Search Results (10,547)

This paper presents an EPANET pressure-dependent analysis-based method for analyzing bursts in every pipe in a water supply system (WSS) and applies the method to large Finnish WSSs. EPANET is enhanced with the per-junction required and minimum pressures, a flow- and pressure-controlled pump battery component and a full control system model to accurately capture the dynamic behavior of the whole system, including the effect of control system parameters and settings. The results are combined with population and income data, and the correlations of the various physical and hydraulic parameters affecting the burst effects are analyzed. Full article

A method for a real-time now- and forecasting hydraulic and quality simulation model for combined sewer networks, based on an enhanced version of the Storm Water Management Model (SWMM) simulator, with added support for storing the hot start file at any time during the simulation, the rotational speed control of the pumps, multiple dry weather flows with unique patterns, and improvements for quality simulations over control devices is presented. The methodology is applied in the combined sewer network of Helsinki, Finland. The model includes all pipes and dry weather flows, including the pollutants, catchment hydrology, infiltration, snowpacks, and other climate aspects. Full article

Predictive information on plant diseases could help to reduce and optimize the usage of pesticides in agriculture. This research presents classification procedures with linear discriminant analysis to predict three possible severity levels of net blotch in spring barley in Finland. The weather data utilized for classification included mathematical transformations, namely features of outdoor temperature and air humidity with calculated dew point temperature values. Historical field observations of net blotch density were utilized as a target class for the identification of classifiers. The performance of classifiers was analyzed in sliding data windows of two weeks with selected, cumulative, summed feature values. According to classification results from 36 yearly data sets, the prediction of net blotch occurrence in spring barley in Finland can be considered as a linearly separable classification task. Furthermore, this can be achieved with linear discriminant analysis by combining the output probabilities of separate binary classifiers identified for each severity level of net blotch disease. In this case, perfect classification with a resolution of three different net blotch severity levels was achieved during the first 50 days from the beginning of the growing season. This strongly suggests that real-time classification based on a few weather variables measured on a daily basis can be applied to estimate the severity of net blotch in advance. This allows application of the principles of integrated pest management (IPM) and usage of pesticides only when there is a proven need. Full article

Objective: The impact of sex on outcomes following carotid endarterectomy (CEA) and carotid artery stenting (CAS) is not fully elucidated. The aim of this study was to analyze the association between sex and outcomes of asymptomatic patients who underwent primary carotid interventions in France. Methods: This nationwide retrospective study was performed using the French National Health Insurance Information System and included asymptomatic patients who underwent primary carotid intervention over a 10-year period (1 January 2013 to 31 August 2023). Symptomatic patients and patients who had peri-operative neurologic events were excluded. The primary endpoints were the occurrence of death and stroke/transient ischaemic attack (TIA) at 30 days, 1 and 5 years after patients’ discharge. Results: In total, 115,879 patients were admitted for an index CEA (29.4% women) and 6500 for CAS (29.8% women). In the CEA group, no significant sex-related difference was observed for 30-day mortality; however, women had significantly lower 1-year and 5-year mortality rates compared to men (1.9% vs. 2.6%, p < 0.001 and 7.9% vs. 11.1%, p < 0.001). In the CAS group, women had lower 30-day, 1-year and 5-year mortality (0.6% vs. 1.0%, p = 0.040, 3.8% vs. 4.9%, p = 0.048, and 10.4% vs. 15.0%, p < 0.001). A multivariate analysis showed that sex was not associated with the risk of stroke/TIA and mortality at 30 days (OR 0.84 (95% CI 0.67–1.04) and 1.27 (95% CI 0.98–1.64)). Male sex was associated with a higher risk of 1-year and 5-year mortality (OR 1.24 (95% CI 1.13–1.36) and 1.25 (95% CI 1.18–1.31)), but a lower risk of stroke/TIA than female sex. Conclusions: No significant sex-related difference was observed at 30 days in patients being discharged alive and without peri-operative neurologic events. Male sex was associated with a higher risk of mortality but a lower risk of stroke/TIA at 1 and 5 years. Full article

Global climate change’s pervasive impacts extend beyond the environment, significantly affecting mental health across diverse regions. This study offers a comprehensive multi-regional analysis spanning Asia, Africa, Oceania, Europe, and the Americas, addressing three critical gaps in existing research: (i) the necessity of a global scope given climate change’s widespread impact, (ii) the under-researched mental health dimension compared to general health effects, and (iii) the integration of climate and mental health data. Using data from 1970 to 2020, we found a strong correlation between climate change and rising mental disorders globally. Regional patterns emerged, with Asia, Africa, and Oceania showing broader associations with various mental health issues, while Europe and the Americas saw increases in anxiety and depression. This study contributes to a more comprehensive understanding of the interconnectedness between climate change, mental health, and sustainability. By addressing the mental health impacts of climate change, we can identify sustainable solutions that promote both environmental well-being and human well-being. Our findings highlight the urgent need for global action to mitigate climate change’s mental health effects and provide insights for tailored interventions and public health strategies. Additionally, socio-economic factors like unemployment, urbanisation, GDP growth, and globalisation are incorporated to explore the intricate interplay between climate change, mental health, and societal contexts, offering a clearer understanding of the mechanisms at play. Full article

Rock climbing has propelled from niche sport to mainstream free-time activity and Olympic sport. Moreover, climbing can be studied as an example of a high-stakes perception-action task. However, understanding what constitutes an expert climber is not simple or straightforward. As a dynamic and high-risk activity, climbing requires a precise interplay between cognition, perception, and precise action execution. While prior research has predominantly focused on the movement aspect of climbing (i.e., skeletal posture and individual limb movements), recent studies have also examined the climber’s visual attention and its links to their performance. To associate the climber’s attention with their actions, however, has traditionally required frame-by-frame manual coding of the recorded eye-tracking videos. To overcome this challenge and automatically contextualize the analysis of eye movements in indoor climbing, we present deep learning-driven (YOLOv5) hold detection that facilitates automatic grasp recognition. To demonstrate the framework, we examined the expert climber’s eye movements and egocentric perspective acquired from eye-tracking glasses (SMI and Tobii Glasses 2). Using the framework, we observed that the expert climber’s grasping duration was positively correlated with total fixation duration (r = 0.807) and fixation count (r = 0.864); however, it was negatively correlated with the fixation rate (r = −0.402) and saccade rate (r = −0.344). The findings indicate the moments of cognitive processing and visual search that occurred during decision making and route prospecting. Our work contributes to research on eye–body performance and coordination in high-stakes contexts, and informs the sport science and expands the applications, e.g., in training optimization, injury prevention, and coaching. Full article

Alkali activated materials (AAMs) offer significant advantages over traditional materials like Portland cement, but require the use of strong alkaline solutions, which can have negative environmental impacts. This study investigates the synthesis of AAMs using metakaolin and wollastonite, aiming to reduce environmental impact by eliminating sodium silicate and using only sodium hydroxide as an activator. The hypothesis is that wollastonite can provide the necessary silicon for the reaction, with calcium from wollastonite potentially balancing the negative charges usually countered by sodium in the alkaline solution. This study compares raw and carbonated wollastonite (AAM-W and AAM-CW) systems, with raw materials carefully characterized and binding networks analyzed using TGA, FT-IR, and XRD. The results show that while wollastonite can reduce the amount of sodium hydroxide needed, this reduction cannot exceed 50%, as higher substitution levels lead to an insufficiently alkaline environment for the reactions. The carbonation of wollastonite enhances the availability of silicon and calcium, promoting the formation of both N-A-S-H and C-A-S-H gels. Full article

The aviation industry is undergoing electrification due to the increased global focus on reducing emissions in air traffic. Regarding the volatility of raw material prices, one main objective is the increase in the specific power of the motor. This matches the ambitious targets of the CoE project (Center of Excellence) in Finland on high-speed electric motors. The targeted specific power is 20 kW/kg. In this work, motors are designed and optimized for a fully electric regional aircraft. motors with different slot/pole configurations and rotational speed values are studied to determine the advantage of increasing speed in terms of weight reduction. As increasing speed requires the use of a gearbox, the overall weight of the motor and the gearbox is evaluated in post-processing, which allows for determining the impact of high speed on the overall weight. An optimization tool coupled with an electromagnetic and mechanical analysis is used to optimize 1 MW surface mounted permanent magnet synchronous motors (S-PMSMs) for given specifications of regional electric aircraft. Optimization results indicate that there is considerable gain in terms of overall weight only when increasing the speed to the range of 10,000–15,000 rpm. Full article

This research aims to address the limitations inherent in the traditional Extreme Learning Machine (ELM) algorithm, particularly the stochastic determination of input-layer weights and hidden-layer biases, which frequently leads to an excessive number of hidden-layer neurons and inconsistent performance. To augment the neural network’s efficacy in pattern classification, Principal Component Analysis (PCA) is employed to reduce the dimensionality of the input matrix and alleviate multicollinearity issues during the computation of the input weight matrix. This paper introduces an enhanced ELM methodology, designated the PCA-DP-ELM algorithm, which integrates PCA with Double Pseudo-Inverse Weight Determination (DP). The PCA-DP-ELM algorithm proposed in this study consistently achieves superior average classification accuracy across various datasets, irrespective of whether assessed through longitudinal or cross-sectional experiments. The results from both experimental paradigms indicate that the optimized algorithm not only enhances accuracy but also improves stability. These findings substantiate that the proposed methodology exerts a positive influence on pattern classification. Full article

This article is a case study that illustrates the complex intersection of art, politics, and diplomacy in the interwar period. Based on Finnish and Soviet archival documents and press publications, it examines the entire process of organising a Finnish art show abroad. The exhibition, held from 28 November to 24 December 1934, in Moscow, was seen as a landmark event, drawing significant attendance and fostering Finnish–Soviet cultural exchange. By analysing various factors contributing to its success, we provide a detailed picture of both artistic and political influences, demonstrating how cultural events can transcend mere aesthetic appreciation to become significant diplomatic tools. Full article

Several studies proposed relationships linking irradiances in the photosynthetically active radiation (PAR) range and broadband irradiances. A previous study published in 2024 by the same authors proposes a linear model relating clear-sky indices in the PAR and broadband ranges that has been validated in clear and overcast conditions only. The present work extends this study for broken-cloud conditions by using ground-based measurements obtained from the Surface Radiation Budget Network in the U.S.A. mainland. As expected, the clear-sky indices are highly correlated and are linked by affine functions whose parameters depend on the fractional sky cover (FSC), the year, and the site. The previous linear model is also efficient in broken-cloud conditions, with the same level of accuracy as in overcast conditions. When this model is combined with a PAR clear-sky model, the result tends to overestimate the PAR as the FSC decreases, i.e., when fewer and fewer scattered clouds are present. The bias is equal to 1 W m⁻² in overcast conditions, up to 18 W m⁻² when the FSC is small, and 6 W m⁻² when all cloudy conditions are merged. The RMSEs are, respectively, 5, 24, and 15 W m⁻². The linear and the clear-sky models can be combined with estimates of the broadband irradiance from satellites to yield estimates of PAR. Full article

Chitin–glucan (CG) is a new generation of prebiotic. Lactobacillus acidophilus NCFM^® (NCFM) is a probiotic with the ability to decrease abdominal pain. We evaluate the functional and molecular gastrointestinal responses to a synbiotic administration combining CG and NCFM in a rat model of long-lasting colon hypersensitivity. The intracolonic pressure was assessed during the 9-week experiment in animals receiving CG in association or not with NCFM and compared to that in Lacticaseibacillus paracasei Lpc-37^®-treated animals and control rats receiving tap water. The effects of the synbiotic were evaluated using the Wallace score, the quantification of colon myeloperoxidase (MPO) and the master genes driving analgesia and inflammation. CG 1.5 alone and NCFM 10⁹ colony forming units (CFU) alone similarly decreased the visceral pain sensitivity. Lpc-37 had no significant effect. The best profile of pain perception inhibition was obtained with the combination of CG 1.5 g and NCFM 10⁹ CFU, confirming a synbiotic property. This synbiotic treatment significantly reduced macroscopic colonic lesions and MPO concentrations, and induced master genes involved in analgesia (CB1, CB2, MOR, PPARα), with a downregulation of inflammatory cytokines (IL-1β, TNFα) and an induction of IL-10 and PPARγ. In conclusion, CG 1.5 g + NCFM 10⁹ CFU significantly decreased visceral pain perception and intestinal inflammation through the regulation of master genes. Full article

Integrating remote Internet of Things (IoT) laboratories into project-based learning (PBL) in higher education institutions (HEIs) while exploiting the approach of technology-enhanced learning (TEL) is a challenging yet pivotal endeavor. Our proposed approach enables students to interact with an IoT-equipped lab locally and remotely, thereby bridging theoretical knowledge with practical application, creating a more immersive, adaptable, and effective learning experience. This study underscores the significance of combining hardware, software, and coding skills in PBL, emphasizing how IoTRemoteLab (the remote lab we developed) supports a customized educational experience that promotes innovation and safety. Moreover, we explore the potential of IoTRemoteLab as a TEL, facilitating and supporting the understanding and definition of the requirements of remote learning. Furthermore, we demonstrate how we incorporate generative artificial intelligence into IoTRemoteLab’s settings, enabling personalized recommendations for students leveraging the lab locally or remotely. Our approach serves as a model for educators and researchers aiming to equip students with essential skills for the digital age while addressing broader issues related to access, engagement, and sustainability in HEIs. The practical findings following an in-class experiment reinforce the value of IoTRemoteLab and its features in preparing students for future technological demands and fostering a more inclusive, safe, and effective educational environment. Full article