Environmental Sensing in High-Altitude Mountain Ecosystems Powered by Sedimentary Microbial Fuel Cells.

The increasing need for fresh water in a climate change scenario requires remote monitoring of water bodies in high-altitude mountain areas. This study aimed to explore the feasibility of SMFC operation in the presence of low dissolved oxygen concentrations for remote, on-site monitoring of physical environmental parameters in high-altitude mountainous areas. The implemented power management system (PMS) uses a reference SMFC (SMFC) to implement a quasi-maximum power point tracking (quasi-MPPT) algorithm to harvest energy stably.

Improving the remote estimation of soil organic carbon in complex ecosystems with Sentinel-2 and GIS using Gaussian processes regression.

Background And Aims: The quantitative retrieval of soil organic carbon (SOC) storage, particularly for soils with a large potential for carbon sequestration, is of global interest due to its link with the carbon cycle and the mitigation of climate change. However, complex ecosystems with good soil qualities for SOC storage are poorly studied.

Methods: The interrelation between SOC and various vegetation remote sensing drivers is understood to demonstrate the link between the carbon stored in the vegetation layer and SOC of the top soil layers.

Multi-predictor mapping of soil organic carbon in the alpine tundra: a case study for the central Ecuadorian páramo.

Background: Soil organic carbon (SOC) affects essential biological, biochemical, and physical soil functions such as nutrient cycling, water retention, water distribution, and soil structure stability. The Andean páramo known as such a high carbon and water storage capacity ecosystem is a complex, heterogeneous and remote ecosystem complicating field studies to collect SOC data. Here, we propose a multi-predictor remote quantification of SOC using Random Forest Regression to map SOC stock in the herbaceous páramo of the Chimborazo province, Ecuador.

Pendulum tuned mass damper: optimization and performance assessment in structures with elastoplastic behavior.

Different types of tuned mass dampers (TMD) have been applied to reduce wind and seismic induces vibrations in buildings. We analyze a pendulum tuned mass damper (PTMD) to reduce vibrations of structures that exhibit elastoplastic behavior subjected to ground motion excitation. Using a simple dynamic model of the primary structure with and without the PTMD and a random process description of the ground acceleration, the performance improvement of the structure is assessed using statistical linearization.

Mechanical and electrical properties of MWCNTs - high early strength cement - mortars composite: Dispersion of CNTs and effect of chemical admixtures.

The objectives of this research were to study (1) the dispersion of MWCNTs in an aqueous system by three commercial admixtures (CAds) for concrete, and (2) the effect of CAds and MWCNTs on indirect tensile strength and electrical conductivity of MWCNTs-high early strength (HE) cement-mortar composites. To achieve the objectives, we dispersed MWCNTs in an aqueous system with (1) hydroxylated polymers-based water reducing plasticizer (HPs), a nonionic compound, (2) Naphthalene based superplasticizer (SNF), an anionic compound, and (3) calcium chloride-based accelerating agent (CC) a neutral amphoteric salt. We prepared a total of 242 samples grouped in three sets: (1) Plain mortar [PM] (water + HE cement + Sand), (2) [PM+CAd], and (3) [PM+CAd+MWCNTs].

Evaluating the conservation state of the ecosystem: An object-based image analysis and CART algorithm approach for central Ecuador.

Ecuadorian ecosystems (EPEs) function as water sources, contain large soil carbon stores and high levels of biodiversity, and support human populations. The EPEs are mainly herbaceous (HP). To inform policy and management and help drive ecological science toward a better understanding of the HP ecosystem, and the relationships among its multiple ecosystem services, we asked: (1) What is the state of the HP regarding its land use/land cover (LULC)?; and (2) Is the HP being pushed away from its natural state or it is regenerating? To answer these questions, we assessed the LULC in central EPEs using Landsat 8 imagery, Object-Based Image Analysis (OBIA) and a Classification and Regression Trees (CART) algorithm.