry and Cytochrome P450 Hepatic Zonation: Insights into CYP1A2, CYP2E1, CYP2D6 and CYP3A4

This study explores the critical interplay between lobular geometry and the zonated distribution of cytochrome P450 (CYP) enzymes across species. We present an innovative approach to assess lobular geometry and zonation patterns using whole slide imaging (WSI). This method allows a detailed, systematic comparison of lobular structures and spatial distribution of key CYP450 enzymes and glutamine synthetase in four different species (mouse, rat, pig, and human). Our results shed light on species differences in lobular geometry and enzymatic zonation, providing critical insights for drug metabolism research. Based on our approach we could determine the minimum number of lobules required for a statistically representative analysis, an important piece of information when evaluating liver biopsies and deriving information from WSI.
The evolution of fitness during range expansions in multiple dimensions

We efficiently simulate range expansions of populations, by using our set of computer programs, on a laterally connected lattice in 1D, 2D (on a strip, and on a disk) and 3D (in a cylinder, and in a sphere). We employ a model with finite genome regions, each containing infinite sites, for a population of diploid individuals. Using the programs, we generate tens of simulation replicates to analyse the temporal evolution of mean fitness of individuals on the expansion front. We explore the model over different conditions, compare normalisation methods for fitness, and explore the case of radial (sphere) and axial (cylinder) expansions in 3D, which might apply in the analysis of the behaviour of viruses/bacteria inside a host, in the prediction of expansions of marine species in ocean environments, and even in scenarios of interstellar space colonization. In 3D expansions, we find complex spatial fluctuations in deme-average fitness values, different from those in radial 2D expansions. In axial 3D (cylinder) expansions, we determine that the highest-valued deme-average fitness lies along the axis of the expansion. We also find the fluctuation patterns of fitness in 3D cylinder expansions, similar to those previously seen in radial expansions in 2D. In radial 2D (disk) expansions, we find that the fitness of a population undergoing multiple mutations shows a smooth combination of binary segregation pictures against each of those mutations. We confirm the accumulation of deleterious mutations -- a phenomenon known as expansion load -- in all scenarios above.
An Efficient and Safe Trans-complementation System of Mpox Virus Reproduces Authentic Viral Architecture and Infection

The current Mpox virus (MPXV) outbreak since 2022 has led to 92,783 cases and at least 171 fatalities across 116 countries, with increased transmission noted particularly among male homosexual activities, though the underlying causes remain unknown. The requirement of biosafety level 3 (BSL-3) laboratories poses a barrier to MPXV research and the formulation of antiviral strategies, while genetic modifications to the wild-type live virus raise biosafety and bioethical concerns. Here we report a novel trans-complementary system that produces a single-round infectious MPXV, preserving the virus’s authentic architecture and enabling it to complete its life cycle in complementary cells. This deficient MPXV genome lacks two essential genes critical for viral late genes transcription, viral assembly, and release. The entire 197 kb genome of the deficient MPXV was synthesized and assembled in vitro, a method that reduces the risk of recombination with bacterial or yeast DNA, in contrast to traditional recombination techniques. The deficient MPXV, limited to single-round infection in various normal cell lines, regained reproductive capability in the complementary cells. Notably, SCID mice inoculated with this deficient MPXV exhibited no detectable disease or viral load in their organs. Therefore, this trans-complementation platform can be safely utilized in BSL-2 laboratories, providing a valuable tool for MPXV research and the development of countermeasures.
Improving the power of drug toxicity measurements by quantitative nuclei imaging

Imaging-based anticancer drug screens are becoming more prevalent due to development of automated fluorescent microscopes and imaging stations, as well as rapid advancements in imaging processing software. Automated cell imaging provides many benefits such as their ability to provide high-content data, modularity, dynamics recording and the fact that imaging is the most direct way to access cell viability and cell proliferation. However, currently most publicly available large-scale anticancer drugs screens, such as GDSC, CTRP and NCI-60, provide cell viability data measured by assays based on colorimetric or luminometric measurements of NADH or ATP levels. Although such datasets provide valuable data, it is unclear how well drug toxicity measurements can be integrated with imaging data. Here we explored the relations between drug toxicity data obtained by XTT assay, two quantitative nuclei imaging methods and trypan blue dye exclusion assay using a set of four cancer cell lines with different morphologies and 30 drugs with different mechanisms of action. We show that imaging-based approaches provide high accuracy and the differences between results obtained by different methods highly depend on drug mechanism of action. Selecting AUC metrics over IC50 or comparing data where significantly drugs reduced cell numbers noticeably improves consistency between methods. Using automated cell segmentation analysis and data-driven approach we show that XTT assay produces unreliable data for cell cycle and DNA repair inhibitors due induced cell size growth and increase in mitochondria activity. We also explored several benefits of image-based analysis such as ability to monitor cell number dynamics, dissect changes in mitochondria activity from cell proliferation, and ability to identify chromatin remodeling drugs.
An impact perspective on pan-European drought sensitivity

In the past decades, Europe experienced several severe drought events with diverse environmental and socio-economic impacts. The EU FP-7 project DROUGHT RS the importance of energy and industry impacts appears to be country-specific. The differences in relevance of the affected sectors and in type of impacts even within the same broader category support the need to determine impact-specific indicators for monitoring and management. The EDII database is now publicly available online for use and for contribution from the community, and the patterns found will have to be reassessed as it expands over time.
Impact of firm-created and user-generated social media communication on brand associations

The purpose of this article is to study the impact of firm-created and user-generated social media communication on brand association through Facebook. This study evaluated 262 data sets that were generated through a standardized online survey to investigate the impact of firm-created and user-generated social media brand communication on brand associations, across 3 brands within the mobile network service providers in Sri Lanka. The study was applied a structural equation modeling technique to investigate the effects of social media communication on brand association. The results of the empirical studies showed that both firm-created and user-generated social media brand communication influence brand associations. This study is pioneering in that it exposes the effects of two different types of social media communication such as firm-created and user-generated social media brand communication on brand association, this study of relevance for both marketers and scholars in the era of social media. Additionally, this included the recommendations for practitioners, strategies to create effective social media brand communication.
Fast high fidelity CFD/CSM fluid structure interaction using RBF mesh morphing and modal superposition method

Purpose This paper aims to present a fast and effective approach to tackle complex fluid structure interaction problems that are relevant for the aeronautical design. Design/methodology/approach High fidelity computer-aided engineering models (computational fluid dynamics [CFD] and computational structural mechanics) are coupled by embedding modal shapes into the CFD solver using RBF mesh morphing. Findings The theoretical framework is first explained and its use is then demonstrated with a review of applications including both steady and unsteady cases. Different flow and structural solvers are considered to showcase the portability of the concept. Practical implications The method is flexible and can be used for the simulation of complex scenarios, including components vibrations induced by external devices, as in the case of flapping wings. Originality/value The computation mesh of the CFD model becomes parametric with respect to the modal shape and, so, capable to self-adapt to the loads exerted by the surrounding fluid both for steady and transient numerical studies.
Ethnic Differences in Clinical Presentation of Depression in Adult Women

• Hector F. Myers, Department of Psychology, University of California, Los Angeles (UCLA), and Department of Psychiatry, Charles R. Drew University of Medicine and Science; Ira Lesser, Christina Camp, Dora Anderson, and Marcy Wohl, Department of Psychiatry, Harbor–UCLA Medical Center; Norma Rodriguez, Department of Psychology, Pitzer College; Consuelo Bingham Mira and Lucy Erickson, Department of Psychiatry, Charles R. Drew University of Medicine and Science; Wei-Chin Hwang, Department of Psychology, UCLA. Christina Camp is now at the California School of Professional Psychology. This research is supported in part by National Institute of Mental Health Grant MH47913 to the Research Center on the Psychobiology of Ethnicity, Harbor–UCLA Medical Center, and by National Institutes of Health (NIH) Grant 1 P20 RR11145 to the Research Centers in Minority Institutions Clinical Research Center, Charles R. Drew University of Medicine and Science, and NIH Grant RR00425 to the NIH General Clinical Research Center, Harbor–UCLA Medical Center. Correspondence concerning this article should be addressed to Hector F. Myers, Department of Psychology, UCLA, P. O. Box 951563, Los Angeles, California 90095-1563. E-mail: myers@psych.ucla. edu
Comparing the Associations of Dietary Patterns Identified through Principal Component Analysis and Cluster Analysis with Colorectal Cancer Risk: A Large Case–Control Study in China

Examining the association between dietary patterns and colorectal cancer (CRC) risk can provide valuable insights beyond the assessment of individual foods or nutrients. However, there is a lack of in-depth analysis of dietary patterns and CRC risk in Chinese populations, and few studies have compared dietary patterns derived from different posteriori methods with the aim of predicting disease risk. The aim of this study was to derive dietary patterns using both principal component analysis (PCA) and cluster analysis (CA) and to assess their respective associations with CRC risk. A large-scale case-control study was conducted in Guangdong Province, China, including 2799 incident colorectal cancer cases and an equal number of frequency-matched controls. Dietary intake information was gathered through the use of a validated food frequency questionnaire. PCA and CA were used to derive dietary patterns. A multivariable logistic regression model was used to calculate the adjusted odds ratio (aOR) and 95% confidence interval (CI). Four major dietary patterns were identified by PCA. CA identified two dietary patterns, referred to as the “Balanced dietary pattern” and the “Refined grain dietary pattern”. Notably, there were significant inverse associations between the milk-egg-nut-soy dietary pattern (aOR, 0.51; 95% CI, 0.42, 0.62), the vegetable-fruit dietary pattern (aOR, 0.61; 95%CI, 0.51, 0.74), and the poultry-fish dietary pattern (aOR, 0.81; 95%CI, 0.68, 0.97) and CRC risk. However, the red meat-preserved food dietary pattern was associated with an increased risk of CRC (aOR, 2.99; 95%CI, 2.43, 3.67). When compared with the Refined grain dietary pattern, the Balanced dietary pattern showed a decreased risk of CRC (aOR, 0.59; 95%CI, 0.52, 0.66). The results from the comparison of the two methods indicate that both CA and PCA derived remarkably similar patterns. The combined use of PCA and CA identified consistent underlying patterns, showing comparable associations with CRC risk. These findings suggest that individuals who prefer dietary patterns characterized by a high intake of red meat, preserved food, and refined grains should be cautious about their increased CRC risk. Conversely, dietary patterns rich in fruits, vegetables, and high-quality protein sources are advisable for the prevention of CRC in the Chinese population.
Pilbara regional flood frequency analysis

The paper reviews the Pilbara Region flood frequency factors and design discharge equations used for Index-flood method in 1987 version of Engineers Australia Australian Rainfall and Runoff using an up to date dataset and more recent statistical techniques. Updated flood frequency factors and design discharge equations for the Indian Ocean Drainage Division of Western Australia (including the Pilbara) are presented. Comparisons are made between the design peak discharge from this study and other recent studies.
Rif2 protects Rap1-depleted telomeres from MRX-mediated degradation in Saccharomyces cerevisiae

Rap1 is the main protein that binds double-stranded telomeric DNA in Saccharomyces cerevisiae. Examination of the telomere functions of Rap1 is complicated by the fact that it also acts as a transcriptional regulator of hundreds of genes and is encoded by an essential gene. In this study, we disrupt Rap1 telomere association by expressing a mutant telomerase RNA subunit (tlc1-tm) that introduces mutant telomeric repeats. tlc1-tm cells grow similar to wild-type cells, although depletion of Rap1 at telomeres causes defects in telomere length regulation and telomere capping. Rif2 is a protein normally recruited to telomeres by Rap1, but we show that Rif2 can still associate with Rap1-depleted tlc1-tm telomeres, and that this association is required to inhibit telomere degradation by the MRX complex. Rif2 and the Ku complex work in parallel to prevent tlc1-tm telomere degradation; tlc1-tm cells lacking Rif2 and the Ku complex are inviable. The partially redundant mechanisms may explain the rapid evolution of telomere components in budding yeast species.