Miracle-dz/UniFAR-FTUs huggingface dataset:
Deep Gaussian processes and variational propagation of uncertainty

Uncertainty propagation across components of complex probabilistic models is vital for improving regularisation. Unfortunately, for many interesting models based on non-linear Gaussian processes (GPs), straightforward propagation of uncertainty is computationally and mathematically intractable. This thesis is concerned with solving this problem through developing novel variational inference approaches. From a modelling perspective, a key contribution of the thesis is the development of deep Gaussian processes (deep GPs). Deep GPs generalise several interesting GP-based models and, hence, motivate the development of uncertainty propagation techniques. In a deep GP, each layer is modelled as the output of a multivariate GP, whose inputs are governed by another GP. The resulting model is no longer a GP but, instead, can learn much more complex interactions between data. In contrast to other deep models, all the uncertainty in parameters and latent variables is marginalised out and both supervised and unsupervised learning is handled. Two important special cases of a deep GP can equivalently be seen as its building components and, historically, were developed as such. Firstly, the variational GP-LVM is concerned with propagating uncertainty in Gaussian process latent variable models. Any observed inputs (e.g. temporal) can also be used to correlate the latent space posteriors. Secondly, this thesis develops manifold relevance determination (MRD) which considers a common latent space for multiple views. An adapted variational framework allows for strong model regularisation, resulting in rich latent space representations to be learned. The developed models are also equipped with algorithms that maximise the information communicated between their different stages using uncertainty propagation, to achieve improved learning when partially observed values are present. The developed methods are demonstrated in experiments with simulated and real data. The results show that the developed variational methodologies improve practical applicability by enabling automatic capacity control in the models, even when data are scarce.
Racial and Ethnic Differences in Longevity Perceptions and Implications for Financial Decision-Making

Inaccurate perceptions regarding life expectancy can lead to suboptimal financial decisions with long-term consequences, including undersaving prior to retirement, and overspending during retirement. As prior research suggests that Covid-19 mortality has disproportionately harmed those with low incomes, African Americans, and Hispanics in the United States, we seek to determine whether subjective survival perceptions among these groups changed in a manner consistent with observed outcomes. We fielded two online experimental surveys of US residents: one took place early in the pandemic outbreak, and the second, a year later. Using vignettes, we examine whether minorities’ perceptions regarding longevity at the outbreak were consistent with observed reality, and how these compared to members of the white majority population. Furthermore, the panel aspect of our study enables us to test whether and how these perceptions updated over time during the pandemic. Finally, we show how these perceptions related to advice regarding retirement saving and drawdowns.
Non‐linearity in event runoff generation in a small agricultural catchment

Understanding the role of soil moisture and other controls in runoff generation is important for predicting runoff across scales. This paper aims to identify the degree of non‐linearity of the relationship between event peak runoff and potential controls for different runoff generation mechanisms in a small agricultural catchment. The study is set in the 66 ha Hydrological Open Air Laboratory, Austria, where discharge was measured at the catchment outlet and for 11 sub‐catchments or hillslopes with different runoff generation mechanisms. Peak runoff of 73 events was related to three potential controls: event precipitation, soil moisture and groundwater levels. The results suggest that the hillslopes dominated by ephemeral overland flow exhibit the most non‐linear runoff generation behaviour for its controls; runoff is only generated above a threshold of 95% of the maximum soil moisture. Runoff generation through tile drains and in wetlands is more linear. The largest winter and spring events at the catchment outlet are caused by runoff from hillslopes with shallow flow paths (ephemeral overland flow and tile drainage mechanisms), while the largest summer events are caused by other hillslopes, those with deeper flow paths or with saturation areas throughout the year. Therefore, the response of the entire catchment is a mix of the various mechanisms, and the groundwater contribution makes the response more linear. The implications for hydrological modelling are discussed.
The Pyla-1 Natural Accession of Arabidopsis thaliana Shows Little Nitrate-Induced Plasticity of Root Development

Optimizing root system architecture is a strategy for coping with soil fertility, such as low nitrogen input. An ample number of Arabidopsis thaliana natural accessions have set the foundation for studies on mechanisms that regulate root morphology. This report compares the Columbia-0 (Col-0) reference and Pyla-1 (Pyl-1) from a coastal zone in France, known for having the tallest sand dune in Europe. Seedlings were grown on vertical agar plates with different nitrate concentrations. The lateral root outgrowth of Col-0 was stimulated under mild depletion and repressed under nitrate enrichment. The Pyl-1 produced a long primary root and any or very few visible lateral roots across the nitrate supplies. This could reflect an adaptation to sandy soil conditions, where the primary root grows downwards to the lower strata to take up water and mobile soil resources without elongating the lateral roots. Microscopic observations revealed similar densities of lateral root primordia in both accessions. The Pyl-1 maintained the ability to initiate lateral root primordia. However, the post-initiation events seemed to be critical in modulating the lateral-root-less phenotype. In Pyl-1, the emergence of primordia through the primary root tissues was slowed, and newly formed lateral roots stayed stunted. In brief, Pyl-1 is a fascinating genotype for studying the nutritional influences on lateral root development.
English teaching in Colombian rural schools: Challenges and opportunities

This qualitative multiple case study reports the perceptions of education stakeholders about English teaching in rural areas of one of Colombia’s regions: Quindío. The participants of this investigation belong to the academic community (teachers, principals, coordinators, the bilingual coordinator of the region, and pedagogical staff) of different institutions in rural areas. Through in-depth interviews, observations, and focus groups, it was possible to identify the challenges that still persist in rural contexts regarding language teaching and the opportunities this region has had, thanks to the introduction of new initiatives whose main goal is to strengthen English learningteaching processes. Amongst the challenges, rural institutions still need major investment in resources and training; and there is a call for continuity of the projects being implemented. As for the opportunities, it is evident that better progress can be reached in all processes when education stakeholders’ voices are heard.
Conveyor-Less Urban-Car Assembly Factory with VaaC and Matrix System

The advent of autonomous electric vehicles (AEVs) will give drivers time and space instead of focusing on driving. Because of this, some drivers may want to personalize their car for their work, while others may want to customize their vehicle space to be more suitable for relaxation, which will accelerate the megatrend of mass individualization. However, the production of individualized cars faces several challenges. For example, since high-level automation during individualized car production is difficult, a stable skilled labor supply is essential, low-volume/high-variety production is required, and customer proximity or involvement is also important. These conditions can be satisfied by building a car assembly plant in an urban area. The problem is that urban areas are often spatially and environmentally constrained. However, it is be possible to overcome these urban limitations by implementing a conveyor-less micro factory. The objective of this study is to propose a new iterative matrix-system layout design method that can realize a conveyor-less urban car assembly factory with two technologies—VaaC (vehicle as a conveyor) and matrix assembly system. VaaC consists of three novel ideas: sensor skid, safety-sensor guidance system, and vehicle-powered devices, and this paper views each of them in detail. The proposed iterative matrix-system layout design method consists of four steps: (1) layout refinement, (2) simulation, (3) cost analysis, and (4) optimization check, and will examine how each step is performed through simple examples. The authors hope that this paper will arouse interest and provide elements to spur future research on the conveyor-less urban car assembly system.
Visualizing Laguerre polynomials as a complete orthonormal set for the inner product space ℙ n

This linear algebra note offers teaching and learning ideas in the treatment of the orthonormal Laguerre polynomials as vectors of the inner product space with the associated improper integral inner product in a DGS (Dynamic Geometry Software)-MATLAB facilitated learning environment. The proposed learning module demonstrates creative ways of integrating DGS-MATLAB technology into various properties of the integral inner products of Laguerre polynomials along with other notions inherent in the inner product space, such as Triangle Inequality, Pythagorean Theorem, Parallelogram Law, Orthogonality and Orthonormality, Coordinates Relative to an Orthonormal Basis, and Parseval’s Identity.
Marker-Trait Associations for Total Carotenoid Content and Individual Carotenoids in Durum Wheat Identified by Genome-Wide Association Analysis

Yellow pigment content is one of the main traits considered for grain quality in durum wheat (Triticum turgidum L.). The yellow color is mostly determined by carotenoid pigments, lutein being the most abundant in wheat endosperm, although zeaxanthin, α-carotene and β-carotene are present in minor quantities. Due to the importance of carotenoids in human health and grain quality, modifying the carotenoid content and profile has been a classic target. Landraces are then a potential source for the variability needed for wheat breeding. In this work, 158 accessions of the Spanish durum wheat collection were characterized for carotenoid content and profile and genotyped using the DArTSeq platform for association analysis. A total of 28 marker-trait associations were identified and their co-location with previously described QTLs and candidate genes was studied. The results obtained confirm the importance of the widely described QTL in 7B and validate the QTL regions recently identified by haplotype analysis for the semolina pigment. Additionally, copies of the Zds and Psy genes on chromosomes 7B and 5B, respectively, may have a putative role in determining zeaxanthin content. Finally, genes for the methylerythritol 4-phosphate (MEP) and isopentenyl diphosphate (IPPI) carotenoid precursor pathways were revealed as additional sources of untapped variation for carotenoid improvement.
Principal Stratification Approach to Broken Randomized Experiments

The precarious state of the educational system in the inner cities of the United States, as well as its potential causes and solutions, have been popular topics of debate in recent years. Part of the difficulty in resolving this debate is the lack of solid empirical evidence regarding the true impact of educational initiatives. The efficacy of so-called “school choice” programs has been a particularly contentious issue. A current multimillion dollar program, the School Choice Scholarship Foundation Program in New York, randomized the distribution of vouchers in an attempt to shed some light on this issue. This is an important time for school choice, because on June 27, 2002 the U.S. Supreme Court upheld the constitutionality of a voucher program in Cleveland that provides scholarships both to secular and religious private schools. Although this study benefits immensely from a randomized design, it suffers from complications common to such research with human subjects: noncompliance with assigned “treatments” and missing data. Recent work has revealed threats to valid estimates of experimental effects that exist in the presence of noncompliance and missing data, even when the goal is to estimate simple intention-to-treat effects. Our goal was to create a better solution when faced with both noncompliance and missing data. This article presents a model that accommodates these complications that is based on the general framework of “principal stratification” and thus relies on more plausible assumptions than standard methodology. Our analyses revealed positive effects on math scores for children who applied to the program from certain types of schools—those with average test scores below the citywide median. Among these children, the effects are stronger for children who applied in the first grade and for African-American children.
Risky-Driving-Image Recognition Based on Visual Attention Mechanism and Deep Learning

Risky driving behavior seriously affects the driver’s ability to react, execute and judge, which is one of the major causes of traffic accidents. The timely and accurate identification of the driving status of drivers is particularly important, since drivers can quickly adjust their driving status to avoid safety accidents. In order to further improve the identification accuracy, this paper proposes a risky-driving image-recognition system based on the visual attention mechanism and deep-learning technology to identify four types of driving status images including normal driving, driving while smoking, driving while drinking and driving while talking. With reference to ResNet, we build four deep-learning models with different depths and embed the proposed visual attention blocks into the image-classification model. The experimental results indicate that the classification accuracy of the ResNet models with lower depth can exceed the ResNet models with higher depth by embedding the visual attention modules, while there is no significant change in model complexity, which could improve the model recognition accuracy without reducing the recognition efficiency.
Anabasine and Anatabine Exposure Attributable to Cigarette Smoking: National Health and Nutrition Examination Survey (NHANES) 2013–2014

Anabasine and anatabine are minor alkaloids in tobacco products and are precursors for tobacco-specific nitrosamines (TSNAs). The levels of these two compounds have been used to differentiate tobacco product sources, monitor compliance with smoking cessation programs, and for biomonitoring in TSNA-related studies. The concentrations of urinary anabasine and anatabine were measured in a representative sample of U.S. adults who smoked cigarettes (N = 770) during the 2013–2014 National Health and Nutrition Examination Survey (NHANES) study cycle, which was the first cycle where urinary anabasine and anatabine data became available. Weighted geometric means (GM) and geometric least squares means (LSM) with 95% confidence intervals were calculated for urinary anabasine and anatabine categorized by tobacco-use status [cigarettes per day (CPD) and smoking frequency] and demographic characteristics. Smoking ≥20 CPD was associated with 3.6× higher anabasine GM and 4.8× higher anatabine GM compared with smoking <10 CPD. Compared with non-daily smoking, daily smoking was associated with higher GMs for urinary anabasine (1.41 ng/mL vs. 6.28 ng/mL) and anatabine (1.62 ng/mL vs. 9.24 ng/mL). Urinary anabasine and anatabine concentrations exceeded the 2 ng/mL cut point in 86% and 91% of urine samples from people who smoke (PWS) daily, respectively; in comparison, 100% of them had serum cotinine concentrations greater than the established 10 ng/mL cut point. We compared these minor tobacco alkaloid levels to those of serum cotinine to assess their suitability as indicators of recent tobacco use at established cut points and found that their optimal cut point values would be lower than the established values. This is the first time that anabasine and anatabine are reported for urine collected from a U.S. population-representative sample of NHANES study participants, providing a snapshot of exposure levels for adults who smoked during 2013–2014. The results of this study serve as an initial reference point for future analysis of NHANES cycles, where changes in the national level of urinary anabasine and anatabine can be monitored among people who smoke to show the effect of changes in tobacco policy.
On velocity observers for a planar robot subject to non-smooth impacts

The goal of this paper is to compare the performances of two different velocity observers, a full order one and a reduced order one, when used to estimate the velocity vector of a planar robot subject to impacts with the environment, modelled as perfectly rigid. Both the sensitivity of the observers to quantization errors in the position measurements and their behaviour in closed-loop are investigated. Keywords— Mechanical systems, non-smooth impacts, velocity observers.
First molecular confirmation of the fungus Leveillula taurica causing powdery mildew disease on sweet pepper in Iraq

Abstract A study was initiated to investigate powdery mildew disease on pepper during the growing season 2019/2020. Disease incidence scored 73, 85, 80 and 56% in Al-Mahmudiyah, Al-Yusufiyah and Al-Jadriya/Baghdad and Suwaira/Wasit, respectively. Morphological identification revealed L. taurica formed dimorphic conidia, lanceolate primary conidia and cylindrical to clavate secondary conidia. Conidiophores were straight, having short hyaline and unbranched baring single conidiospores. Sequence comparison of ITS region confirmed L. taurica shared 99% maximum nucleotide identity with sequences from South Korea (MH698492.1), Mexico (MG571545.1) and Australia (MT125857.1). To the best of our knowledge, this is the first molecular confirmation of L. taurica infecting pepper in Iraq.
An Integrated Machine Learning Scheme for Predicting Mammographic Anomalies in High-Risk Individuals Using Questionnaire-Based Predictors

This study aimed to investigate the important predictors related to predicting positive mammographic findings based on questionnaire-based demographic and obstetric/gynecological parameters using the proposed integrated machine learning (ML) scheme. The scheme combines the benefits of two well-known ML algorithms, namely, least absolute shrinkage and selection operator (Lasso) logistic regression and extreme gradient boosting (XGB), to provide adequate prediction for mammographic anomalies in high-risk individuals and the identification of significant risk factors. We collected questionnaire data on 18 breast-cancer-related risk factors from women who participated in a national mammographic screening program between January 2017 and December 2020 at a single tertiary referral hospital to correlate with their mammographic findings. The acquired data were retrospectively analyzed using the proposed integrated ML scheme. Based on the data from 21,107 valid questionnaires, the results showed that the Lasso logistic regression models with variable combinations generated by XGB could provide more effective prediction results. The top five significant predictors for positive mammography results were younger age, breast self-examination, older age at first childbirth, nulliparity, and history of mammography within 2 years, suggesting a need for timely mammographic screening for women with these risk factors.
The Determination and Measurement of the Minimal Essentials of Elementary School Geography

In the few attempts that have been made to select minimal eSSCiltials in geography, einphasis has been placed, almost exclusively, on place geography. Minimal place material has been selected ( 1) through the individual judgment of a teacher or geography specialist, (2) through the collective judgment of a number of teachers or geography specialists, (3) through a comparison of the relative emphasis given to certain materials in textbooks of geography, and ( 4) through a study of the frequency with which place names occur in newspapers and magazines. By the individual judgment method there will he as many lists of minimal essentials as there are individuals. By the collective judgment method, a list may be selected that will represent the combined judgments of the group. Since it is largely the work of specialists in geography to determine the content, and of administrators to adopt methods that will insure the mastery of content, the judgment of a group of specialists regarding minimal essentials should he more nearly right than the judgment of a group of teachers. The individual judgment method was used, presumably, by Mr. Thompson1 in his exercises in minimal essentials; and by Superintendent Witham2 in establishing ''A Minimum Standard for Measuring Geography" in the sixth grade, who states that he sought
Antimicrobial and Cytotoxic Cyathane-Xylosides from Cultures of the Basidiomycete Dentipellis fragilis

In our continued search for biologically active metabolites from cultures of rare Basidiomycota species, we found eight previously undescribed cyathane-xylosides from submerged cultures of Dentipellis fragilis, which were named dentifragilins A–H. In addition, the known cyathane derivatives striatal D and laxitextine A were isolated. All compounds were characterized by high-resolution electrospray ionization mass spectrometry (HR-ESIMS) as well as by 1D and 2D nuclear magnetic resonance (NMR) spectroscopy. Several of the compounds exhibited significant activities in standardized cell-based assays for the determination of antimicrobial and cytotoxic effects. The discovery of cyathanes in the genus Dentipellis has chemotaxonomic implications, as this class of diterpenoids has already been shown to be characteristic for mycelial cultures of the related genera Hericium and Laxitextum, which are classified as Dentipellis in the family Hericiaceae.
MAID-Q: Minimizing Tail Latency in Embedded Flash With SMR Disk via -Learning Model

As the mainstream solid-state storage technology, NAND flash has the advantages of tiny size, cost-effective, and high performance, which make it a promising candidate to be embedded into the shingled magnetic recording (SMR) disk to build a faster, denser, and cheaper storage system. However, such an embedded flash with SMR (EF-SMR) disk system suffers from lengthy tail-latency due to “reclamation issues” in both the NAND flash and the SMR disk. Our preliminary observations reveal that tremendous idle time intervals exist in real-world scenarios, and few prior works have focused on addressing the tail-latency issue in the EF-SMR disk. In this article, we propose a novel method termed MAID-Q to fully exploit the idle time intervals to minimize the lengthy tail-latency of the EF-SMR disk based on a lightweight reinforcement learning model (i.e., the $Q$ -learning model). In addition, fine-grained block-level space management and a parallel reclamation strategy are proposed to improve the reclamation efficiency and hide the reclamation overheads. The effectiveness of our proposed design was evaluated with realistic I/O traces, and the results show that the proposed design can remedy the tail-latency by 88.31% and improve the overall performance by 79.03%.