Transfer learning with graph neural networks for pressure estimation in monitoring-limited water distribution networks.

Water distribution networks (WDNs) constitute essential urban infrastructure, yet their monitoring is hindered by limited monitoring conditions. Soft sensing methods have been applied to estimate pressure at unmonitored nodes using the latest deep learning models, however, they rely on large datasets from the same WDNs for training. There is a critical gap in pressure estimation of WDNs under realistic monitoring limitations.

Mechanical thrombectomy for acute ischemic stroke with simultaneous aorto-iliac occlusion due to cardiac myxoma dislodgement - Case report with review of the literature.

Introduction - Cardiac myxomas are the most common cardiac tumors that can present with a spectrum of clinical manifestations. They are an uncommon cause of cerebral stroke, and simultaneous involvement of the aorto-iliac vessels is extremely rare with 8 cases reported in the literature over the past 10 years. We provide a pictorial illustration of the radiological, surgical, and histopathological findings, which differentiates our case from others in the literature.

Heterogeneous graph neural networks enhance pressure estimation in water distribution networks.

Pressure estimation is crucial for efficient operation and management of water distribution networks (WDNs). However, it is often challenged by limited sensor observations. While graph neural networks (GNNs) have been used to improve hydraulic and water quality predictions of WDNs, their reliance on homogeneous graphs oversimplifies the diverse roles and interactions of hydraulic components, resulting in lower performance under dynamic system states.

Supporting decision-making for industrial symbioses using a hybrid modelling approach and its application to wastewater treatment.

Industrial Symbiosis (InSym) capitalises on the proximity of entities to gain a competitive advantage through collective strategies. Within the Circular Economy, this involves the circular exchange and reuse of water, energy, and resources among participating businesses, enhancing resource valorisation in manufacturing. However, as a distinct business model, InSym requires collaboration among multiple stakeholders working toward a shared goal, posing challenges in achieving mutually beneficial outcomes.

Towards the development of an online platform for an industry metabolic pathway.

This paper presents the design of a web-based decision co-creation platform to showcase water treatment technologies connected via industrial symbiosis for a circular economy approach. The platform is developed as part of the EU H2020-funded ULTIMATE project. This system initially investigates three case studies focusing respectively on: water and nutrient recovery in greenhouses, pre-treatment of wastewater from olive mills before integration into communal wastewater systems, and value-added compound recovery from wastewater in a juice factory.

Enhancing inflow and infiltration detection in urban sewer networks with a new deterministic sensor placement method.

The inflow and infiltration (I&I) is an issue for many urban sewer networks (USNs), which can significantly affect system functioning. Placing sensors within the USNs is a typical approach to detect large I&I event, but deploying a limited number of sensors while achieving maximum detection reliability is challenging. While some methods are available for sensor placement, they are generally heuristic search-based methods (HSBMs) and hence the resultant sensor placement strategies (SPSs) are variable over different algorithm runs or parameterizations.

Making Waves: Towards data-centric water engineering.

Artificial intelligence (AI) is expected to transform many scientific disciplines, with the potential to significantly accelerate scientific discovery. This perspective calls for the development of data-centric water engineering to tackle water challenges in a changing world. Building on the historical evolution of water engineering from empirical and theoretical paradigms to the current computational paradigm, we argue that a fourth paradigm, i.

Economic assessment of nature-based solutions to reduce flood risk and enhance co-benefits.

Flooding is expected to increase due to climate change, urbanisation, and land use change. To address this issue, Nature-Based Solutions (NBSs) are often adopted as innovative and sustainable flood risk management methods. Besides the flood risk reduction benefits, NBSs offer co-benefits for the environment and society.

Poisson rectangular pulse (PRP) model establishment based on uncertainty analysis of urban residential water consumption patterns.

The commonly used Poisson rectangular pulse (PRP) model, employed for simulating high-resolution residential water consumption patterns (RWCPs), relies on calibration via medium-resolution RWCPs obtained from practical measurements. This introduces inevitable uncertainty stemming from the measured RWCPs, which consequently impacts the precision of model simulations. Here we enhance the accuracy of the PRP model by addressing the uncertainty of RWCPs.

Machine Learning for Detecting Virus Infection Hotspots Via Wastewater-Based Epidemiology: The Case of SARS-CoV-2 RNA.

Wastewater-based epidemiology (WBE) has been proven to be a useful tool in monitoring public health-related issues such as drug use, and disease. By sampling wastewater and applying WBE methods, wastewater-detectable pathogens such as viruses can be cheaply and effectively monitored, tracking people who might be missed or under-represented in traditional disease surveillance. There is a gap in current knowledge in combining hydraulic modeling with WBE.

Service-lines as major contributor to water quality deterioration at customer ends.

Biofilm detachment contributes to water quality deterioration. However, the contributions of biofilm detachment from different pipes have not been quantified or compared. Following the introduction of partial reverse osmosis (RO) in drinking water production, this study analyzed particles at customers' ends and tracked their origins to water distribution mains and service lines.

Failure Conditions Assessment of Complex Water Systems Using Fuzzy Logic.

Climate change, energy transition, population growth and other natural and anthropogenic impacts, combined with outdated (unfashionable) infrastructure, can force Dam and Reservoir Systems (DRS) operation outside of the design envelope (adverse operating conditions). Since there is no easy way to redesign or upgrade the existing DRSs to mitigate against all the potential failure situations, Digital Twins (DT) of DRSs are required to assess system's performance under various what-if scenarios. The current state of practice in failure modelling is that failures (system's not performing at the expected level or not at all) are randomly created and implemented in simulation models.

An Analysis of SARS-CoV-2 in Wastewater to Evaluate the Effectiveness of Nonpharmaceutical Interventions against COVID-19 in The Netherlands.

Wastewater-based epidemiology (WBE) is increasingly being recognized as a powerful tool for detecting and monitoring SARS-CoV-2 trends at a population level. This study looked to extend the use of WBE to explore the effectiveness of nonpharmaceutical interventions (NPIs) that have been used in response to COVID-19 and compare the results to the effect of such interventions on COVID-19 hospitalizations. A data-driven approach demonstrated that trends of SARS-CoV-2 RNA in wastewater, from Amsterdam and Utrecht (The Netherlands), precede hospitalizations by at least 3-9 days.

Governance using the water-food-energy nexus and human-factor measures.

Household water food and energy (WFE) expenditures, reflect respective survival needs for which their resources and social welfare are inter-related. We developed a policy driven quantitative decision-making strategy (DMS) to address the domain geospatial entities' (nodes or administrative districts) of the WFE nexus, assumed to be information linked across the domain nodal-network. As investment in one of the inter-dependent nexus components may cause unexpected shock to the others, we refer to the WFE normalized expenditures product (Volume) as representing the nexus holistic measure.

Does establishing a neurovascular unit improve the outcome after surgical clipping for aneurysmal subarachnoid hemorrhage? Results from a 5-year observational study in Kuwait.

Background: Failure to prevent rebleeding after cerebral subarachnoid hemorrhage (SAH) is the most frequent reason for high morbidity and mortality of aneurysmal SAH. Our study aims to identify the outcome after surgical clipping of aneurysmal SAH before and after the establishment of the neurovascular unit. The clarifications of the positive turnover in the outcome will be discussed.

Optimal virtual water flows for improved food security in water-scarce countries.

The worsening water scarcity has imposed a significant stress on food production in many parts of the world. This stress becomes more critical when countries seek self-sufficiency. A literature review shows that food self-sufficiency has not been assessed as the main factor in determining the optimal cultivation patterns.

Foul sewer model development using geotagged information and smart water meter data.

Hydraulic modeling of a foul sewer system (FSS) enables a better understanding of the behavior of the system and its effective management. However, there is generally a lack of sufficient field measurement data for FSS model development due to the low number of in-situ sensors for data collection. To this end, this study proposes a new method to develop FSS models based on geotagged information and water consumption data from smart water meters that are readily available.

Water quality modeling in sewer networks: Review and future research directions.

Urban sewer networks (SNs) are increasingly facing water quality issues as a result of many challenges, such as population growth, urbanization and climate change. A promising way to addressing these issues is by developing and using water quality models. Many of these models have been developed in recent years to facilitate the management of SNs.

Real-time foul sewer hydraulic modelling driven by water consumption data from water distribution systems.

Real-time hydraulic modelling can be used to address a wide range of issues in a foul sewer system and hence can help improve its daily operation and maintenance. However, the current bottleneck within real-time FSS modelling is the lack of spatio-temporal inflow data. To address the problem, this paper proposes a new method to develop real-time FSS models driven by water consumption data from associated water distribution systems (WDSs) as they often have a proportionally larger number of sensors.

Using Complex Network Analysis for Optimization of Water Distribution Networks.

The optimization of water networks supports the decision-making process by identifying the optimal trade-off between costs and performance (e.g., resilience and leakage).

Ruptured cerebral pseudoaneurysm in an adolescent as an early onset of COVID-19 infection: case report.

The clinical manifestations of coronavirus disease 2019 (COVID-19) are non-specific and multi-inflammatory. They vary from mild to severe manifestations that can be life-threatening. The association of SARS-CoV-2 infection and pseudoaneurysm formation or rupture of an already existing aneurysm is still unexplored.

The Impact of Intraoperative Monitoring on Extent of Resection and Long-Term Neurological Outcomes: A Series of 39 Intramedullary Ependimomas.

Aim: To analyze the impact of intraoperative neurophysiological monitoring (IONM) on the extent of removal and long-term neurological outcomes in a series of grade II ependymomas.

Material And Methods: We retrospectively reviewed 88 consecutive patients who underwent surgical resection of an intramedullary spinal cord tumor (IMSCT) at the Clinic of Neurosurgery of the Clinical Center of Serbia in Belgrade between January 2012 and December 2017. In all, 39 patients (25 males and 14 females; mean age 46.

Assessing the global resilience of water quality sensor placement strategies within water distribution systems.

Water quality sensors are often spatially distributed in water distribution systems (WDSs) to detect contamination events and monitor quality parameters (e.g., chlorine residual levels), thereby ensuring safety of a WDS.