Are bottled mineral waters and groundwater for human supply different?

Moreno-Merino, Luis; Aguilera, Héctor; Roman, Adam

doi:10.1016/j.scitotenv.2022.155554

Cited by 9 publications

(4 citation statements)

References 35 publications

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“…Iteratively combining computational tools with human expertise holds promise for the identification of treatments for rare and neglected diseases, e.g., drugs for the COVID-19 [50] and optimizing hemodynamic predictors of spinal cord injury outcome [51], in areas of biological discovery where relevant data may be lacking or hidden in the mass of available biomedical literature [50]. Recently, expertaugmented machine learning has been advanced to gain the trust of artificial intelligence in the area of healthcare, e.g., [39] and environmental science, e.g., [52] by rectifying machine learning algorithms' ungeneralizable findings, inefficient data usage, and the lack of domainspecific general knowledge. Expert-augmented machine learning in the current study sampled a smart and efficient dataset to study rare events (i.e., the building-level case counts during the early COVID-19 spread) with the aid of individual samples that shared the same total environment but never went through a pandemic, i.e., SARS or COVID-19.…”

Section: Discussionmentioning

confidence: 99%

Quantifying the Risk of General Health and Early COVID-19 Spread in Residential Buildings with Deep Learning and Expert-augmented Machine Learning

Guan

Leung

Kwok

et al. 2023

Preprint

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Buildings’ built environment has been linked to their occupants’ health. It remains unclear whether those elements that predisposed its residents to poor general health before the two SARS pandemics also put residents at risk of contracting COVID-19 during early outbreaks. Relevant research to uncover the associations is essential, but there lacks a systematic examination of the relative contributions of different elements in one’s built environment and other non-environmental factors, singly or jointly. Hence, the current study developed a deep-learning approach with multiple input channels to capture the hierarchical relationships among an individual’s socioecology’s demographical, medical, behavioral, psychosocial, and built-environment levels. Our findings supported that 1) deep-learning models whose inputs were structured according to the hierarchy of one’s socioecology outperformed plain models with one-layered input in predicting one’s general health outcomes, with the model whose hierarchically structured input layers included one’s built environment performed best; 2) built-environment features were more important to general health compared to features of one’s sociodemographic and their health-related quality of life, behaviors, and service utilization; 3) a composite score representing built-environment features’ statistical importance to general health significantly predicted building-level COVID-19 case counts; and 4) building configurations derived from the expert-augmented learning of granular built-environment features that were of high importance to the general health were also linked to building-level COVID-19 case counts of external samples. Specific built environments put residents at risk for poor general health and COVID-19 infections. Our machine-learning approach can benefit future quantitative research on sick buildings, health surveillance, and housing design.HighlightsThe current modeling approaches for COVID-19 transmission at early spread are limited due to uncertainty and rare events.Socio-ecological structure (SES) can organize variables from different hierarchies of a total environment.TensorFlow-based deep learning with recurrent and convolutional neural networks is developed to explain general health with SES-organized variables.Among SES factors, built environments have a greater association with general health.Built-environment risks on individual general health associated with early-spread COVID-19 infections in residential buildings.

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Section: Discussionmentioning

confidence: 99%

Quantifying the Risk of General Health and Early COVID-19 Spread in Residential Buildings with Deep Learning and Expert-augmented Machine Learning

Guan

Leung

Kwok

et al. 2023

Preprint

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“…The groundwater quality and chemical process is affected by several factors in the oasis-desert region, such as geological conditions, runoff, land use types, groundwater exploitation, and agricultural activities [43,[50][51][52]. The chemical composition of ground-water in Yaoba Oasis was closely related to residual salts in the Quaternary sedimentary environment.…”

Section: Discussionmentioning

confidence: 99%

“…The three mechanisms controlling the chemical components in natural waters include atmospheric precipitation, rock weathering, and evaporation. Recently, Gibbs diagrams have been extensively applied to represent the controlling mechanisms of hydrochemistry in groundwater [40][41][42][43][44].…”

Section: Hydrochemical Formation Mechanism Of Groundwatermentioning

confidence: 99%

Hydrodynamic Behaviors and Geochemical Evolution of Groundwater for Irrigation in Yaoba Oasis, China

Huo

Wang

et al. 2022

Water

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The Yaoba Oasis is an irrigated cropland entirely dependent on groundwater; previous investigations (1980–2015) revealed an over-abstraction of groundwater and deteriorating groundwater quality. For further exploring the hydrodynamic behaviors and geochemical processes of groundwater during the irrigation season, groundwater samples were collected and analyzed using different techniques including classical statistics, correlation analysis, Piper diagrams, and Gibbs diagrams. The results indicated that Na+, K+, SO42− and Cl− were the main ions in groundwater, which were significantly correlated with TDS. The water–rock interaction is manifested by the precipitation of calcite and dolomite and the dissolution of rock salt and gypsum as an increase in TDS related to evaporation. In addition, the increasing complexity of hydrochemical type is caused by the rapid variation of hydrodynamic regime, irrigation and evaporation, which are subjected to the constraints of salty water intrusion from the desert salty lake and infiltration of irrigation return flow. Existing wells should limit overexploitation to halt the decline in groundwater levels and cut down irrigation water to reduce the risk of groundwater contamination and restore ecological balance in desert oasis.

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“…The therapeutic and preventive potential of mineral water consumption in addressing numerous ailments, including respiratory, skin, liver, and intestinal diseases, is wellacknowledged [1][2][3]. To gain insights into the inherent properties of mineral waters, their classifications were critically examined.…”

Section: Introductionmentioning

confidence: 99%

Influence of Microwave Energy and Agitation on the Physicochemical Properties of Natural Mineral Water

Shevchenko,

Ustinova,

Popov

et al. 2023

IJHT

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This study investigates the modifications in the physicochemical properties of natural mineral waters induced by microwave radiation and agitation. Mineral waters from Svyatoi Istochnik, Aqua Minerale, Karachinskaya, Arkhyz, and Serebrianyi Kliuch were subjected to these two activation methods. The pH and redox potential parameters were meticulously evaluated to observe alterations. Experimental studies provide evidence that microwave radiation and agitation significantly alter the physical and chemical characteristics of the selected mineral waters. A standard microwave oven operating at a frequency of 2.45 GHz was utilized for microwave radiation while agitation was performed using established techniques. The changes in pH and redox potential were carefully measured post-treatment. Technologically significant properties of the treated water were identified. These include a reduction in acidity due to an increase in pH value and a near tripling of the water's redox potential following a total stirring time of 2 minutes compared to an untreated control sample. The mechanochemical technique employed during agitation caused water molecule destruction due to friction forces, plastic deformation, impact compression, and mass transfer intensification. Conversely, the microwave radiation effect is attributed to the resonance effect resulting from the absorption of microwaves by water molecules. Moreover, it was experimentally determined that the activation effect of agitation persisted in the mineral waters for one hour, while the effect of microwave radiation lasted for one day. This longevity indicates a more profound influence of microwaves on the electronic systems of the water's components. In conclusion, the study demonstrates the feasibility of altering the physicochemical parameters of mineral waters with varying compositions and degrees of mineralization using short-term microwave radiation and agitation. The successful modification of the water samples' hydrogen index and redox potential signifies the potential utility of these techniques in manipulating the properties of mineral water.

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Are bottled mineral waters and groundwater for human supply different?

Cited by 9 publications

References 35 publications

Quantifying the Risk of General Health and Early COVID-19 Spread in Residential Buildings with Deep Learning and Expert-augmented Machine Learning

Quantifying the Risk of General Health and Early COVID-19 Spread in Residential Buildings with Deep Learning and Expert-augmented Machine Learning

Hydrodynamic Behaviors and Geochemical Evolution of Groundwater for Irrigation in Yaoba Oasis, China

Influence of Microwave Energy and Agitation on the Physicochemical Properties of Natural Mineral Water

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