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A Novel Bayesian Probabilistic Approach for Debris Flow Accumulation Volume Prediction Using Bayesian Neural Networks with Synthetic and Real-World Data Integration
No full textDebris flow events are complex natural phenomena that are challenging to predict, especially when data are limited or uncertain. This study presents a novel probabilistic approach using Bayesian Neural Networks (BNN) to predict possible volumes of debris flow accumulation by using synthetic and real-world data. Synthetic datasets are created based on statistical distributions informed by geomorphological and hydrological knowledge, allowing the model to learn typical behaviors when real data is scarce. BNN provide uncertainty quantification by modeling neural weights as probability distributions. The model resulting from validation on synthetic data and two real datasets from China and South Korea show strong predictive performance (R2 > 0.98) and close alignment between predicted and observed volumes, even in the presence of outliers. The key strength of this integrated approach lies in its integration of synthetic data generation, real data augmentation based on Bootstrapping, expert knowledge and Bayesian deep learning to overcome limitations of traditional statistical models, improving debris flow forecasting and enabling more informed and resilient risk management strategies
Cation Tuning of Polaron Barriers in Layered Perovskites for Optical Spin Lifetime Control
No full textLayered metal-halide perovskites (L-MHPs) form self-assembled quantum wells with strongly bound excitons and electron–phonon interactions that promote polaron formation. Due to spin–orbit coupling and Rashba-type spin-splitting of the electronic bands, spin-polarized excitons can be photoexcited with circularly polarized light, making these materials promising in opto-spintronics. Recently, we have shown that photoexcitation with excess energy extends spin-lifetimes in (BA)2FAPb2I7by over 2 orders of magnitude compared to resonant excitation and attributed this to polaron formation. Here, we study spin-lifetimes in L-MHPs with different A-site cations: (Hexa)2MAPb2I7, (Hexa)2FAPb2I7, (Hexa)2CsPb2I7(Hexa: hexylammonium, MA: methylammonium, FA: formamidinium, Cs: cesium). We find that all studied materials exhibit vastly extended spin-lifetimes under excess-energy excitation, but that the polaron formation barrier is reduced with increasing polarity of the A-site cations. First-principles calculations show that (Hexa)2MAPb2I7has the most stable polarons and (Hexa)2CsPb2I7, the least. Our findings demonstrate tuning of optically controlled exciton spin-lifetimes in L-MHPs through composition engineering, providing a pathway toward optimized materials for spintronics
Rational optimization of D3R/GSK-3β dual target-directed ligands as potential treatment for bipolar disorder: Design, synthesis, X-ray crystallography, molecular dynamics simulations, in vitro ADME, and in vivo pharmacokinetic studies
No full textBipolar disorder is a complex neuropsychiatric condition with a significant unmet medical need, as current treatments lack disease-modifying properties and multimodal therapeutic effects. To overcome the limitations of single-target drugs, we designed dual-target ligands that combine partial agonism at the dopamine D3 receptor (D3R) with inhibition of glycogen synthase kinase-3β (GSK-3β). We previously identified ARN24161 (1) as a promising prototype, demonstrating partial agonism at D3R (EC50 = 10.1 nM, % Eff. = 26.3) and GSK-3β inhibition (IC50 = 561 nM). However, its drug-like properties remained suboptimal. To optimize this compound, we initiated a multidisciplinary refinement campaign, leveraging computational modeling and crystallographic data to fine-tune the balance between D3R and GSK-3β activity, reduce P-glycoprotein (P-gp) affinity, and improve the pharmacokinetic profile. This effort led to the identification of ARN25297 (5), a moderately balanced dual-target ligand that exhibits partial agonism at D3R (EC50 = 13.1 nM, % Eff. = 17.1) and potent GSK-3β inhibition (IC50 = 47.0 nM). Notably, ARN25657 (16) emerged as the most well-balanced candidate, demonstrating enhanced D3R partial agonism (EC50 = 15.2 nM, % Eff. = 37.7) alongside strong GSK-3β inhibition (IC50 = 19.3 nM). Compound 16 also exhibited the lowest P-gp inhibition and significant improvements in in vitro ADME properties compared to prototype 1, while maintaining a balanced dual target profile. Although the PK profile of 16 remained comparable to that of prototype 1, these findings lay the groundwork for further lead optimization and structural refinement, driving future in vivo proof-of-concept toward innovative therapeutic strategies for bipolar disorder and related neuropsychiatric conditions
Use of Ozone for Disinfection of PHARMODUCT® Automatic System for Antineoplastic Compounding
No full textThe influence of dimensions on the complexity of computing decision trees
No full textA decision tree recursively splits a feature space & Ropf;(d) and then assigns class labels based on the resulting partition. Decision trees have been part of the basic machine-learning toolkit for decades. A large body of work considers heuristic algorithms that compute a decision tree from training data, usually aiming to minimize in particular the size of the resulting tree. In contrast, little is known about the complexity of the underlying computational problem of computing a minimum- size tree for the given training data. We study this problem with respect to the number d of dimensions of the feature space & Ropf;(d), which contains n training examples. We show that it can be solved in O(n(2d+1)) time, but under reasonable complexity-theoretic assumptions it is not possible to achieve f(d) & sdot; n(O(d / log d)) running time. The problem is solvable in (dR)(O(dR))& sdot; n(1+o(1) )time if there are exactly two classes and R is an upper bound on the number of tree leaves labeled with the first class
Swinging pressure reducing valve in a real water distribution network: Where is the catch?
No full textTo reduce leakage in water distribution networks, several strategies have been developed, each addressing different aspects of the problem. Alongside advanced leak detection technologies, pressure control has proven to be one of the most powerful and widely implemented strategies to reduce leakage. In this perspective, a key technology in pressure management is the use of pressure reducing valves (PRVs). This paper presents field measurements showing significant instability (swing) of a PRV installed in a real pressure management area in Trieste (Italy). Such instability is characterized by very frequent and significant pressure variations. The various factors influencing this feature are pointed out, finding the catch of the problem and suggesting effective solutions
Understanding Barriers and Developing Facilitators in School reentry for students with medical and mental health needs
No full textThis workshop focuses on strategies for reintegrating students after prolonged school absences due to medical or mental health conditions. It utilizes the WHO’s ICF framework to analyze barriers and facilitators, emphasizing environmental modifications to enhance inclusion and participation. The workshop will present findings from a Delphi study on a School Reentry Model and demonstrate how to adapt strategies for individual learners and systems
The Palette of the Medieval North – a non-invasive investigation of the colourants of ten fragments from Medieval Swedish Manuscripts
No full textThe palette and constituting materials of several medieval parchment fragments coming from books thought to be locally produced in Sweden have, for the first time, been examined by non-invasive methods for chemical and physical characterization. These books were primarily used in medieval Swedish parish churches (including present-day Finland), and they could be said to represent everyday book culture of the time. Ten fragments from the collections of the National Archives of Sweden dated to the 12th to the 15th century were studied by microscopy, hyperspectral imaging in the visible and ultraviolet range, X-ray fluorescence spectrometry, reflectance spectroscopy in the UV, visible and near-infrared range, external reflectance in the mid- and near-infrared and Raman spectroscopy. Pigments, colourants, and inks have been characterized and identified. The aim was to enhance the understanding of these objects and to evaluate the value of technical analysis, the results of which, when combined with historical and palaeographic studies, will advance the comprehension of medieval Nordic book culture. The results reveal the presence of many of the materials commonly used in book production in Europe at the time, such as vermilion, red lead, azurite, orpiment, and copper-based greens, and also some more unusual substances. The colourant components evince significant variation, and it appears likely that they were largely received via trade routes and learned networks from various European locations. The documents from the 12th century differ from the others in their substances and practices, such as the use of ultramarine for calendar rubrics and the varied use of different reds and greens. There is an unusual use of an iron-based red with copper particles for initials, green earth for initials, organics for highlights, and a probable tannin writing ink with neither iron nor carbon
High-resolution satellite observations for developing advanced decision support systems for water resources management in the Po River
No full textThis work presents a prototype of a Decision Support System (DSS) designed for water resources management in the Po River basin, in Italy. A comprehensive Water Resources Management database was constructed by employing high-resolution (1 km/hourly) satellite data and a modular hydrological model capable of simulating both natural and anthropogenic processes within the study area. This database represents the full range of plausible hydrological responses of the study basin to a multitude of climatic and initial state scenarios, providing a comprehensive overview of potential outcomes. The system enables the assessment of the water resources available within the basin, allowing the identification of specific conditions of water stress and, consequently, the transition from a reactive to a proactive water management strategy. The Water Resources Management database can be visualised and queried on the Digital Twin Earth (DTE) platform (https://explorer.dte-hydro.adamplatform.eu/?use_case=5), where it is presented as a user-friendly DSS tool to strive towards informed decision-making approaches in the context of water resources management. Even in its initial form, the Water Resources Management database demonstrated to be a versatile tool, adaptable to a wide range of basins with varying levels of human intervention and different climatic characteristics. The approach benefits from the use of high-resolution satellite data, including precipitation, soil moisture, evaporation and snow depth developed within the framework of the European Space Agency DTE Hydrology and 4DMED-Hydrology projects. Our results demonstrate that high-resolution satellite data is an invaluable tool for reconstructing the hydrological cycle and developing advanced and accurate DSS for water resources management