Miracle-dz/UniFAR-FTUs huggingface dataset:
On Morrey's inequality in Sobolev-Slobodecki\u{\i} spaces

We study the sharp constant in the Morrey inequality for fractional Sobolev-Slobodecki\u{\i} spaces on the whole $\mathbb{R}^N$. By generalizing a recent work by Hynd and Seuffert, we prove existence of extremals, together with some regularity estimates. We also analyze the sharp asymptotic behaviour of this constant as we reach the borderline case $s\,p=N$, where the inequality fails. This can be done by means of a new elementary proof of the Morrey inequality, which combines: a local fractional Poincar\'e inequality for punctured balls, the definition of capacity of a point and Hardy's inequality for the punctured space. Finally, we compute the limit of the sharp Morrey constant for $s\nearrow 1$, as well as its limit for $p\nearrow \infty$. We obtain convergence of extremals, as well.
Same process, different patterns: pervasive effect of evolutionary time on species richness in freshwater fishes

Tropical lands harbour the highest number of species, resulting in the ubiquitous latitudinal diversity gradient (LDG). However, exceptions to this pattern have been observed in some taxa, explained by the interaction between the evolutionary histories and environmental factors that constrain species' physiological and ecological requirements. Here, we applied a deconstruction approach to map the detailed species richness patterns of Actinopterygian freshwater fishes at the class and order levels and to disentangle their drivers using geographical ranges and a phylogeny, comprising 77% (12 557) of all described species. We jointly evaluated seven evolutionary and ecological hypotheses posited to explain the LDG: diversification rate, time for speciation, species–area relationship, environmental heterogeneity, energy, temperature seasonality and past temperature stability. We found distinct diversity gradients across orders, including expected, bimodal and inverse LDGs. Despite these differences, the positive effect of evolutionary time explained patterns for all orders, where species-rich regions are inhabited by older species compared to species-poor regions. Overall, the LDG of each order has been shaped by a unique combination of factors, highlighting the importance of performing a joint evaluation of evolutionary, historical and ecological factors at different taxonomic levels to reach a comprehensive understanding on the causes driving global species richness patterns.
No phylogenetic evidence for angiosperm mass extinction at the Cretaceous–Palaeogene (K-Pg) boundary

The Cretaceous–Palaeogene mass extinction event (K-Pg) witnessed upwards of 75% of animal species going extinct, most notably among these are the non-avian dinosaurs. A major question in macroevolution is whether this extinction event influenced the rise of flowering plants (angiosperms). The fossil record suggests that the K-Pg event had a strong regional impact on angiosperms with up to 75% species extinctions, but only had a minor impact on the extinction rates of major lineages (families and orders). Phylogenetic evidence for angiosperm extinction dynamics through time remains unexplored. By analysing two angiosperm mega-phylogenies containing approximately 32 000–73 000 extant species, here we show relatively constant extinction rates throughout geological time and no evidence for a mass extinction at the K-Pg boundary. Despite high species-level extinction observed in the fossil record, our results support the macroevolutionary resilience of angiosperms to the K-Pg mass extinction event via survival of higher lineages.
Investigating the Physiological and Metabolic Requirements of the Tramway Ridge Microbial Community, Mt Erebus, Antarctica

ii ACKNOWLEDGEMENTS . iv TABLE OF CONTENTS . vi LIST OF FIGURES. ix LIST OF TABLES . x 1 LITERATURE REVIEW . 1 1.1 THERMOPHILIC METABOLISM . 1 1.2 THEORY OF THERMOPHILIC PROKARYOTIC ORIGINS . 3 1.3 METHODOLOGIES FOR STUDYING THERMAL ECOSYSTEMS . 4 1.4 CULTURE DEPENDANT TECHNIQUES . 6 1.4. 1 Advances in Culture Dependent Techniques . 6 1.5 CULTURE INDEPENDENT ANALYSIS OF MICROBIAL COMMUNITIES . 10 1.5. 1 Molecular Biomarkers . 10 1.5. 2 DNA Fingerprinting . 12 1.5. 3 16S rRNA Gene Clone Libraries and Sanger Sequencing . 13 1.5. 4 Pyrosequencing . 14 1.6 GEOTHERMAL AREAS . 16 1.6. 1 Geothermal Areas in Antarctica . 17 1.6. 2 Mount Erebus and Tramway Ridge Geothermal Subsurface Soils . 18 1.6. 3 Research on Tramway Ridge Geothermal Soils . 20 1.7 AIMS, APPROACHES AND OUTLINE OF THESIS . 26 1.8 REFERENCES . 28
A Flexible School and College Level Qualification in Data Science

This poster abstract describes the design and development of a high school-level qualification in data science. The qualification has been available for 4 years; 1982 learners have completed the course to date across 30 educational institutions. We describe the structure of the course and its pedagogical principles. We conclude with a set of recommendations for other educators who are designing similar qualifications in other school systems.
Broadening Participation in Computing: Experiences of the Hour of Code in an African Country

To increase participation in formal computer science education in underrepresented regions like Africa, an initiative called CSEdBotswana was launched in Botswana. To take an initial step towards this change, an "Hour of Code" (HoC) event was carried out, engaging 16 secondary schools, over 700 students, 20 teachers, and 20 facilitators. In this paper, we recount our firsthand experiences of organizing the Hour of Code event, with a focus on its impact on students’ attitudes towards programming, as well as the experiences of teachers and facilitators. The results indicate a positive impact on students’ perceived importance of programming, engagement, and learning but no significant impact on their interest in pursuing programming. The feedback from teachers and facilitators underlines the potential of Hour of Code as an educational tool, while also highlighting the requirement for more resources and teacher expertise. This research forms part of a broader study aimed at expanding participation in formal computer science education in a developing country.
Comparison of morphological and physiological parameters of the planting material of Norway spruce (Picea abies [L.] Karst.) from intensive nursery technologies with current bareroot plants.

High quality of planting material is an essential prerequisite for successful artificial forest regeneration. We carried out a detailed investigation aimed at differences between plantable bareroot and container plants of Norway spruce (Picea abies [L.] Karst.). Based on the results of this experiment, there exist marked differences in basic morphological traits between bareroot plants and plugs. The largest differences were observed in root collar diameter and root system volume. Differences in physiological quality (nutrient content, function of assimilatory organs) were also great. The results document that container seedlings of Norway spruce produced by intensive technology in controlled conditions of plastic greenhouses have very good predispositions for successful growth in difficult mountain conditions.
Scaffolding Block Coding Through Multiple Entry Points

A major tenet of Universal Design for Learning (UDL) is providing flexibility and choice. This pilot study investigated a UDL-based approach called multiple entry points for project creation in Scratch as a way of scaffolding learning for block-based programming projects. Allowing student choices for interactions with computer science (CS) learning decreases barriers to entry for all students, especially those with disabilities. Multiple entry points provide varied challenges and scaffolding and aligns with the UDL framework as delineated by CAST [3]. Multiple entry points involve presenting learners with different versions of projects, requiring different kinds of interactions and scaffolds that assist learners in achieving the goals of UDL: Multiple means of engagement, representation, and action & expression - especially those related to comprehension, perception, and language & symbols. The pilot identified that the names given to the options as well as the order of the options impacted learner selections. This information can inform the development of future multiple entry point projects.
Task supply, wage earning, and segmentation among natives and two generations of immigrants in Canada

ABSTRACT The different life paths of the generation following immigration have become a matter of public discussion and scholarly research in the past decades in many migrant-receiving countries. These differences would be key points for the immigration decision made by first-generation immigrants. This paper adopts a new perspective to study the differences in task supplies and economic status between natives and two generations of immigrants to see their different life paths. This paper estimates differences in task supply and earnings between natives and immigrants in 1970 and 2015, which are the beginning and end of the fifth (and current) wave of immigration to Canada. Furthermore, using a three-fold Blinder-Oaxaca decomposition, I link the average weekly wage of workers to their task productivity, and try to find the effects of the returns to tasks as well as different task supplies on the average wage gap between natives and immigrants. Finally, I use ordered probit and logit models to demonstrate and measure the significant effects of immigrant status on an employee’s labour market segment.
MODELING OF SEASONAL TRACE GAS AND PARTICULATE EMISSIONS FROM VEGETATION FIRES IN SOUTHERN AFRICA

Title of dissertation: MODELING OF SEASONAL TRACE GAS AND PARTICULATE EMISSIONS FROM VEGETATION FIRES IN SOUTHERN AFRICA Stefania Korontzi, Doctor of Philosophy, 2004 Dissertation directed by: Professor Christopher O. Justice Department of Geography Fire is widespread in southern African savannas with important implications for tropical and global atmospheric chemistry. However, previous regional emission studies have not fully accounted for the variability of the emissions throughout the burning season and the associated impacts on emissions quantification. The main aim of this study is to address this gap. The complexity of the emissions process is described using a spatially and temporally explicit modeling approach that integrates recently published satellite-driven fuel load amounts, satellite burned area products, and empirically derived parameterizations of combustion completeness and emission factors. To represent fire behavior characteristics, land cover is classified into grasslands and woodlands, using a satellite-derived percent tree cover product. The combustion completeness is modeled as a function of grass fuel moisture and the emission factors as a function of grass fuel moisture in grasslands and fuel mixture in woodlands. Fuel moisture is derived from a fuel load model and by using satellite vegetation index time series. A sensitivity analysis with respect to three satellite burned area products reveals large differences in emissions due to differences in their amounts and spatial distribution. The analysis at the regional scale shows, that early burning in grasslands may lead to higher amounts of products of incomplete combustion despite the lower amounts of fuel consumed, compared with late dry season burning. In contrast, early burning in woodlands results in lower emissions because less fuel gets consumed. These seasonal emissions trends become more pronounced when the fuels are wetter. Burning in woodlands dominates the regional emissions budgets. Emissions estimates for various atmospheric species, many of which are modeled for the first time, are reported and compared with other regional sources of pyrogenic emissions and global biomass burning and fossil fuel emissions. The modeled estimates for 2000 are (in Tg): 537 CO2, 23.2 CO, 0.726 CH4, 0.661 NMHC, 2.4 particulates (< 2.5 μm), 1.0 NOx and account for significant fractions of regional emissions from all pyrogenic sources. Especially high is the previously undetermined contribution of Oxygenated Volatile Organic Compounds (1.8 Tg). The methodology and results have direct implications for national reporting of savanna fire emissions. MODELING OF SEASONAL TRACE GAS AND PARTICULATE EMISSIONS FROM VEGETATION FIRES IN SOUTHERN AFRICA
Nutrient availability influences E. coli biofilm properties and the structure of purified curli amyloid fibers

Bacterial biofilms are highly adaptable and resilient to challenges. Nutrient availability can induce changes in biofilm growth, biomass, morphology, architecture and mechanical properties. Bacterial extracellular matrix plays a major role in achieving biofilm stability under different environmental conditions. Curli amyloid fibers are determining for the architecture and stiffness of E. coli biofilms, but how this major matrix component adapts to different environmental cues remains unclear. Here, we investigated for the first time the effect of nutrient availability on both i) biofilm materials properties and ii) the structure and properties of curli amyloid fibers extracted from the biofilms. For this, we cultured E. coli W3110, which main matrix component is curli fibers. We quantified the size, mass and water content of the resulting biofilms and estimated their mechanical properties by microindentation. The curli amyloid fibers were then purified from the biofilms and their molecular structure and properties were studied by spectroscopic techniques. Our results show that the availability of nutrients in the substrate influences the yield of curli fibers, their structural composition and chemical stability, and suggest that these molecular features contribute to the stiffness of the biofilms. Biofilms grown on substrates with high nutrient concentration are softer, contain less curli fibers, and these fibers exhibit low β-sheet content and chemical stability. Our multiscale study sheds new light on the relationship between the molecular structure of bacterial matrix and the macroscopic properties of biofilms. This knowledge will benefit the development of both anti-biofilm strategies and biofilm-based materials. Graphical abstract
Dual Roles of the Conditional Exosomes Derived from Pseudomonas aeruginosa Biofilms: Promoting and Inhibiting Bacterial Biofilm Growth

Antibiotic-resistant biofilm infections have emerged as public health concerns because of their enhanced tolerance of high-dose antibiotic treatments. The biofilm life cycle involves multiple developmental stages, which are tightly regulated by active cell-cell communication via specific extracellular signal messengers such as exosomes. This study was aimed at exploring the roles of Pseudomonas aeruginosa exosomes secreted at different developmental stages in controlling biofilm growth. Our results show that exosomes secreted by P. aeruginosa biofilms during their exponential growth phase (G-Exo) enhance biofilm growth. In contrast, exosomes secreted by P. aeruginosa biofilms during their death/survival phase (D-Exo) can effectively inhibit/eliminate P. aeruginosa PAO1 biofilms up to 4.8-log10 CFU/cm2. The inhibition effectiveness of D-Exo against P. aeruginosa biofilms grown for 96 hours improved further in the presence of 10-50 μM Fe3+ ions. Proteomic analysis suggests the inhibition involves an iron-dependent ferroptosis mechanism. This study is the first to report the functional role of bacterial exosomes in bacterial growth, which depends on the developmental stage of the parent bacteria. The finding of D-Exo-activated ferroptosis-based bacterial death may have significant implications for preventing antibiotic resistance in biofilms. Significance statement Antibiotic-resistant bacterial infections caused 1.27 million deaths in 2019 [1], and this number is projected to increase to 10 million deaths annually worldwide by 2050 [2]. Of these infections, up to 80% are caused by biofilm-associated infections [3, 4], which pose a significant challenge to human health. The treatment of biofilm infections remains a formidable problem because of the limited effectiveness of the currently available antibiotics against drug-resistant biofilms [5, 6]. The development of new therapeutic approaches that can effectively combat biofilm infections is required. This study represents a promising solution to antibiotic-resistant biofilm infections. The successful use of exosomes against biofilms opens new possibilities for combating challenging antibiotic-resistant biofilm infections.
Loop extrusion by cohesin plays a key role in enhancer-activated gene expression during differentiation

Enhancers and their target promoters often come into close physical proximity when activated. This proximity may be explained by a variety of mechanisms; most recently via cohesin-mediated chromatin loop extrusion. Despite this compelling hypothesis, acute depletion of cohesin does not cause widespread changes in gene expression. We have tested the role of cohesin-mediated loop extrusion on gene expression at the mouse alpha-globin locus during erythropoiesis. Acute depletion of cohesin downregulates alpha-globin expression at early but not late stages of differentiation. When single or multiple CTCF sites are placed between the alpha-globin enhancers and promoters, alpha-gene expression is downregulated. Importantly, the orientation of the CTCF site plays a critical role, suggesting that within this activated domain, cohesin predominantly but not exclusively translocates from the enhancers to the promoters. We find that loop extrusion does play an important role in establishing enhancer-promoter proximity and consequent expression of inducible genes during differentiation.
Pruning Ternary Quantization

Inference time, model size, and accuracy are three key factors in deep model compression. Most of the existing work addresses these three key factors separately as it is difficult to optimize them all at the same time. For example, low-bit quantization aims at obtaining a faster model; weight sharing quantization aims at improving compression ratio and accuracy; and mixed-precision quantization aims at balancing accuracy and inference time. To simultaneously optimize bit-width, model size, and accuracy, we propose pruning ternary quantization (PTQ): a simple, effective, symmetric ternary quantization method. We integrate L2 normalization, pruning, and the weight decay term to reduce the weight discrepancy in the gradient estimator during quantization, thus producing highly compressed ternary weights. Our method brings the highest test accuracy and the highest compression ratio. For example, it produces a 939kb (49$\times$) 2bit ternary ResNet-18 model with only 4\% accuracy drop on the ImageNet dataset. It compresses 170MB Mask R-CNN to 5MB (34$\times$) with only 2.8\% average precision drop. Our method is verified on image classification, object detection/segmentation tasks with different network structures such as ResNet-18, ResNet-50, and MobileNetV2.
Human Brain Dynamics Dissociate Early Perceptual and Late Motor-Related Stages of Affordance Processing

Affordances, the opportunity for action offered by the environment to an agent, are vital for meaningful behavior and exist in every interaction with the environment. There is an ongoing debate in the field about whether the perception of affordances is an automated process. Some studies suggest that affordance perception is an automated process that is independent from the visual context and bodily interaction with the environment, while others argue that it is modulated by the visual and motor context in which affordances are perceived. The present paper aims to resolve this debate by examining affordance automaticity from the perspective of sensorimotor time windows. We replicated a previous study on affordance perception in which participants actively moved through doors of different width in immersive 3D virtual environments. To investigate the impact of different forms of bodily interactions with an environment, i.e., the movement context (physical vs. joystick movement), we used the identical virtual environment from Djebbara and colleagues (2019) but displayed it on a 2D screen with participants moving through different wide doors using the keys on a standard keyboard. We compared components of the event-related potential (ERP) from the continuously recorded electroencephalogram (EEG) that were previously reported to be related to affordance perception of architectural transitions (passable and impassable doors). Comparing early sensory and later motor-related ERPs, our study replicated ERPs reflecting early affordance perception but found differences in later motor-related components. These results indicate a shift from automated perception of affordances during early sensorimotor time windows to movement context dependence of affordance perception at later stages suggesting that affordance perception is a dynamic and flexible process that changes over sensorimotor stages.
The anti-SARS-CoV-2 BNT162b2 vaccine suppresses mithramycin-induced erythroid differentiation and expression of embryo-fetal globin genes in human erythroleukemia K562 cells

The COVID-19 severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) the ongoing coronavirus disease 2019 (COVID-19) pandemic. The SARS-CoV-2 Spike protein (S-protein) plays an important role in the early phase of SARS-CoV2 infection through efficient interaction with ACE2. The S-protein is produced by RNA-based COVID-19 vaccines, and has been hypothesized to be responsible for damaging cells of several tissues and for some important side effects of RNA-based COVID-19 vaccines. The aim of this study was to verify the effect of the BNT162b2 vaccine on erythroid differentiation of the human K562 cell line, that has been in the past intensively studied as a model system mimicking some steps of erythropoiesis. We found that the BNT162b2 vaccine suppresses mithramycin-induced erythroid differentiation of K562 cells. Reverse-transcription-PCR and Western blotting assays demonstrated that suppression of erythroid differentiation was associated with sharp inhibition of the expression of α-globin and γ-globin mRNA accumulation. Inhibition of accumulation of ζ-globin and ε-globin mRNAs was also observed. In addition, we provide in silico studies suggesting a direct interaction between SARS-CoV-2 Spike protein and Hb Portland, that is the major hemoglobin produced by K562 cells. This study thus provides information suggesting the need of great attention on possible alteration of hematopoietic parameters following SARS-CoV-2 infection and/or COVID-19 vaccination.
Several fitness functions and entanglement gates in quantum kernel generation

Quantum machine learning (QML) represents a promising frontier in the quantum technologies. In this pursuit of quantum advantage, the quantum kernel method for support vector machine has emerged as a powerful approach. Entanglement, a fundamental concept in quantum mechanics, assumes a central role in quantum computing. In this paper, we investigate the optimal number of entanglement gates in the quantum kernel feature maps by a multi-objective genetic algorithm. We distinct the fitness functions of genetic algorithm for non-local gates for entanglement and local gates to gain insights into the benefits of employing entanglement gates. Our experiments reveal that the optimal configuration of quantum circuits for the quantum kernel method incorporates a proportional number of non-local gates for entanglement. The result complements the prior literature on quantum kernel generation where non-local gates were largely suppressed. Furthermore, we demonstrate that the separability indexes of data can be leveraged to estimate the number of non-local gates required for the quantum support vector machine's feature maps. This insight can be helpful in selecting appropriate parameters, such as the entanglement parameter, in various quantum programming packages like https://qiskit.org/ based on data analysis. Our findings offer valuable guidance for enhancing the efficiency and accuracy of quantum machine learning algorithms.