Continuous Monitoring Research Articles

Premature ovarian insufficiency in pediatric cancer patients: a 10 year Rady Children's hospital experience.

To highlight the occurrence of premature ovarian insufficiency in pediatric cancer patients and determine which patient characteristics or treatment modalities are associated with ovarian failure and recovery. Between August 2011-August 2021, 36 of 2,661 patients with cancer were identified to have subsequent ovarian failure. Data collected included cancer type, diagnosis age, types of chemotherapy, bone marrow transplant or radiation treatment, peak FSH, peak AMH, GnRHa treatment, type of hormone replacement therapy, and if ovarian function recovery occurred. The most common cancer type identified was ALL. The mean age of diagnosis was 8.5±4.3 years and mean age of peak FSH value was 12.6±2.8 years. Most patients (97.2 %) were treated with alkylating agents and 72.2 % received radiation. Most patients (72.2 %) received hormone therapy, and 15.8 % of patients received GnRHa Lupron. Ten patients (27.8 %) had ovarian function recovery. Diagnosis age and treatment type were recovery predictors in multivariate regression modeling. Each year older in age was associated with a 30 % decrease in odds of recovery (OR: 0.7, CI: 0.5-0.95, p=0.035), and alkylating agent treatment without transplant was associated with a 3-fold increase in odds of recovery (OR: 3, CI: 2.7-564, p=0.007). This retrospective review demonstrates that POI can occur in pediatric cancer survivors, emphasizing the importance of educating patients on potential long-term effects of cancer treatment and importance of routine surveillance. This study confirmed that recovery of ovarian function is possible, especially when diagnosed at a younger age, making continued monitoring essential.

Different Types of Milk Flow Curves and Factors Affecting Milkability in Buffalo Species

Buffaloes are characterized by longer teats and teat canals and stronger muscular resistance of the teat wall than cattle; it is necessary to have a high vacuum level to open the teat canal and begin milk ejection. In buffalo milking management, milk yield, and flow profiles are essential parameters to record and evaluate. The milking machine is a critical point, and the characteristics of the milking vacuum and the pulsation rate are closely related to milk flow observations. In Italy, the most used vacuum levels are 44-46 kPa (range 40-53 kPa). The data on the milkability traits of the Mediterranean Italian breed made it possible to classify eight different types of milk flow curves due to anatomical, physiological, and management differences. This study aims to evaluate the main factors influencing milkability in dairy buffaloes. The results suggest the detachment of the milking cluster to reduce the decreasing and blind phases with the following advantages: reduction of the total milking time and consequently of the worker's time, improvement of the farmer's profitability and milk quality through decreasing the incidence of mastitis. Milk ability is influenced by physiological, sanitary, management, and genetic factors. In Mediterranean Italian buffaloes milked with the Automatic Milking System (AMS), a considerable variation in milk ejection and, consequently, in the milk flow curve was found compared to the conventional one, with better pre-stimulation, independent milk ejection for each teat, optimal milking of all quarters. In conclusion, continuous milkability monitoring will help optimize milking practices by reducing labor time and increasing farmers’ income through better milk quality. In addition, the identification of buffaloes with desirable types of milk flow curves could be helpful for buffalo breeders’ associations to address farmer management and to define potential new breeding objectives.

Effect of quantitative consciousness index on seizure parameters during electroconvulsive therapy in patients with major depressive disorder

BACKGROUND Electroconvulsive therapy (ECT) is both an effective treatment for patients with major depressive disorder (MDD) and a noxious stimulus. Although some studies have explored the effect of sedation depth on seizure parameters in ECT, there is little research on the noxious stimulation response to ECT. In this study, we used two electroencephalography (EEG)-derived indices, the quantitative consciousness (qCON) index and quantitative nociceptive (qNOX) index, to monitor sedation, hypnosis, and noxious stimulation response in patients with MDD undergoing acute ECT. AIM To evaluate the effect of anesthesia depth based on the qCON and qNOX indices on seizure parameters. METHODS Patients with MDD (n = 24) underwent acute bilateral temporal ECT under propofol anesthesia. Before ECT, the patients were randomly divided into three groups according to qCON scores (qCON60-70, qCON50-60, and qCON40-50). Continuous qCON monitoring was performed 3 minutes before and during ECT, and the qCON, qNOX, vital signs, EEG seizure parameters, and complications during the recovery period were recorded. The 24-item Hamilton Rating Scale for Depression, Zung’s Self-rating Depression Scale, and Montreal Cognitive Assessment scores were evaluated before the first ECT session, after the fourth ECT session, and after the full course of ECT. RESULTS A total of 193 ECT sessions were performed on 24 participants. The qCON index significantly affected the EEG seizure duration, peak mid-ictal amplitude, and maximum heart rate during ECT (P < 0.05). The qNOX index significantly affected the post-ictal suppression index (P < 0.05). Age, number of ECT sessions, and anesthetic-ECT time intervals also had a significant effect on EEG seizure parameters (P < 0.05). However, there were no significant differences in complications, 24-item Hamilton Rating Scale for Depression scores, Zung’s Self-rating Depression Scale scores, or Montreal Cognitive Assessment scores among the three groups (P > 0.05). CONCLUSION Electrical stimulation at a qCON index of 60-70 resulted in better EEG seizure parameters without increasing complications in patients with MDD undergoing bilateral temporal ECT under propofol anesthesia.

Analysis of the physico-chemical relationship between losses of water, soil and soil nutrients in the water of the Farinha River – MA

Brazil has a vast reserve of water resources, but pollution from various sources and the effects of climate change have triggered a crisis in this sector. The as-sessment of water quality indices plays a crucial role in monitoring and unders-tanding this issue, and the country has established its own standards and moni-toring requirements to guarantee water quality. In addition, the physical-chemical relationship plays a fundamental role in the conservation of both soil and water. In this context, a study was carried out in the Farinha river basin, located in Maranhão, in the Cerrado biome, over an area of 55,338.12 hecta-res. Data was collected at ten different points along the river during the rainy and dry seasons. A Van Dorn bottle was used to collect water samples at vari-ous depths, which were analysed for pH, dissolved oxygen, electrical conducti-vity and temperature. Nutrients such as potassium, calcium, magnesium, sodi-um, silicon, nitrate and total phosphorus were quantified using filtration and spectroscopy techniques. The data obtained was tabulated and subjected to analysis of variance, with the means analysed using the Tukey test. This study reveals significant seasonal variations in the physico-chemical parameters of the water in the Farinha River in Maranhão, impacting aquatic life and water quality. This highlights the importance of continuous monitoring and manage-ment of these resources.

A sulphide resistant Ag|AgCl reference electrode for long-term monitoring.

Reference electrodes which demonstrate long-term potential stability are essential for many continuous monitoring applications and are commonly based on Ag|AgCl electrodes; however, these electrodes are susceptible to poisoning from aqueous sulphide species which are commonly present in wastewater and natural groundwater. This work presents a sulphide resistant solid-state reference electrode (SSRE) based on a composite material using suspended KCl electrolyte and sacrificial AgCl in a cross-linked polyvinyl acetate polymer matrix. Sulphidation of the sacrificial AgCl produces a stable Ag2S precipitate and prevents further ingress of the poisoning sulphide species through the composite material. A novel SSRE using this material is compared to a control SSRE without suspended AgCl and a typical liquid filled reference electrode. These three reference electrodes are studied using electrochemical impedance spectroscopy (EIS), and their application is also studied in potentiometric pH sensing and cyclic voltammetry (CV). The long-term sulphide resistance of the two SSREs is also studied with potentiometry, and cross-sections of these electrodes were examined using micro X-ray fluorescence (μXRF). Both SSREs demonstrated higher impedance than the liquid reference electrode but were similar to other SSREs reported in the literature. This impedance did not result a meaningful difference in potentiometric pH sensing or CV experiments done using typical scan rates. The KCl/AgCl SSRE exhibited remarkable sulphide resistance, with all samples demonstrating a stable potential without maintenance after ca. 120 days of continuous immersion in 1 g L-1 Na2S solution, whereas KCl SSRE samples all demonstrated significant drift before this time. μXRF sulphur maps revealed that suspended AgCl prevented sulphide ingress, thus protecting the embedded Ag|AgCl electrode. This work presents a reference electrode that could enable long-term monitoring in challenging sulphide solutions, and also highlights a novel approach for preventing reference electrode poisoning which could be more widely explored.

Automating insulin delivery through pump and continuous glucose monitoring connectivity: Maximizing opportunities to improve outcomes.

The development of automated insulin delivery (AID) systems, which connect continuous glucose monitoring (CGM) systems with algorithmic insulin delivery from an insulin pump (continuous subcutaneous insulin infusion, [CSII]), has led to improved glycaemia and quality of life benefits in those with insulin-treated diabetes. This review summarizes the benefits gained by the connectivity between insulin pumps and CGM devices. It details the technical requirements and advances that have enabled this, and highlights the clinical and user benefits of such systems. Clinical trials and real-world outcomes from the use of AID systems in people with type 1 diabetes (T1D)will be the focus of this article; outcomes in people with type 2 diabetes (T2D) and other diabetes subtypes will also be discussed. We also detail the limitations of current technological approaches for connectivity between insulin pumps and CGM devices. While recognizing the barriers, we discuss opportunities for the future.

Harnessing the Heart’s Magnetic Field for Advanced Diagnostic Techniques

Heart diseases remain one of the leading causes of morbidity and mortality worldwide, necessitating innovative diagnostic methods for early detection and intervention. An electrocardiogram (ECG) is a well-known technique for the preliminary diagnosis of heart conditions. However, it can not be used for continuous monitoring due to skin irritation. It is well known that every body organ generates a magnetic field, and the heart generates peak amplitudes of about 10 to 100 pT (measured at a distance of about 3 cm above the chest). This poses challenges to capturing such signals. This paper reviews the different techniques used to capture the heart’s magnetic signals along with their limitations. In addition, this paper provides a comprehensive review of the different approaches that use the heart-generated magnetic field to diagnose several heart diseases. This research reveals two aspects. First, as a noninvasive tool, the use of the heart’s magnetic field signal can lead to more sensitive advanced heart disease diagnosis tools, especially when continuous monitoring is possible and affordable. Second, its current use is limited due to the lack of accurate, affordable, and portable sensing technology.

Impact of diverse aerobic exercise plans on glycemic control, lipid levels, and functional activity in stroke patients with type 2 diabetes mellitus

AimsThis study aimed to assess the effects of Low-to-Moderate Intensity Continuous Training (LMICT), Moderate-Intensity Interval Training (MIIT), and Reduced-Exertion High-Intensity Training (REHIT) on blood glucose regulation, functional recovery, and lipid levels in individuals who have experienced a stroke and are diagnosed with Type 2 Diabetes Mellitus (T2DM).MethodsForty-two T2DM stroke patients were randomly allocated to four groups: LMICT, MIIT, REHIT, and a control group (CON). Participants continuously monitored their blood glucose levels throughout the intervention using continuous glucose monitoring (CGM) devices. The study comprised two exercise intervention cycles: the first lasting from Day 3 to Day 14 and the second from Day 15 to Day 28, with the initial two days serving as contrasting periods. Primary outcomes encompassed CGM-derived blood glucose measurements, the Barthel Index (BI), Fugl-Meyer Assessment lower-extremity subscale (FMA-LE), and alterations in triglycerides (TG), total cholesterol (TC), high-density lipoprotein cholesterol (HDL-c), and low-density lipoprotein cholesterol (LDL-c).ResultsCompared with the CON, the MIIT group showed significant improvements in mean glucose (MG), glucose standard deviation (SD), time above range (TAR), and time in range (TIR). The REHIT group exhibited significantly reduced time below range (TBR), glucose SD, and coefficient of variation (CV). Regarding lipid levels, although the REHIT group achieved a significant reduction in TG levels compared with the CON, the overall effects of LMICT, MIIT, and REHIT on lipid profiles were relatively modest. Concerning functional recovery, the REHIT group significantly improved the BI and FMA-LE.ConclusionAlthough the short-term quantitative impact of exercise on lipid levels may be limited, both REHIT and MIIT significantly improved glycemic management and reduced glucose variability in post-stroke patients with Type 2 Diabetes Mellitus. Additionally, REHIT notably enhanced functional recovery.

An Evaluation of the Brine Flow in the Upper Part of the Halite Nucleus of the Salar de Atacama (Chile) through an Isotopic Study of δ18O and δ2H

A hydrogeological study of the shallowest part of the halite nucleus of the Salar de Atacama is presented, focusing on the isotopic variability in δ18O and δ2H (SMOW) in the brine. It is observed that intensive brine extraction has induced upward vertical flows from the lower aquifer, which presents with a lighter isotopic composition (δ18O: −0.87‰ to −2.49‰; δ2H: −26.04‰ to −33.25‰), toward the upper aquifer, which has more variable and enriched isotopic values. Among the possible explanations for the lighter isotopic composition of the lower aquifer waters is the influence of paleolakes formed during the wetter periods of the Late Pleistocene and Holocene that recharged the underlying aquifers. The geological structure of the Salar, including faults and the distribution of low-permeability layers, has played a determining role in the system’s hydrodynamics. This study emphasizes the need for continuous and detailed monitoring of the isotopic composition to assess the sustainability of the water resource in response to brine extraction and future climate changes. Additionally, it suggests applying this methodology to other salt flats in the region for a better understanding of hydrogeological processes in arid zones. The research provides an integrative view of the relationship between resource extraction, water management, and ecosystem conservation in one of the most important salars in the world.

Flexible, Electrochemical Skin-Like Platform for Inflammatory Biomarker Monitoring.

Addressing global challenges in wound management has greatly encouraged the emergence of home diagnosis and monitoring devices. This technological shift has accelerated the development of new skin patch sensors for continuous health monitoring. A key requirement is the creation of flexible platforms capable of mimicking human skin features. Here, for the first time, an innovative, highly adaptable electrochemical biosensor with molecularly imprinted polymers (MIPs) is customized for the detection of the inflammatory biomarker interleukin-6 (IL-6). The 3-electrode gold pattern is geometrically standardized onto a 6µm thick polyimide flexible membrane, an optically transparent, and biocompatible polymeric substrate. Subsequently, a biomimetic sensing layer specifically designed for the detection of IL-6 target is produced on these transducers. The obtained MIP biosensor shows a good linear response within the concentration range 50pgmL-1-50ngmL-1, with a low limit of detection (8pgmL-1). X-ray photoelectron spectroscopy, scanning electron microscopy, and Fourier transform infrared spectroscopy characterizations confirm the modifications of the flexible gold transducer. After optimization, the biosensing device shows remarkable potential in terms of sensitivity, selectivity, and reproducibility. Overall, the integration of a low-cost electrochemical sensor on biocompatible flexible polymers opens the way for a new generation of monitoring tools with higher accuracy, less invasiveness, and greater patient comfort.

Insulin Delivery Technology for Treatment of Infants with Neonatal Diabetes Mellitus: A Systematic Review.

Neonatal diabetes mellitus is a rare disorder of glucose metabolism with onset within the first 6months of life. The initial treatment is based on insulin infusion. The technologies for diabetes treatment can be very helpful, even if guidelines are still lacking. The current study aimed to provide a comprehensive review of the literature about the safety and efficacy of insulin treatment with technology for diabetes to support clinicians in the management of infants with neonatal diabetes mellitus. A total of 22 papers were included, most of them case reports or case series. The first infants with neonatal diabetes mellitus treated with insulin pumps were described nearly two decades ago. Over the years, continuous glucose monitoring systems were added to treat these individuals, allowing for a better customization of insulin administration. Insulin was diluted in some cases to further minimize the doses. Improvement in technology for diabetes prompted clinicians to use new devices and algorithms for insulin delivery in infants with neonatal diabetes as well. These systems are safe and effective, may shorten hospital stay, and help clinicians weaning insulin during the remission phase in the transient forms or switching from insulin to sulfonylurea when suggested by the molecular diagnosis. New technologies for insulin delivery in infants with neonatal diabetes can be used safely and closed-loop algorithms can work properly in these situations, optimizing blood glucose control.

Early spectral dynamics are indicative of distinct growth patterns in post‐wildfire forests

AbstractWestern North America has seen a recent dramatic increase in large and often high‐severity wildfires. After forest fire, understanding patterns of structural recovery is important, as recovery patterns impact critical ecosystem services. Continuous forest monitoring provided by satellite observations is particularly beneficial to capture the pivotal post‐fire period when forest recovery begins. However, it is challenging to optimize optical satellite imagery to both interpolate current and extrapolate future forest structure and composition. We identified a need to understand how early spectral dynamics (5 years post‐fire) inform patterns of structural recovery after fire disturbance. To create these structural patterns, we collected metrics of forest structure using high‐density Remotely Piloted Aircraft (RPAS) lidar (light detection and ranging). We employed a space‐for‐time substitution in the highly fire‐disturbed forests of interior British Columbia. In this region, we collected RPAS lidar and corresponding field plot data 5‐, 8‐, 11‐,12‐, and 16‐years postfire to predict structural attributes relevant to management, including the percent bare ground, the proportion of coniferous trees, stem density, and basal area. We compared forest structural attributes with unique early spectral responses, or trajectories, derived from Landsat time series data 5 years after fire. A total of eight unique spectral recovery trajectories were identified from spectral responses of seven vegetation indices (NBR, NDMI, NDVI, TCA, TCB, TCG, and TCW) that described five distinct patterns of structural recovery captured with RPAS lidar. Two structural patterns covered more than 80% of the study area. Both patterns had strong coniferous regrowth, but one had a higher basal area with more bare ground and the other pattern had a high stem density, but a low basal area and a higher deciduous proportion. Our approach highlights the ability to use early spectral responses to capture unique spectral trajectories and their associated distinct structural recovery patterns.

Microseismic Monitoring and Disaster Warning via Mining and Filling Processes of Residual Hazardous Ore Bodies

The thick ore bodies in the Xianglushan tungsten mine have been irregularly mined, forming a super large, connected irregular goaf group and tall, isolated irregular pillars inside. At the same time, there is a production capacity task of recovering residual and dangerous ore bodies. This poses the potential for serious ground-pressure disasters, such as roof caving, pillar collapse, and large-scale goaf collapse during mining. Based on the actual needs of the site, we established a microseismic monitoring system. After analyzing the mining and filling processes and their relationships, and, combined with the distribution characteristics of microseismic multiple parameters, we constructed a ground-pressure disaster warning mode and mechanism. We analyzed the stability of the goaf, further formed a warning system, and achieved disaster warning. In response to the current situation of the difficulty of early warning of ground pressure in the Xianglushan tungsten mine, continuous on-site monitoring of existing goaves, point pillars, and strip pillars, as well as analysis of stress changes during dynamic mining and filling processes, we explored scientific and reasonable early warning mechanisms and models, understanding the relationship between the changes in microseismic parameters during dynamic mining and filling processes and ground pressure, studying and improving the reliability of underground microseismic monitoring and early warning, and achieved the internal connection between building early warning systems and the prevention of ground-pressure disasters. The results indicate that the mining and filling process of the ore body is the main factor in maintaining a stable and balanced distribution of underground ground pressure in mining engineering. Microseismic monitoring can invert the evolution of ground pressure and form a feedback system with ground-pressure warning, achieving mine safety management.

Real-Time and Wireless Transmission of a Nitrogen-Doped Ti3C2Tx Wearable Gas Sensor for Efficient Detection of Food Spoilage and Ammonia Leakage.

With the rising popularity of smart homes, there is an urgent need for devices that can perform real-time online detection of ammonia (NH3) concentrations for food quality measurement. In addition, timely warning is crucial to preventing individual deaths from NH3. However, few studies can realize continuous monitoring of NH3 with high stability and subsequent application validation. Herein, we report on an integrated device equipped with a nitrogen-doped Ti3C2Tx gas sensor that shows great potential in detecting food spoilage and NH3 leakage. The nitrogen doping results in the lattice misalignment of Ti3C2Tx, subsequently realizing effective barrier height modulation and enhanced charge transfer efficiency of nitrogen-doped Ti3C2Tx. Density functional theory calculations confirm the greatly enhanced adsorption of NH3 on nitrogen-doped Ti3C2Tx. Our work can inspire the design of efficient gas sensors for real-time and wireless detection of food spoilage and NH3 leakage.

Comparing airborne and along-sidewall ground-based measurements to retrieve thermal and PM10 concentration profiles in two Alpine valleys

Abstract The paper aims at investigating the effectiveness of estimating vertical profiles of air temperature and PM10 concentrations in Alpine valleys through ground stations positioned at different altitudes on one valley sidewall (i.e. pseudo-vertical profiles). Two case studies in the Italian Alps are investigated: Chiese Valley in Trentino province and Camonica Valley in Lombardy region. Vertical profiles of temperature and PM10 concentrations were derived from airborne measurements at the center of the two valleys by means of low-cost sensors installed on a drone during summer 2019 and a tethered balloon during winter 2020. At the same time, five stations, equipped with the same kind of low-cost sensors, simultaneously monitored the same variables on one mountain slope. Comparisons between pseudo-profiles and airborne soundings revealed that ground stations well approximated temperature and PM10 soundings during the night and early morning, while temperatures along the slopes were higher than in the center of the valley during daytime, due to solar radiative heating, with larger differences in summer than in winter. On the contrary, some episodes with PM10 concentrations slightly higher in the valley center than on the slope were recorded, due to transport events and upslope winds. Nonetheless, the pseudo-profiles based on slope ground measurements faithfully reproduced the vertical gradients of both air temperature and PM10 if compared to those assessed from the soundings performed at the center of the two valleys. Results show that pseudo-vertical profiles can be a reliable and inexpensive method for continuous monitoring of vertical air temperature and PM10 distribution in mountain valleys.

Natural forest colonisation as a management strategy to restore soil functioning of abandoned agricultural lands

Abstract Land abandonment promotes forest expansion into abandoned agricultural lands in Europe. This process leads to changes that affect several ecosystem services, but it is considered a low‐cost strategy to restore soil functions in past agricultural lands. Soil microbial communities play a key role in restoring functions. However, the relationship among forest expansion, microbial communities, and soil functioning is unclear. In this study, we used a Juniperus thurifera expansion gradient on abandoned agricultural lands in Alto Tajo National Park (Spain) to discover the changes elicited by the soil microbial communities and their functions along this gradient considering two microhabitats, under the canopy and open areas. Specifically, our objectives were (i) to analyse how soil properties (organic matter and pH), microbial communities (using PLFAs‐NFLAs) and enzymatic activities (related to C, N and P cycling) varied along the forest expansion gradient and between microhabitats and (ii) to decipher the pathways by which soil properties control the carbon and nutrient cycling in soils. The forest expansion gradient had a direct negative effect on phosphatase activity. The microhabitat showed a positive direct effect on organic matter content, pH, actinomycetes and arbuscular mycorrhizal fungi biomass and on soil C and P cycling. Moreover, the biomass of gram‐positive bacteria determined the biomass of other microbial groups. Synthesis and Applications: Though its effectiveness is variable, passive restoration can be more effective than active restoration. Our research indicates that passive tree colonisation of past agricultural land is enough to achieve soil functionality similar to a mature forest for most variables studied. However, some variables would need more time to reach mature forest levels, such as total microbial biomass and organic matter content. Therefore, to support ecosystem recovery, the management of this applied forest ecology strategy requires continuous monitoring of newly established trees and soil to elucidate the time needed to achieve mature soil properties.

Pharmacomechanical thrombectomy in management of pulmonary embolism

BackgroundAcute pulmonary embolism is recorded as one of the most common and critical medical conditions, resulting in a notable mortality rate requiring a multidisciplinary management. In this series, we address the management of massive and sub-massive pulmonary embolism utilizing catheter-based intervention, in particular the conjunction of mechanical thrombus disruption and aspiration with pharmacological thrombolysis (pharmacomechanical thrombectomy).Results37 patients were diagnosed with massive and sub-massive pulmonary embolism based on the clinical and radiological findings. Pre-procedural vital parameters were obtained, including oxygen saturation, pulse rate, and blood pressure. Under continuous monitoring and conscious sedation, a pulmonary angiography via right common femoral vein access was performed for pre-procedural assessment. Pharmacomechanical thrombectomy was performed using the AngioJet Ultra System (Boston Scientific). Using the power pulse option, a fibrinolytic agent was infused into the thrombus. After 5–10 min, mechanical thrombectomy is performed with a maximum 3 passes through the thrombus. This technique is performed in the main pulmonary artery and lower branch. The procedure is repeated on the other side. The maximum duration of thrombectomy is 2–3 min on each side. Procedure success was based on improvement of vital signs and not related to post-procedure angiographic findings. All patients showed immediate improvement of vital signs (blood pressure, 02 saturation, and pulse rate) with progressive improvement over the following days. There were no procedure-related complications.ConclusionPharmacomechanical thrombectomy is a safe and effective technique in the treatment of massive and submassive pulmonary embolism. It can be a first-line treatment even in patients without absolute contraindication to systemic thrombolysis.

Contribution to Conditional Maintenance by Vibration Analysis of Rotating Machine Mechanical Failures and Proposed Solutions

Objective: The aim of this study is to analyze the Cement Separator machine and identify potential condition indicators through vibration measurements and analysis. The goal is to diagnose and repair the machine before any material damage occurs. Background: Maintenance Technology: Modern maintenance technologies are crucial for monitoring equipment performance and planning timely maintenance interventions. Vibration Monitoring: As a key component in maintenance programs, especially for mechanical systems, vibration monitoring provides early warnings of faults based on the actual state of the machine. Cement Separator Machine: Issue: The cement separator exhibits significant vibrations despite its low operating speed. Data Sources: The construction and operational details of the machine are available from its operating manual and vibration measurements. Methodology: Practical Vibration Measurements: Extensive measurements are performed in a research laboratory and on-site to monitor the machine's condition. Vibration measuring devices are used to monitor rotating machines at specified intervals according to their condition and international standards. Condition Indicators: Various condition indicators are monitored to detect possible deterioration and the onset of mechanical or electrical failures during the machine's operation. Experimental Studies: Practical experiments validate the theoretical and numerical findings and refine the vibration analysis approach. Strategy: Adequate scheduling of interventions and repairs based on the machine's condition. Continuous monitoring through vibration analysis devices. Expected Outcomes: Early detection of potential mechanical or electrical failures. Sustainable solutions to reduce vibrations and enhance the machine's performance. Improved maintenance scheduling to prevent material damage and extend the machine's lifespan. By integrating vibration monitoring and analysis with practical studies, this research aims to provide a comprehensive diagnosis and repair strategy for the cement separator machine.

Recent advances in gold nanostructure-based biosensors in detecting diabetes biomarkers

Diabetes mellitus (DM) is a prevalent disorder with an urgent need for continuous, precise, and on-site biomarker monitoring devices. The continuous monitoring of DM biomarkers from different biological matrices will become routine in the future, thanks to the promising biosensor design. Lately, employing different nanomaterials in biosensor receptor parts has had a great impact on smart DM monitoring. Among them, gold nanostructures (AuNSs) have arisen as highly potential materials in fabricating precise DM biosensors due to their unique properties. The present study provides an update on the applications of AuNSs in biosensors for detecting glucose as well as other DM biomarkers, such as glycated hemoglobin (HbA1c), glycated albumin (GA), insulin, insulin antibodies, uric acid, lactate, and glutamic acid decarboxylase antibodies (GADA), with a focus on the most important factors in biosensor performance such as sensitivity, selectivity, response time, and stability. Specified values of limit of detection (LOD), linear concentrations, reproducibility%, recovery%, and assay time were used to compare studies. In conclusion, AuNSs, owing to the wide electrochemical potential window and low electrical resistivity, are valuable tools in biosensor design, alongside other biological reagents and/or nanomaterials.

A system of ODEs for representing trends of CGM signals

Diabetes Mellitus is a metabolic disorder which may result in severe and potentially fatal complications if not well-treated and monitored. In this study, a quantitative analysis of the data collected using CGM (Continuous Glucose Monitoring) devices from eight subjects with type 2 diabetes in good metabolic control at the University Polyclinic Agostino Gemelli, Catholic University of the Sacred Heart, was carried out. In particular, a system of ordinary differential equations whose state variables are affected by a sequence of stochastic perturbations was proposed and used to extract more informative inferences from the patients’ data. For this work, Matlab and R programs were used to find the most appropriate values of the parameters (according to the Akaike Information Criterion (AIC) and the Bayesian Information Criterion (BIC)) for each patient. Fitting was carried out by Particle Swarm Optimization to minimize the ordinary least squares error between the observed CGM data and the data from the ODE model. Goodness of fit tests were made in order to assess which probability distribution was best suitable for representing the waiting times computed from the model parameters. Finally, both parametric and non-parametric density estimation of the frequency histograms associated with the variability of the glucose elimination rate from blood were conducted and their representative parameters assessed from the data. The results show that the chosen models succeed in capturing most of the glucose fluctuations for almost every patient.