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Applying variation theory:a challenging case in pre-service teacher education
No full textAlthough research has shown that conducting a learning studya lesson study using variation theory can enhance mathematical knowledge for teaching, the specific role of variation theory in this process remains unclear. The aim of this study was to get more insight in the relation between the use of variation theory and the development of participants' mathematical knowledge for teaching. A team of three pre-service teachers carried out a learning study, as part of a last-year module within mathematics teacher education. Pre-tests, student work and lesson plans were analyzed on how variation theory was applied and how this related to the participants' mathematical knowledge for teaching. Findings suggest that applying key elements of variation theory contributes to aspects of this knowledge, particularly during the first phase of the learning study. However, implementing variation theory in lesson design remains challenging, indicating a need to strengthen the support provided within the learning study module in pre-service teacher education
Implications of biological activated carbon (BAC) filters for pharmaceutical removal from municipal wastewater:A review on its properties, operational factors, and biofilms
No full textConventional domestic wastewater treatment plants (WWTPs) are not currently designed to completely remove organic micro-pollutants (OMPs), specifically pharmaceutical residues, from the water. Biological activated carbon (BAC) filters are applied as a treatment to further remove the residues. This study consists of a systematic review (n = 158) and cross-study comparison (n = 17) from studies published between 2011 and 2025, evaluates the performance of BAC filters for treating secondary WWTP effluent, quantifies the roles of different operational parameters to achieve a higher pharmaceutical removal, and identifies research gaps in understanding BAC filter performance. In total, 77 BAC filter performance data sets were extracted from studies. An increase in EBCT showed significance in removing diclofenac but not for atenolol, carbamazepine, and dissolved organic carbon (DOC). A higher removal of atenolol, carbamazepine, and diclofenac was observed with advanced oxygen oxidation processes (AOPs) pre-treatment to BAC filters, such as ozonation. Other operational parameters, such as physico-chemical characteristics of carbon, aeration, and backwash practice, are also discussed in this review. Future research that could be impactful in BAC filter optimization includes the assessment of microbial activity and its characterization, the role of biofilm, and the effects of influent compositions on the removal of pharmaceutical removal.</p
POMP:Pathology-omics Multimodal Pre-training Framework for Cancer Survival Prediction
No full textCancer survival prediction is an important direction in precision medicine, aiming to help clinicians tailor treatment regimens for patients. With the rapid development of high-throughput sequencing and computational pathology technologies, survival prediction has shifted from clinical features to joint modeling of multi-omics data and pathology images. However, existing multimodal learning methods struggle to effectively learn pathology-omics interactions due to the lack of proper alignment of multimodal data before fusion. In this paper, we propose POMP, a pathology-omics multimodal pre-training framework jointly learned with three training tasks for integrating pathological images and omics data for cancer survival prediction. To better perform cross-modal learning, we introduce a pathology-omics contrastive learning method to align the pathology and omics information. POMP leverages the principle of pre-trained models and explores the benefit of aligning multimodal information from the same patient, achieving state-of-the-art results on six cancer datasets from the Cancer Genome Atlas (TCGA). We also show that our contrastive learning method allows us to exploit the cosine similarity of pathological images and omics data as the survival risk score, which can further boost prediction performance compared with other commonly used methods. The code is available at https://github.com/SuixueWang/POMP.</p
Distributionally Robust and Risk-Averse Model Predictive Control for Motion Planning and Control:Reformulations and Computational Issues
No full textIn this chapter, we focus on a risk-constrained optimal control problem and explore a model predictive control scheme with distributionally robust risk constraints as a solution strategy. The primary objective of such a control problem is to encode a motion planning and control task for an autonomous agent. Considering conditional value-at-risk as the risk metric with ambiguity sets based on the Wasserstein metric and total variation distance, we present various reformulations of the distributionally robust constraints, where the constraint function encodes a collision avoidance condition. We comment on the computational effort in deriving controllers using our schemes and prescribe various approximations. </p
Structural Performance of Novel 3D-Printed Multilayer Sandwich Structures with Bio-Inspired Cellular Architecture
No full textThis experimental research investigates the structural performance of novel 3D-printed multilayer sandwich structures with bio-inspired cellular core configurations under quasi-static out-of-plane compressive load. Specimens were fabricated using the Multi Jet Fusion (MJF) additive manufacturing method with Nylon PA12 and designed with various core geometric configurations to assess their impact on mechanical performance and energy absorption capacity. The experimental results indicate that structural geometry significantly influences the energy absorption efficiency of the proposed novel multilayer sandwich panels. Among the tested configurations, the sample with the rhombic cell shape proved to be the most effective. They distributed stress evenly and deformed gradually, preventing sudden failure or buckling in the core components. Hexagonal cell structures also exhibited significant energy absorption properties, providing an optimal balance between structural strength and weight efficiency. In contrast, square and circular cell shapes were less effective than other cell types, exhibiting lower load-bearing capacity and reduced energy absorption efficiency. These findings demonstrate the potential of the proposed 3D-printed bio-inspired structures to advance the development of lightweight, high-performance solutions for a wide range of engineering applications.</p
Review of Brendan Dooley and Alexander S. Wilkinson (eds.), "Exciting News!: Event, Narration and Impact from Past to Present" (Leiden and Boston: Brill, 2024).
No full textObserver-based detection and isolation of permanent sensor faults in a class of uncertain switched affine systems
No full textThis paper develops a robust fault detection and isolation (FDI) strategy for a class of uncertain continuous-time switched affine systems when the system state is not fully available for measurement, and all system sensors are prone to permanent abrupt bounded faults. The FDI strategy is obtained by designing a number of FDI devices equal to the number of sensors. First, we give linear matrix inequalities conditions to design a bank of full-state Luenberger observers in a pseudo-dedicated scheme with guaranteed S− and L∞ performances to work as residual error generators (REGs). In the sequence, considering an extension of the concepts of weak and strong detectability and novel concepts of weak and strong isolation, residual evaluation functions are defined, and threshold functions are designed considering the gains and parameters obtained in the REG design, taking into consideration the smallest fault magnitude to be detected to achieve a mixed S−/L∞ performance. An Algorithm to determine a piecewise constant threshold function is proposed to obtain less conservative constraints in the optimization problem. Furthermore, parameter-tuning algorithms are proposed to obtain local optima thresholds and REGs to satisfy weak isolation conditions over a range of uncertainties. Finally, a Cuk DC–DC converter is considered to demonstrate the effectiveness of the proposed approach.</p
It’s getting kind of heavy—Linking episodes of sickness presence to changes in fatigue over time
No full textSickness presence-working while being ill-is an episodic goal-directed behavior that depends on health events. Drawing on allostatic load theory, we adopt a temporal perspective to study associations between sickness presence and fatigue both across weeks and within weeks. We theorize that sickness presence episodes are associated with immediate increases in fatigue and that accumulating sickness presence episodes increase within-person fatigue over multiple workweeks. We further examine short-term temporal cycles underlying these long-term trajectories, namely workweek strain and weekend recovery. We expect that the duration of sickness presence episodes is associated with steeper increases in fatigue within person during the workweek and altered patterns of change within person during the weekend. We test our assumptions with a week-level study with 123 employees over 16 consecutive workweeks. Participants reported sickness presence episodes during the week on Fridays and fatigue on Fridays and Mondays. Discontinuous growth models based on 734 weekly self-reports suggest that sickness presence episodes are associated with immediate increases in fatigue and hardly any recovery in the following weeks. Frequent sickness presence episodes contributed to increases in fatigue over time. Longer sickness presence episodes were associated with higher initial levels of fatigue on Mondays and no change in fatigue during the workweek. The duration of sickness presence was unrelated to changes in fatigue during weekends. In summary, our study provides a more precise description of how between-person differences in fatigue, as reported in the literature, may emerge from discrete sickness presence episodes. (PsycInfo Database Record (c) 2025 APA, all rights reserved).</p