Analysis Of Continuous Monitoring Data Research Articles

Hydrogeochemical changes with emphasis on trace elements in an artesian well before and after the September 8, 2018 Ms 5.9 Mojiang Earthquake in Yunnan, southwest China

Most groundwater geochemical studies associated with earthquakes have focused on changes in major ions and radon concentration. However, trace elements have also shown a dramatic response to earthquakes and attracted increasing attention. In this study, hydrochemical and water level changes were detected by an artesian well (DZ well) in Yunnan, China, during the 2018 Ms 5.9 Mojiang earthquake. The results show that the major and trace element concentrations changed considerably before and after the earthquake, which were attributed to the mixing of water from different aquifers due to the earthquake-induced alteration of permeability through wavelet analysis of continuous monitoring data and coseismic static strain. In addition, Self-Organizing Map (SOM) and K-means clustering algorithms were used to classify all water samples with 10 trace elements as variables, and the results showed that samples collected in pre- and post-earthquake can be categorized as two groups, showing a significant difference. We argue that the response of trace elements remains unaffected by their initial concentration levels. Notably, both high- and low-concentration trace elements (e.g., Cs, Rb, V, etc.) exhibit discernible changes in response to the Ms 5.9 Mojiang earthquake. These observations corroborate the efficacy of clustering methodologies in delineating seismic-induced concentration shifts and furnish fresh insights into the anomalous behavior of trace elements during the earthquake.

3D Monitoring Model for Real‐Time Displacement of Metro Tunnel under “Dual Carbon” Background

Real‐time automatic displacement monitoring of metro tunnels is vital for ensuring operational safety and contributes to carbon reduction goals by improving system efficiency. This study focuses on key monitoring elements such as displacement, settlement, convergence, and cracking. Through the analysis of continuous monitoring data, a real‐time displacement monitoring model for metro tunnels based on robotic total stations is proposed. This model can timely identify potential risks, thereby ensuring the safe operation of tunnels and reducing carbon emissions from unnecessary maintenance operations, thereby reducing the carbon footprint of metro operations. This article takes the Jinan Metro Tunnel Displacement Real‐time Monitoring Project in China as a case study and constructs a comprehensive monitoring framework using robotic total stations, intelligent automated deformation monitoring data collectors, and cloud servers. The implementation details of the project, displacement monitoring principles, monitoring system construction, and data analysis processes are elaborated in detail. Taking the monitoring data of Jinan Metro Line 2 from April 1, 2022, to May 31, 2023, as an example, the results show that the tunnel displacement is within the safe range, verifying the practical application value of the method proposed in this paper. It can effectively ensure the safe operation of the metro and promote sustainable development and low‐carbon metro construction.

Physical environment research of the family ward for a healthy residential environment.

Climate change and population aging are two of the most important global health challenges in this century. A 2020 study by the Environmental Protection Agency showed that average people, particularly older adults, spent 90% of their time at home. This is even more evident during the coronavirus disease 2019 (COVID-19) pandemic. Home-based care models have become a new trend. The health and comfort of the living environment profoundly impacts the wellbeing of older adults. Therefore, research on the physical environment of the family wards has become an inevitable part of promoting the health of older adults; however, current research is still lacking. Based on the study and analysis of continuous monitoring data related to elements of the physical environment (thermal comfort, acoustic quality, lighting quality, and indoor air quality) of family wards, this paper explores the living behaviors of the participants in this environmental research (open or closed windows, air conditioning, artificial lighting, and television) on the indoor physical environment. (1) While referring to the requirements of international standards for an indoor aging-friendly physical environment, we also discuss and analyze the physical environment parameter values according to Chinese standards. (2) People's life behaviors have different degrees of influence on the elements of indoor physical environments. For example, opening doors and windows can alleviate the adverse effects of indoor environmental quality on the human body better than simply turning on the air conditioner. (3) Owing to the decline in physical function, older adults need special care. Studying the status quo of physical environmental elements and proposing suitable environmental improvement measures for aging are of great significance. (4) This research aims to address global warming and severe aging and to contribute to sustainable environmental development.

An empirical analysis on the operational profile of liquefied natural gas carriers with steam propulsion plants

AbstractLiquefied natural gas (LNG) offers negligible NOx and SOx emissions as well as reductions in CO2 compared with other liquid hydrocarbons. LNG is a significant player in the global energy mix, with a projection of 40% increase in demand for the next two decades. It is anticipated that the expected rise in demand will cause the fleet of LNG carriers (LNGC) to expand. This work concentrates on steam-powered LNGC, which accounted for 47% of the LNGC fleet in 2018. It performs an empirical analysis of continuous monitoring data that provide high levels of accuracy and transparency. The analysis is done on data collected from 40 LNGCs for over a year to estimate the fleet's operational profile, fuel mix and energy performance. The findings of this work are relevant for bottom-up analysis and simulation models that depend on technical assumptions, but also for emission studies such as the upcoming Fourth International Maritime Organization Greenhouse Gases study.

Longitudinal Analysis of Continuous Pulse Oximetry as Prognostic Factor in Neonatal Respiratory Distress.

Analysis of longitudinal data can provide neonatologists with tools that can help predict clinical deterioration and improve outcomes. The aim of this study is to analyze continuous monitoring data in newborns, using vital signs to develop predictive models for intensive care admission and time to discharge. We conducted a retrospective cohort study, including term and preterm newborns with respiratory distress patients admitted to the neonatal ward. Clinical and epidemiological data, as well as mean heart rate and saturation, at every minute for the first 12 hours of admission were collected. Multivariate mixed, survival and joint models were developed. A total of 56,377 heart rate and 56,412 oxygen saturation data were analyzed from 80 admitted patients. Of them, 73 were discharged home and 7 required transfer to the intensive care unit (ICU). Longitudinal evolution of heart rate (p < 0.01) and oxygen saturation (p = 0.01) were associated with time to discharge, as well as birth weight (p < 0.01) and type of delivery (p < 0.01). Longitudinal heart rate evolution (p < 0.01) and fraction of inspired oxygen at admission at the ward (p < 0.01) predicted neonatal ICU (NICU) admission. Longitudinal evolution of heart rate can help predict time to transfer to intensive care, and both heart rate and oxygen saturation can help predict time to discharge. Analysis of continuous monitoring data in patients admitted to neonatal wards provides useful tools to stratify risks and helps in taking medical decisions. · Continuous monitoring of vital signs can help predict and prevent clinical deterioration in neonatal patients.. · In our study, longitudinal analysis of heart rate and oxygen saturation predicted time to discharge and intensive care admission.. · More studies are needed to prospectively prove that these models can helpmake clinical decisions and stratify patients' risks..

Seismic and structural health monitoring of Cabril dam. Software development for informed management

Nowadays, the management and safety control of large dams is generally based on automatic monitoring, including the so-called seismic and structural health monitoring systems (SSHM), using the latest technology for automatic data measurement, acquisition and transmission. These systems should include software for automatic management and analysis of continuous monitoring data and software for numerical simulation of the dam dynamic behavior using 3D finite element models. This software should be designed to provide useful and reliable information to meet the needs and expectations of stakeholders, and to support the studies of researchers and engineers responsible for structural health monitoring. This paper is focused on the experience gathered from the SSHM system of Cabril dam, a 132 m high-arch dam, in Portugal, that has been under continuous dynamic monitoring since 2008. The importance of the software specifically developed for automatic modal identification, automatic detection of seismic vibrations (distinct from vibrations due to the operation of discharge gates and power groups), and automatic comparison between experimental data and computed results from a reference finite element model of the dam-reservoir-foundation system, is highlighted. This software includes: (1) the generation of graphics with the evolution of the identified natural frequencies over time and the comparison with calculated frequencies using different hypothesis for concrete damage evolution; and (2) a service to automatically send emails summarizing key dynamic monitoring results to stakeholders to provide the necessary support for informed management and engineering decision making. The main results from SSHM of Cabril dam are presented, namely regarding the evolution of modal parameter over time, considering the influence of water level variations, and the measured response during an earthquake event.

Peak concentrations of ground-level ozone during the summer heat waves of 2010 and 2016 in the background region of the Kirov region of the Russian Federation

The analysis of continuous monitoring data on surface ozone concentrations during summer heat waves in July and August 2010 and 2016 in a low-urbanized region of European Russia, Kirov region is presented. The values of the maximum short-term (peak) recorded values, obtained at 20-minute, 1-hour and 8-hour averaging, were analyzed. Under close temperature conditions, the amplitudes and durations of peak ozone concentrations in 2016 significantly exceeded the values observed in 2010. One of the possible reasons for this difference may be associated with an increase in the concentration of ozone precursors in the region’s atmosphere.

AID-GM: An Advanced System Supporting Continuous Monitoring of T1DM Patients.

In this paper, we present AID-GM, a web application for the analysis and summarization of continuous blood glucose monitoring data in patients with Type 1 Diabetes. AID-GM allows patients and their care providers to share data and analyze them thanks to a set of advanced and personalized intelligent data analysis tools. Such tools enable the extraction of complex multivariate temporal patterns from data. We present a preliminary evaluation of the functionalities of the tool, both on a set of healthy volunteers, and on real patients' data in the pediatric context.

Multiyear and Seasonal Variation of Infiltration from Storm-Water Best Management Practices

Reduction of storm-water volumes through infiltration is becoming a commonly applied practice in the effort to mitigate the negative hydrologic impacts commonly associated with land development. The hydrologic impacts generally include increases in both the volume and peak flow rate of runoff along with an associated decrease in groundwater recharge. Infiltration best management practices (BMPs) are the foundation of many low impact development and Green infrastructure practices. As the movement to volume reduction is a relatively recent concept, there remains a lack of detailed long-term monitoring data to support the implementation of storm-water infiltration BMPs. Two storm-water infiltration BMPs on the campus of Villanova University located in Southeastern Pennsylvania have been continuously monitored to determine the long-term and seasonal variation related to the engineered infiltration of storm-water runoff. The analysis of continuous monitoring data indicates that both BMPs show considerable seasonal variation but exhibit no evidence of a systematic decrease in performance to date. The seasonal variation of the BMPs is explained primarily by the temperature dependency of the viscosity of water.