A Review on Applications of Time-Lapse Electrical Resistivity Tomography Over the Last 30 Years : Perspectives for Mining Waste Monitoring.

Mining operations generate large amounts of wastes which are usually stored into large-scale storage facilities which pose major environmental concerns and must be properly monitored to manage the risk of catastrophic failures and also to control the generation of contaminated mine drainage. In this context, non-invasive monitoring techniques such as time-lapse electrical resistivity tomography (TL-ERT) are promising since they provide large-scale subsurface information that complements surface observations (walkover, aerial photogrammetry or remote sensing) and traditional monitoring tools, which often sample a tiny proportion of the mining waste storage facilities. The purposes of this review are as follows: (i) to understand the current state of research on TL-ERT for various applications; (ii) to create a reference library for future research on TL-ERT and geoelectrical monitoring mining waste; and (iii) to identify promising areas of development and future research needs on this issue according to our experience.

PyLEnM: A Machine Learning Framework for Long-Term Groundwater Contamination Monitoring Strategies.

In this study, we have developed a comprehensive machine learning (ML) framework for long-term groundwater contamination monitoring as the Python package PyLEnM (Python for Long-term Environmental Monitoring). PyLEnM aims to establish the seamless data-to-ML pipeline with various utility functions, such as quality assurance and quality control (QA/QC), coincident/colocated data identification, the automated ingestion and processing of publicly available spatial data layers, and novel data summarization/visualization. The key ML innovations include (1) time series/multianalyte clustering to find the well groups that have similar groundwater dynamics and to inform spatial interpolation and well optimization, (2) the automated model selection and parameter tuning, comparing multiple regression models for spatial interpolation, (3) the proxy-based spatial interpolation method by including spatial data layers or in situ measurable variables as predictors for contaminant concentrations and groundwater levels, and (4) the new well optimization algorithm to identify the most effective subset of wells for maintaining the spatial interpolation ability for long-term monitoring.

Low-Power, Flexible Sensor Arrays with Solderless Board-to-Board Connectors for Monitoring Soil Deformation and Temperature.

Landslides are a global and frequent natural hazard, affecting many communities and infrastructure networks. Technological solutions are needed for long-term, large-scale condition monitoring of infrastructure earthworks or natural slopes. However, current instruments for slope stability monitoring are often costly, require a complex installation process and/or data processing schemes, or have poor resolution.

Surface parameters and bedrock properties covary across a mountainous watershed: Insights from machine learning and geophysics.

Bedrock property quantification is critical for predicting the hydrological response of watersheds to climate disturbances. Estimating bedrock hydraulic properties over watershed scales is inherently difficult, particularly in fracture-dominated regions. Our analysis tests the covariability of above- and belowground features on a watershed scale, by linking borehole geophysical data, near-surface geophysics, and remote sensing data.

Integrated hydrogeophysical modelling and data assimilation for geoelectrical leak detection.

Time-lapse electrical resistivity tomography (ERT) measurements provide indirectobservations of hydrological processes in the Earth's shallow subsurface at high spatial and temporal resolution. ERT has been used in the past decades to detect leaks and monitor the evolution of associated contaminant plumes. Specifically, inverted resistivity images allow visualization of the dynamic changes in the structure of the plume.

Dual in-aquifer and near surface processes drive arsenic mobilization in Cambodian groundwaters.

Millions of people globally, and particularly in South and Southeast Asia, face chronic exposure to arsenic from reducing groundwaters in which. Arsenic release to is widely attributed largely to reductive dissolution of arsenic-bearing iron minerals, driven by metal reducing bacteria using bioavailable organic matter as an electron donor. However, the nature of the organic matter implicated in arsenic mobilization, and the location within the subsurface where these processes occur, remains debated.

High resolution profile of inorganic aqueous geochemistry and key redox zones in an arsenic bearing aquifer in Cambodia.

Arsenic contamination of groundwaters in South and Southeast Asia is a major threat to public health. In order to better understand the geochemical controls on the mobility of arsenic in a heavily arsenic-affected aquifer in northern Kandal Province, Cambodia, key changes in inorganic aqueous geochemistry have been monitored at high vertical and lateral resolution along dominant groundwater flow paths along two distinct transects. The two transects are characterized by differing geochemical, hydrological and lithological conditions.

Geoelectrical monitoring of simulated subsurface leakage to support high-hazard nuclear decommissioning at the Sellafield Site, UK.

A full-scale field experiment applying 4D (3D time-lapse) cross-borehole Electrical Resistivity Tomography (ERT) to the monitoring of simulated subsurface leakage was undertaken at a legacy nuclear waste silo at the Sellafield Site, UK. The experiment constituted the first application of geoelectrical monitoring in support of decommissioning work at a UK nuclear licensed site. Images of resistivity changes occurring since a baseline date prior to the simulated leaks revealed likely preferential pathways of silo liquor simulant flow in the vadose zone and upper groundwater system.

Parathyroid hormone-related protein confers chemoresistance by blocking apoptosis signaling via death receptors and mitochondria.

Parathyroid hormone (PTH) has a central role in the regulation of serum calcium and phosphate, whereas parathyroid hormone-related peptide (PTHrP) has important developmental roles. In addition, PTHrP has been discovered as a causative agent of hypercalcemia of malignancy. PTHrP is also expressed in many tumors, and expression often correlates with unfavorable prognosis.