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The difficulty with shale sampling and testing and the lack of pile load tests in shales have created challenges with shale classification, pile resistance prediction, and understanding time-dependent pile responses. Treating shale as soil can yield a conservative pile design. Shales were classified into soil-based and rock-based depending on their weathering conditions, mechanical properties, and measured pile resistances. Failure behaviors of soil- and rock-based shales are discussed. Prediction equations were developed to account for predicting shale properties. Properties of rock-based shales decrease with the increase in weathering. New static analysis (SA) methods were proposed to predict unit shaft resistance ([q.sub.s]) and unit end bearing ([q.sub.b]) of piles in shales and validated. Our study yields higher resistance and efficiency factors for the proposed SA methods and piles in shales than existing SA methods developed for piles in soils. The [q.sub.s] in the soil-based shale exhibits pile setup, while the [q.sub.s] in rock-based shales experience both setup and relaxation. The [q.sub.b] in both soil-based and highly weathered shales is likely to experience pile setup. However, the [q.sub.b] in the moderately and slightly weathered shales experience both setup and relaxation. Key words: driven piles, shale classification, static analysis method, load and resistance factor design, reliability analysis, pile setup and relaxation La difficulty d'echantillonnage et d'essai des schistes et le manque d'essais de charge des pieux dans les schistes ont cree des defis en matiere de classification des schistes, de prediction de la resistance des pieux et de comprehension des reponses des pieux en fonction du temps. En traitant le schiste comme un sol, on peut obtenir une conception conservatrice des pieux. Les schistes ont ete classes en sols et roches en fonction de leurs conditions d'alteration, de leurs proprietes mecaniques et des resistances mesurees des pieux. Les comportements de rupture des schistes a base de sol et de roche sont discutes. Des equations de prediction ont ete developpees pour tenir compte des proprietes previsibles du schiste. Les proprietes des schistes a base de roche diminuent avec l'augmentation de l'alteration. De nouvelles methodes d'analyse statique (SA) ont ete proposees et validees pour predire la resistance unitaire de l'arbre ([q.sub.s]) et l'appui unitaire d'extremite ([q.sub.b]) des pieux dans les schistes. Notre etude donne des facteurs de resistance et d'efficacite plus eleves pour les methodes SA proposees et les pieux dans les schistes que les methodes SA existantes developpees pour les pieux dans les sols. Le [q.sub.s] dans le schiste a base de sol presente une mise en place de la pile, tandis que le [q.sub.s] dans les schistes a base de roche presente a la fois une mise en place et une relaxation. Le [q.sub.b] dans les schistes a base de sol et dans les schistes fortement alteres est susceptible de connaitre une mise en place des piles. Cependant, les [q.sub.b] dans les schistes moderement et legerement alteres connaissent a la fois une mise en place et une relaxation. [Traduit par la Redaction] Mots-cles : pieux battus, classification des schistes, methode d'analyse statique, conception des facteurs de charge et de resistance, analyse de fiabilite, mise en place et relaxation des pieux, Introduction Driven steel piles are an excellent foundation system for shallow bedrock stratigraphy due to their economy and durability. Many states in North America have an extensive distribution of soft [...]

Two predominant methodologies in forecasting temporal processes include traditional time series models and machine learning methods. This paper investigates the impact of time series cross‐validation (TSCV) on both approaches in the context of a case study predicting the incidence of COVID‐19 based on wastewater data. The TSCV framework outlined in the paper begins by engineering interpretable features hypothesized as potential predictors of COVID‐19 incidence. Feature selection and hyperparameter tuning are then utilized with TSCV to identify the best features and hyperparameters for optimal model performance given a specific forecast horizon. While evidence supporting the utility of TSCV for auto‐regressive integrated moving average model with exogenous variables (TS‐ARIMAX) forecasts is lacking in this study, such an approach proves advantageous for gradient boosting machine forecasts (TS‐GBM). In Wyoming, for instance, TS‐GBM had a 34.9% improvement compared to naïve predictions, whereas GBM without TSCV only had a 15.6% improvement. However, TSCV also enhances interpretability for both TS‐ARIMAX and TS‐GBM models as this approach selects specific features, such as lagged values of COVID‐19 cases, based on forecast performance and forecast length. Future research should work to explore the influence of stationarity and model averaging on the performance of TSCV in forecasting applications. [ABSTRACT FROM AUTHOR]

Methodologies are proposed to develop criteria for classifying geomaterials into soils, intermediate geomaterials (IGMs), and hard rocks to achieve efficient driven pile designs. IGMs were categorized into IGM-soils and IGM-rocks to reduce the uncertainties in pile resistance estimations associated with properties ranging from soils to rocks. A boundary between soils and IGM-soils was established based upon the performance of two static analysis methods measured in terms of the coefficients of variation between measured and estimated shaft resistances. A boundary between IGM-rocks and hard rocks was established by limiting the geotechnical resistance in IGM-rocks to the compressive strength of a steel pile. Finally, a geomaterial classification flowchart and sample design charts are proposed to facilitate the classification of geomaterials specifically for the design and construction of driven steel H-piles. The proposed framework can be adapted for other driven pile types. Key words: intermediate geomaterial, classification, rock, pile, foundation. Des methodologies sont proposees pour elaborer des criteres de classification des geomateriaux en sols, les geomateriaux intermediaires (IGM) et roches dures afin d'obtenir des modeles efficaces de pieux fores. Les IGM ont ete categorises en sols IGM et en roches IGM pour reduire les incertitudes dans les estimations de resistance des pieux associees aux proprietes allant des sols jusqu'aux roches. Une limite entre les sols et les sols IGM a ete etablie sur la base du rendement de deux methodes d'analyse statique mesurees en termes de coefficients de variation entre les resistances mesurees et estimees des arbres. Une limite entre les roches IGM et les roches dures a ete etablie en limitant la resistance geotechnique des roches IGM a la resistance a la compression d'un pieu en acier. Enfin, un organigramme de classification des geomateriaux et des diagrammes de plan d'echantillonnage sont proposes pour faciliter la classification des geomateriaux specifiquement pour la conception et la construction des pieux en forme H en acier fore. L'ossature proposee peut etre adaptee a d'autres types de pieux fores. [Traduit par la Redaction] Mots-cles : geomateriau intermediaire, classification, roche, pieux, fondation., Introduction The structural limit state, based on the buckling failure mode, governs the axial capacity (compressive resistance) of piles driven in hard rocks while the geotechnical resistance, based on the [...]

Bayesian methodology continues to be widely used in statistical applications. As a result, it is increasingly important to introduce students to Bayesian thinking at early stages in their mathematics and statistics education. While many students in upper level probability courses can recite the differences in the Frequentist and Bayesian inferential paradigms, these students often struggle using Bayesian methods when conducting data analysis. Specifically, students tend to struggle translating subjective belief to the specification of a prior distribution and the incorporation of uncertainty in the Bayesian inferential approach. The purpose of this paper is to present a hands-on activity involving the Beta-Binomial model to facilitate an intuitive understanding of the Bayesian approach through subjective problem formulation which lies at the heart of Bayesian statistics.

This article focuses on one instructor's evolution from formal lecturing to interactive teaching and learning in a statistics course. Student perception data are used to demonstrate the instructor's use of communication to align the content, students, and instructor throughout the course. Results indicate that the students learned, that communication in the alignment process played a role in the learning, and that the instructor used four key categories of communication: encouraging open communication, demonstrating examples interactively, structuring opportunities for application through problem-solving, and engaging students in reflection about their learning. The article concludes with the instructor's reflections on how communication and the approach to teaching and learning changed as a result of conducting the scholarship of teaching and learning in the course.

In the northern plains of North America, the wetland breeding habitat of amphibians and their populations could be reduced by a change in climate that included decreased precipitation. To test this hypothesis, relative abundance of late-stage tadpoles of the Wood Frog (Lithobates sylvaticus (LeConte, 1825)) was monitored from 1997 to 2010 during a wet-dry-wet cycle in 29 wetlands distributed throughout central Saskatchewan, Canada. The wetlands were dry for up to 7 consecutive years, and for a mean of 3.8 consecutive years. Consequently, tadpole occupancy of the wetlands was reduced to less than 40% for 5 consecutive years and none of the wetlands had tadpoles during the severe drought of 2001 and 2002. However, the drought had no observable long-term effect on either tadpole occupancy of wetlands or tadpole abundance. In 2007, 93% of the wetlands supported tadpoles, and in 2008 the highest mean relative abundance of tadpoles was recorded. Tadpole occupancy of wetlands was related to winter and spring precipitation ([R.sup.2] = 0.84) with 67% of long-term variation in occupancy related to snowfall from November to February and 17% related to rainfall from March to June. Less than 45 mm of winter precipitation for 6 consecutive years would probably cause regional extinction of populations of the Wood Frog. Dans les prairies nordiques d'Amerique du Nord, l'habitat de reproduction et les populations des amphibiens pourraient etre reduits par un changement climatique comportant une diminution des precipitations. Afin de verifier cette hypothese, nous avons suivi l'abondance relative des tetards de derniers stades de la grenouille des bois (Lithobates sylvaticus (LeConte, 1825)) de 1997 a 2010 durant un cycle d'humidite-secheresse-humidite dans 29 terres humides reparties sur l'ensemble du centre de la Saskatchewan, Canada. Les terres humides ont ete assechees pour des periodes de jusqu'a 7 annees consecutives et en moyenne pendant 3,8 annees d'affilee. En consequence, l'utilisation des terres humides par les tetards a ete reduite a moins de 40 % pendant 5 annees de suite et aucune des terres humides ne contenait de tetards durant la grande secheresse de 2001 et 2002. Cependant, la secheresse n'a eu aucun effet observable a long terme ni sur l'utilisation des terres humides par les tetards, ni sur l'abondance de ces tetards. En 2007, 93 % des terres humides contenaient des tetards et en 2008 on a enregistre l'abondance relative la plus elevee de tetards. L'utilisation des terres humides par les tetards est reliee aux precipitations d'hiver et de printemps ([R.sup.2] = 0,84); 67 % de la variation a long terme de l'utilisation s'explique par les chutes de neige entre novembre et fevrier et 17 % par la pluie de mars a juin. Des precipitations d'hiver de moins de 45 mm pendant 6 annees consecutives entraineraient probablement l'extinction regionale des populations de grenouilles des bois. [Traduit par la Redaction], Introduction Climate warming and increased climate variability in the future could reduce the number and seasonal persistence of wetlands in the northern prairies of North America, and thereby reduce the [...]