Structural health monitoring

Structural health monitoring (SHM) is critical for ensuring the safety of infrastructure such as bridges. This article presents a digital twin solution for the SHM of railway bridges using low-cost wireless accelerometers and machine learning (ML). The system architecture combines on-premises edge computing and cloud analytics to enable efficient real-time monitoring and complete storage of relevant time-history datasets. After train crossings, the accelerometers stream raw vibration data, which are processed in the frequency domain and analyzed using machine learning to detect anomalies that indicate potential structural issues...

With the rapid development of big data, the Internet of Things (IoT), and other technological advancements, digital twin (DT) technology is increasingly being applied to the field of bridge structural health monitoring. Achieving the precise implementation of DT relies significantly on a dual-drive approach, combining the influence of both physical model-driven and data-driven methodologies. In this paper, two methods are proposed to predict the displacement and dynamic response of structures under strong winds, namely, a Bayesian Neural Network (BNN) model based on Bayesian inference and a finite element model (FEM) method modified based on genetic algorithms (GAs) and multi-objective optimization (MOO) using response surface methodology (RSM)...

Bipolar disorder (BD) is a serious mental health condition that is clinically complex to monitor and manage. While best practice guidelines exist, they vary internationally lacking consensus. Indigenous peoples, including Māori in New Zealand, experience higher community rates of BD. While New Zealand practice guidelines recommend providing culturally responsive care to Māori, studies show that Māori do not receive best practice. This qualitative study aimed to share the evidence about patterns of health service use and Māori patient experiences with focus group participants involved in the design and delivery of BD services, to discuss and develop guidelines for best practice for Māori with BD and address areas of unmet need...

The state of confinement during the COVID-19 pandemic affected the quality of life of the general population. This study aims to define and contrast an explanatory model of the quality of life in adults and to analyze the relationships between these variables based on the state of confinement and sex. A total of 872 people from Chile aged between 17 and 50 (M = 21.70 years; SD= 3.272), of both sexes (60.90% male and 39.1% female) participated in this research, of whom 46.6% were not confined when tested and 53...

The implementation of monitoring for general medical practice (GMP) can contribute to improving the quality of diabetes mellitus (DM) care. Our study aimed to describe the associations of DM care performance indicators with the structural characteristics of GMPs and the socioeconomic status (SES) of patients. Using data from 2018 covering the whole country, GMP-specific indicators standardized by patient age, sex, and eligibility for exemption certificates were computed for adults. Linear regression models were applied to evaluate the relationships between GMP-specific parameters (list size, residence type, geographical location, general practitioner (GP) vacancy and their age) and patient SES (education, employment, proportion of Roma adults, housing density) and DM care indicators...

Tackling the impact of missing data in water management is crucial to ensure the reliability of scientific research that informs decision-making processes in public health. The goal of this study is to ascertain the root causes associated with cyanobacteria proliferation under major missing data scenarios. For this purpose, a dynamic missing data management methodology is proposed using Bayesian Machine Learning for accurate surface water quality prediction of a river from Limia basin (Spain). The methodology used entails a sequence of analytical steps, starting with data pre-processing, followed by the selection of a reliable dynamic Bayesian missing value prediction system, leading finally to a supervised analysis of the behavioral patterns exhibited by cyanobacteria...

Although ligand-promoted photodissolution of ferrihydrite (FH) has long been known for low molecular weight organic acids (LMWOAs), such as oxalate (Oxa) and malonate (Mal), photochemistry of coprecipitated FH with Oxa and Mal remains unknown, despite the importance of these mineral-organic associations in carbon retention has been acknowledged recently. In this study, ferrihydrite-LMWOAs associations (FLAs) were synthesized under circumneutral conditions. Photo-dissolution kinetics of FLAs were compared with those of adsorbed LMWOAs on FH surface and dissolved Fe-LMWOAs complexes through monitoring Fe(II) formation and organic carbon decay...

Metal-organic frameworks (MOFs) have emerged as a key focus in water treatment and monitoring due to their unique structural features, including extensive surface area, customizable porosity, reversible adsorption, and high catalytic efficiency. While numerous reviews have discussed MOFs in environmental remediation, this review specifically addresses recent advancements in modifying MOFs to enhance their effectiveness in water purification and monitoring. It underscores their roles as adsorbents, photocatalysts, and in luminescent and electrochemical sensing...

The analysis of almost holistic food profiles has developed considerably over the last years. This has also led to larger amounts of data and the ability to obtain more information about health-beneficial and adverse constituents in food than ever before. Especially in the field of proteomics, software is used for evaluation, and these do not provide specific approaches for unique monitoring questions. An additional and more comprehensive way of evaluation can be done with the programming language Python. It offers broad possibilities by a large ecosystem for mass spectrometric data analysis, but needs to be tailored for specific sets of features, the research questions behind...

The availability of carbon nanotube (CNT)-based polymer composites allows the development of surface-attached self-sensing crack sensors for the structural health monitoring of reinforced concrete (RC) structures. These sensors are fabricated by integrating CNTs as conductive fillers into polymer matrices such as polyurethane (PU) and can be applied by coating on RC structures before the composite hardens. The principle of crack detection is based on the electrical change characteristics of the CNT-based polymer composites when subjected to a tensile load...

In this study, we conducted a systematic assessment of the effectsof Deoxynivalenol (DON) and T-2 mycotoxins on the developmental processes and structural integrity of murine femurs, considering both the isolated and synergistic effects of these toxins. To this end, we divided 72 male mice into nine groups, each subjected to varying dosages of T-2, DON, or their combinations. Over a four-week experimental period, meticulous monitoring was undertaken regarding the mice's body weight, biochemical markers of bone formation and resorption, and the activity of relevant cells...

The evaluation of nontarget analysis (NTA) techniques for the monitoring of wastewater is important as wastewater is an anthropogenic pollution source for aquatic ecosystems and a threat to human and environmental health. This study presents the proof-of-concept NTA of industrial wastewater samples. A prototype hydrophilic-lipophilic-balanced (HLB) SPME and gas chromatography interfaced with time-of-flight high-resolution mass spectrometry (GC-TOFMS) with electron ionization (EI) and chemical ionization (CI) in parallel are employed...

BACKGROUND: Hospital resilience is essential in responding to disasters, but current research focuses mainly on frameworks and models rather than the protection of resilience and analysis of risk factors during public health emergencies. This study aims to examine the development of resilience in Chinese frontline hospitals during the initial COVID-19 outbreak in 2020, providing insights for future disaster response efforts. OBJECTIVES: We conducted interviews with 26 hospital staff members who were involved in the initial response to the COVID-19 outbreak in China...

In June 2022, the U.S. federal government passed its first major firearm policy since the Brady Handgun Violence Prevention Act of 1993, the Bipartisan Safer Communities Act (BSCA). Summative content analysis was used to explore how the social problem of firearm violence was outlined in both policies, with the goal of extracting the social issue's definition from the policies' approaches to solving it. Both policies do not outline the various types of firearm violence, nor the disproportionate effect of firearm violence on certain populations...

BACKGROUND: The healthcare sector demands a higher degree of responsibility, trustworthiness, and accountability when implementing Artificial Intelligence (AI) systems. Machine learning operations (MLOps) for AI-based medical diagnostic systems are primarily focused on aspects such as data quality and confidentiality, bias reduction, model deployment, performance monitoring, and continuous improvement. However, so far, MLOps techniques do not take into account the need to provide resilience to disturbances such as adversarial attacks, including fault injections, and drift, including out-of-distribution...

INTRODUCTION: Remote monitoring technologies (RMTs) can measure cognitive and functional decline objectively at-home, and offer opportunities to measure passively and continuously, possibly improving sensitivity and reducing participant burden in clinical trials. However, there is skepticism that age and cognitive or functional impairment may render participants unable or unwilling to comply with complex RMT protocols. We therefore assessed the feasibility and usability of a complex RMT protocol in all syndromic stages of Alzheimer's disease and in healthy control participants...

To the deep tissue penetration and ultra-low background, developing near-infrared (NIR) chemiluminescence probes for human health and environmental safety has attracted more and more attention, but it remains a huge challenge. Herein, a novel NIR chemiluminescence (CL) system was rationally designed and developed, utilizing Cr3+ -activated ZnGa2 O4 (ZGC) nanoparticles as a catalytic luminophore via hypochlorite (NaClO) activation for poisonous target (hydrazine, N2 H4 ) detection. With superior optical performance and unique catalytic structure of ZGC nanoparticles, the fabricated ZGC-NaClO-N2 H4 CL system successfully demonstrated excellent NIR emission centered at 700 nm, fast response, and high sensibility (limit of detection down to 0...

Cardiac fibroblasts (CF) are an essential cell type in cardiac physiology, playing diverse roles in maintaining structural integrity, extracellular matrix (ECM) synthesis, and tissue repair. Under normal conditions, these cells reside in the interstitium in a quiescent state poised to sense and respond to injury by synthesizing and secreting collagen, vimentin, hyaluronan, and other ECM components. In response to mechanical and chemical stimuli, these "resident" fibroblasts can undergo a transformation through a continuum of activation states into what is commonly known as a "myofibroblast," in a process critical for injury response...

BACKGROUND: Foot ulcers in people with diabetes are a serious complication requiring a complex management and have a high societal impact. Quality monitoring systems to optimize diabetic foot care exist, but a formal and more evidence-based approach to develop quality indicators (QIs) is lacking. We aimed to identify a set of candidate indicators for diabetic foot care by adopting an evidence-based methodology. METHODS: A systematic search was conducted across four academic databases: PubMed, Embase CINAHL and Cochrane Library...

The current study was conducted on the inhabitants living in the area adjacent to the Hudiara drain using bore water and vegetables adjacent to the Hudiara drain. Toxic heavy metals badly affect human health because of industrial environmental contamination. Particularly hundreds of millions of individuals globally have faced the consequences of consuming water and food tainted with pollutants. Concentrations of heavy metals in human blood were elevated in Hudiara drainings in Lahore city, Pakistan, due to highly polluted industrial effluents...