Type Of Failure Research Articles

Fracture propagation and pore pressure evolution characteristics induced by hydraulic and pneumatic fracturing of coal.

A two-dimensional unsteady seepage model for coal using a finite element program is developed, and the temporal variations of key factors such as water pressure and hydraulic gradient are analyzed in this paper. Additionally, the triaxial rock mechanical experiment and utilized pneumatic fracturing equipment on raw coal samples to investigate both hydraulic and pneumatic fracturing processes are conducted. Through these experiments, the relationship between pressure and crack formation and expansion are examined. The analysis reveals that the pore pressure gradient at the coal inlet reaches its peak during rapid surges in water pressure but diminishes over time. Conversely, the pore pressure gradient at the outlet side exhibits a gradual increase. Hydraulic fracturing is most likely to occur at the water inlet during sudden increases in water pressure. Besides, as the permeability of coal decreases, the duration for seepage stabilization prolongs due to the intensified pore pressure gradient resulting from sudden increases in water pressure. Moreover, an extended period of high hydraulic gradient further increases the risk of hydraulic fracturing. The experimental findings indicate that coal samples initially experience tensile failure influenced by water and air pressure. Subsequently, mode I cracks form under pressure, propagating along the fracture surface and becoming visible. The main types of failure observed in hydraulic and pneumatic fracturing are diametrical tensile failure, and the development of fractures can be categorized into three distinct stages, which contains the initial stage characterized by slight volume changes while water pressure increases, the expansion stage when pressure reaches the failure strength, and the crack closure stage marked by little or even decreasing volume changes during pressure unloading. The acoustic emission signal accurately corresponds to these three stages.

Analytical solution for estimating the minimum required strength of sill mat by considering failure due to rock wall closure

Underhand cut-and-fill mining has been widely used in underground mining operations, especially when the rock mass or orebody is of poor quality or prone to rockburst due to high stress. In such cases, mining workers should carry out all production activities under the cemented backfill roof or sill mat instead of a highly fractured and unstable rock roof or a strong rock roof with a high potential of rockburst. Therefore, the stability and required strength of the sill mat are critical issues for mining engineers. In 1991, Mitchell considered that sill mat could fail by caving, sliding, rotation, and flexure. Mitchell also proposed an analytical solution to determine the minimum required strength of the sill mat for each type of failure based on two stiff or immobile rock walls. However, recent publications using numerical modeling and field measurements indicate that the compressive stresses in the sill mat induced by rock wall closure due to a stope excavation beneath the sill mat can be significant. It is thus highly necessary to investigate the required strength of the sill mat by considering rock wall closure. In this study, the crushing failure of sill mat due to rock wall closure generated by underground excavation and a new failure mode called "crushing and caving" is revealed by numerical modeling. An analytical solution corresponding to each failure mode is then developed to estimate the minimum required cohesion () of the sill mat. A criterion is also proposed to determine if the sill mat fails by crushing or crushing-and-caving failure. The proposed analytical solution does not involve any correction coefficients. The validity of the proposed analytical solution is demonstrated by numerical modeling. The proposed analytical solution can thus be employed to predict the of sill mat subjected to wall closure generated by underlying stope excavation.

Behavior of Cofferdam Using Non-uniform Geotextile Mats on Soft-overlying-stiff Foundation

Non-uniform geotextile mats are employed as soft foundations in cofferdams. However, investigations on the influence of complicated geological conditions on the mechanical behavior of cofferdams are limited. We investigated the behavior of a cofferdam using non-uniform geotextile mats to explore the failure mechanism of non-uniform geotextile mats over a soft overlying stiff foundation and quantify its stability. The two typical failure modes, global and local failure modes, differed distinctly in the velocity field and sliding surface shape. Geometric factors may partially affect the failure mode, whereas a higher soil strength can enhance the stability of the cofferdam, especially when stiff soil is involved. The failure mechanisms of cofferdams using non-uniform geotextile mats on soft overlying stiff clay and a corresponding stability prediction method are proposed to guide the design of cofferdams using non-uniform geotextile mats.

Influence of adhesive systems containing different functional monomers on the longevity of bond strength at different dentin depths

This study evaluated the influence of adhesive systems containing different functional monomers on the longevity of bond strength (BS) to superficial (SD) and deep dentin (DD). Thirty molars were sectioned longitudinally, to obtain regions of SD (closest to the dentin-enamel junction) and DD (closest to the pulp chamber). Adhesive systems were applied (n = 10): Clearfil SE Bond (containing 10-MDP), FL-Bond II (containing 4-MET) and OptiBond Universal (containing GPDM). Microcylinders were made of resin composite (Filtek Z250) in SD and DD. After 24 h or 180 days of storage in Simulated Body Fluid (SBF) solution, BS tests were carried out. The fracture mode was evaluated by scores. ANOVA showed that there was no statistically significant difference between the adhesives in terms of BS (p = 0.5156). There was no significant difference between storage times for the three adhesive systems (p = 0.4703). There was a significant interaction between storage time and dentin depth (p = 0.0175), and in the time interval of 24 h, irrespective of the adhesive system, BS was significantly higher in SD than in DD (p < 0.05). In the time interval of 24 h, there was a significant association between the adhesive and the type of failure in SD (p = 0.0085) (Fisher's Exact test). Under these conditions, only OptiBond Universal showed cohesive failures in dentin (10 %) and mixed failures (15 %). After 180 days of storage, the percentages of early failures in deep dentin were 25.0 % (OptiBond Universal), 16.7 % (Clearfil SE Bond) and 0.0 % (FL-Bond II), with a significant difference between adhesives regarding early failures (p = 0.0410). The adhesive systems showed similar BS at different dentin depths over time, irrespective of the composition of functional monomers. FL Bond II was the only adhesive system that did not show early failures mode in DD within 180 days.

The effect of immediate dentin sealing on fracture resistance and failure modes of resin composite onlay restorations

Aim: This study aimed to investigate the fracture resistance, failure modes, and reparability of molars restored with laboratory-processed resin composite (Ceramage, SHOFU Inc., Kyoto, Japan) onlays above or below the cemento-enamel junction (CEJ) in the presence or absence of immediate dentin sealing (IDS). Methodology: Forty extracted sound human molars were selected and divided into four groups: 1) Below CEJ with IDS, 2) Below CEJ without IDS, 3) Above CEJ with IDS, and 4) Above CEJ without IDS. Standardized mesio-occlusal (MO) onlay preparations were made with the reduction of mesio-buccal and mesio-palatinal cusps. Butt-joint preparation was used in the proximal box area extending 1 mm below the CEJ (Groups 1 and 2) or 1 mm above the CEJ (Groups 3 and 4). In Groups 1 and 3, IDS was applied immediately after tooth preparation. After cementation (Variolink N, Ivoclar Vivadent AG, Schaan, Liechtenstein), the specimens were thermally aged (20000 cycles, 5–55 ºC) and then subjected to load to failure (1 mm/min). The failure types and reparability of the onlays were recorded, and the data were analyzed using two-way ANOVA and Fisher’s exact tests. Results: The restorations in Group 4 showed the highest mean fracture strength compared to Group 1 (p=0.038), Group 2 (p=0.008), and Group 3 (p=0.019). The interaction between the level of proximal extension and the presence of IDS did not influence fracture mode or reparability (p&gt;0.05). Conclusion: No difference in the fracture strength of resin composite onlays below CEJ with or without IDS was found; however, not using IDS for resin composite onlays above CEJ appears to be preferable. How to cite this article: Gözetici Çil B, Köymen SS, Ünal S, Dönmez N. The effect of immediate dentin sealing on fracture resistance and failure modes of resin composite onlay restorations. Int Dent Res 2024;14(1):27-33. https://doi.org/10.5577/intdentres.510

Comparison of De-Torque and Failure Load Evaluation of Selective-Laser-Sintered CoCr, CAD-CAM ZrO, and Machined Implant Abutment/Restoration.

This study aimed to compare the torque loss, fracture load, compressive strength, and failure types of selective-laser-sintered cobalt chromium (SLM-Co-Cr), computer-aided design and computer-aided manufacturing zirconium oxide (CAD-CAM-ZrO), and machined titanium (Ti) implant abutments. Thirty endosseous dental implants were vertically embedded with machined Ti (control group), CAD-CAM-ZrO, and SLM-Co-Cr abutments. Abutment fabrication involved CAD-CAM milling and SLM technology. The de-torque assessment included preload reverse torque values (RTVs), cyclic loading, and post-RTVs using a customized protocol. Fracture load assessment employed ISO-14801 standards, and statistical analysis was conducted using ANOVA and Tukey Post hoc tests (p < 0.05). In pre-load RTVs, SLM-Co-Cr showed the lowest mean torque loss (24.30 ± 2.13), followed by machined Ti (27.33 ± 2.74) and CAD-CAM-ZrO (22.07 ± 2.20). Post-load RTVs decreased for all groups. Fracture load and compressive strength were highest for SLM-Co-Cr, with significant differences among groups (p < 0.001). Fracture types included abutment failures in SLM-Co-Cr and machined Ti, while CAD-CAM-ZrO exhibited crown separation with deformation. SLM-Co-Cr-fabricated implant abutments exhibited superior stability and resistance to rotational forces, higher fracture loads, and greater compressive strength compared to CAD-CAM-ZrO and machined Ti.

The failure type-dependent characterization of liquefaction resistance by small-strain shear modulus for saturated sand

In this study, a re-visit of existing laboratory tests was carried out to study the relationship between the liquefaction resistance (CRR) and the small-strain shear modulus (Gmax) of saturated sands with consideration of the failure types of both cyclic mobility and flow liquefaction. The result indicates that the relationship between CRR and Gmax is failure type-dependent, and the liquefaction resistance of cyclic mobility grows faster than that of flow liquefaction. Then discrete element method was used to explore the relationship between the liquefaction resistance and the small-strain shear modulus for a typical saturated granular material, with consideration of different liquefaction types. A series of undrained stress-controlled cyclic tests together with shear wave velocity measurements were simulated, and results similar to the laboratory studies were obtained. Then a new expression is proposed to describe the relationship between CRR and Gmax for granular material. The corresponding micromechanical mechanism is further explored, which shows that there are two kinds of distinct behaviors of the particle contact structure when the granular material changes from loose to dense state under the same confining stress. Compression behavior is dominant for flow liquefaction while collapse behavior is dominant for cyclic mobility type of liquefaction. The different behaviors of the particle contact structure influence the growth of the mechanical contacts, which further leads to the failure type-dependent growth of liquefaction resistance for a saturated granular material.

Corrugated Box Damage Classification Using Artificial Neural Network Image Training

ABSTRACTThis paper proposes a novel packaging evaluation method using corrugated box images and an artificial neural network (ANN). An ANN works in a way similar to that of neurons in a human brain: by making connections between a trained dataset and the new images provided after training. The ANN has been implemented in the industry in various ways but limited in packaging evaluation. This paper is focused on the corrugated box damage prediction using ANN with the Orange Data Mining platform. By capturing the damaged corrugated box images with an ANN, damaged products can be identified allowing a decision to be made as to what type of package failure occurred. One of the benefits to using an ANN to evaluate corrugated box images is that it allows for the evaluation of package protection in a real distribution environment as compared to a controlled lab setting. In turn, this reduces the cost of testing, as the package failure will have been identified with the assistance of the ANN, rather than full retesting to identify where damage occurred. This process would also reduce costs associated with the usage of materials for testing, due to the lower number of test samples required.

Mesh stiffness calculation of defective gear system under lubrication with automated assessment of surface defects using convolutional neural networks

As typical failure mode of gear system, the tooth surface pitting, spalling can be detected in most long-running gear system, especially under heavy-load and high-speed condition, or under lubricant-starvation condition, the tooth pitting is characterized by irregular contour and random distribution. Most previous study on the defective gear system mainly based on manually detection of defective region, or just rely on geometric simplification of defects, leading to inaccurate results with low-efficient method, therefore, the machine-vision-based defect inspection method is proposed in the study of defective gear system. First, the pitting defects on gear tooth surface is detected and segmented based on involutional neural network U-net, then the tooth surface with segmented defective region is mapped to the elastohydrodynamic lubrication model of spur gear system, finally, the tribological behavior in addition to the mesh stiffness under lubrication condition of defective spur gear system are investigated and discussed. The results reveal that the machine-vision-based defects inspection could improve the accuracy and efficiency of the failure study for gear system.

Experimental analysis of the effect of bar anchorage length on bond behavior in pull-out test

The article presents bond tests performed using the pull-out method. The experiments were designed to evaluate the effect of anchorage length on the bond in this test. The analysis shows that the length of the bar-concrete interface significantly influences the bond behavior. It determines the type of bond failure, affects the distribution and value of stresses in the bar, and projects the bond-slip curve, which is a key result of the pull-out test

Buyer aware: Three new failure modes in TOPCon modules absent from PERC technology

The n-type tunnel oxide passivated contact (TOPCon) technology is going to be the leading industrial technology in 2024. However, there are still concerns about the reliability of TOPCon when used in the field, especially in glass/backsheet modules. This work investigates the impact of damp heat (DH) on the performance TOPCon and PERC glass/backsheet modules by varying bills of materials (BOM), such as polyolefin elastomer (POE), ethyl-vinyl acetate (EVA), and polymer backsheet options. It is found that PERC modules remain stable, with a maximum power loss (Pmax) of only 1–2%rel after 1000 h of DH testing, regardless of the BOM used. However, TOPCon modules experienced significant degradation with a drop in Pmax ranging from 4 to 65%rel after the same testing duration. Despite utilizing POE, an expensive encapsulant with a significantly lower water vapour transmission rate than EVA and devoid of acetic acid formation, a severe performance decline was observed in a specific POE variant within TOPCon modules, with a loss of power of up to 65%rel. Three types of failures were observed in TOPCon modules: point-localized failure, failure at/around the interconnection of ribbon wires and busbars, and failure throughout the whole area of cells/modules. These failures likely result from electrochemical reactions involving moisture, cell metallization, ribbon wires, contaminants, soldering flux, and additives released from POE. The observed findings underline two crucial points: 1) the vulnerability and potential failure of TOPCon solar cells when exposed to high humidity and contaminants, and 2) the high risk associated with certain POE types, which could potentially adversely affect TOPCon cells. Hence, it is crucial to exercise utmost caution and precision in handling and selecting encapsulation materials for TOPCon modules. Accordingly, urgent and extensive research efforts are crucial to substantially increase our comprehension and fortify the reliability of TOPCon cells against the pernicious effects of moisture and other contaminants.

Right ventricular dysfunction in chronic heart failure: clinical laboratory and echocardiographic characteristics. (the RIVED-CHF registry).

Right ventricular dysfunction (RVD) and pulmonary hypertension have been recognized as two important prognostic features in patients with left side heart failure. Current literature does not distinguish between right heart failure (RHF) and RVD, and the two terms are used indiscriminately to describe pulmonary hypertension and RVD as well as clinical sign of RHF. Therefore, the right ventricle (RV) adaptation across the whole spectrum of left ventricular ejection fraction (LVEF) values has been poorly investigated. This is a multicenter observational prospective study endorsed by the Italian Society of Cardiology aiming to analyze the concordance between the signs and symptoms of RHF and echocardiographic features of RVD. The protocol will assess patients affected by chronic heart failure in stable condition regardless of the LVEF threshold by clinical, laboratory, and detailed echocardiographic study. During the follow-up period, patients will be observed by direct check-up visit and/or virtual visits every 6 months for a mean period of 3 years. All clinical laboratory and echocardiographic data will be recorded in a web platform system accessible for all centers included in the study. The main study goals are: to investigate the concordance and discordance between clinical signs of RHF and RVD measured by ultrasonographic examination; to evaluate prognostic impact (in terms of cardiovascular mortality and heart failure hospitalization) of RVD and RHF during a mean follow-up period of 3 years; to investigate the prevalence of different right ventricular maladaptation (isolated right ventricular dilatation, isolated pulmonary hypertension, combined pattern) and the related prognostic impact. With this protocol, we would investigate the three main RVD patterns according to heart failure types and stages; we would clarify different RVD and pulmonary hypertension severity according to the heart failure types. Additionally, by a serial multiparametric analysis of RV, we would provide a better definition of RVD stage and how much is it related with clinical signs of RHF (ClinicalTrials.gov Identifier: NCT06002321).

Oxidative damage in immunoglobulin light chain and transthyretin cardiac amyloidosis – a closer look

Heart failure is a progressive disease, representing a growing cause of morbidity, hospitalization, and mortality. An increasingly common type of heart failure with preserved ejection fraction (HFpEF) is an immunoglobulin light chain and transthyretin cardiac amyloidosis, in the pathophysiology of which oxidative damage appears to exert a strong impact. Reactive oxygen and nitrogen species have physiological signaling functions, but their overaccumulation, as in cardiac amyloidosis, leads to cardiomyocyte damage and apoptosis, and to cardiac hypertrophy and fibrosis. Moreover, such pathological processes worsen the redox damage with the perpetuation of an inflammatory state, in a vicious cycle. Here, the role of oxidative damage in the transthyretin and immunoglobulin light chain cardiac amyloidosis, the underlying pathogenic mechanisms, the therapeutic implications, and possible future strategies are reviewed.

Interpretable machine learning models for failure cause prediction in imbalanced oil pipeline data

Pipelines are critical arteries in the oil and gas industry and require massive capital investment to safely construct networks that transport hydrocarbons across diverse environments. However, these pipeline systems are prone to integrity failure, which results in significant economic losses and environmental damage. Accurate prediction of pipeline failure events using historical oil pipeline accident data enables asset managers to plan sufficient maintenance, rehabilitation, and repair activities to prevent catastrophic failures. However, learning the complex interdependencies between pipeline attributes and rare failure events presents several analytical challenges. This study proposes a novel machine learning (ML) framework to accurately predict pipeline failure causes on highly class-imbalanced data compiled by the United States Pipeline and Hazardous Materials Safety Administration. Natural language processing techniques were leveraged to extract informative features from unstructured text data. Furthermore, class imbalance in the dataset was addressed via oversampling and intrinsic cost-sensitive learning (CSL) strategies adapted for the multi-class case. Nine machine and deep learning architectures were benchmarked, with LightGBM demonstrating superior performance. The integration of CSL yielded an 86% F1 score and a 0.82 Cohen kappa score, significantly advancing prior research. This study leveraged a comprehensive Shapley Additive explanation analysis to interpret the predictions from the LightGBM algorithm, revealing the key factors driving failure probabilities. Leveraging sentiment analysis allowed the models to capture a richer, more multifaceted representation of the textual data. This study developed a novel CSL approach that integrates domain knowledge regarding the varying cost impacts of misclassifying different failure types into ML models. This research demonstrated an effective fusion of text insights from inspection reports with structured pipeline data that enhances model interpretability. The resulting AI modeling framework generated data-driven predictions of the causes of failure that could enable transportation agencies with actionable insights. These insights enable tailored preventative maintenance decisions to proactively mitigate emerging pipeline failures.

Reliability Study of Metal-Oxide Semiconductors in Integrated Circuits.

This paper is devoted to the study of CMOS IC parameter degradation during reliability testing. The paper presents a review of literature data on the issue of the reliability of semiconductor devices and integrated circuits and the types of failures leading to the degradation of IC parameters. It describes the tests carried out on the reliability of controlled parameters of integrated circuit TPS54332, such as quiescent current, quiescent current in standby mode, resistance of the open key, and instability of the set output voltage in the whole range of input voltages and in the whole range of load currents. The calculated values of activation energies and acceleration coefficients for different test temperature regimes are given. As a result of the work done, sample rejection tests have been carried out on the TPS54332 IC under study. Experimental fail-safe tests were carried out, with subsequent analysis of the chip samples by the controlled parameter quiescent current. On the basis of the obtained experimental values, the values of activation energy and acceleration coefficient at different temperature regimes were calculated. The dependencies of activation energy and acceleration coefficient on temperature were plotted, which show that activation energy linearly increases with increasing temperature, while the acceleration coefficient, on the contrary, decreases. It was also found that the value of the calculated activation energy of the chip is 0.1 eV less than the standard value of the activation energy.

Self-correction method for sensor faulty heat pump system based on machine learning

Sensor faults are a common type of failure in heat pump systems, which can seriously affect the normal operation of systems. Self-correction of the sensor fault in the system is crucial. State-of-the-art sensor fault correction methods based on data-driven and physical models face challenges, such as the need for co-located sensors, accurate physical models, and a large amount of labeled data, greatly limiting their applicability. This paper proposes using machine learning methods for fault self-correction. Firstly, a data self-correction strategy based on the convolutional autoencoder is introduced. Furthermore, an artificial sample generation strategy is proposed to address the scarcity of sensor fault data for data-driven training of the self-correction model. The results demonstrate that the proposed method effectively self-corrects both single and multiple faults. Simultaneously, thermal fault diagnosis evaluations reveal over 90 % accuracy in corrected data, with a maximum diagnostic improvement of 53.5 %. Furthermore, the study shows that the number of parameters is crucial for effective correction, underscoring that over-constraint is essential for successful self-correction.

Spatio-Temporal Prediction of Three-Dimensional Stability of Highway Shallow Landslide in Southeast Tibet Based on TRIGRS and Scoops3D Coupling Model

National Highway G559 is the first highway in Southeast Tibet into Motuo County, which has not only greatly improved the difficult situation of local roads, but also promoted the economic development of Tibet. However, rainfall-induced shallow landslides occur frequently along the Bomi–Motuo section, which seriously affects the safe operation and construction work of the highway. Therefore, it is urgent to carry out geological disaster assessment and zoning along the highway. Based on remote-sensing interpretation and field investigation, the distribution characteristics and sliding-prone rock mass of shallow landslides along the Bomi–Motuo Highway were identified. Three-dimensional stability analysis of regional landslides along the Bomi-Motuo Highway under different rainfall scenarios was carried out based on the TRIGRS and Scoops3D coupled model (T-S model). The temporal and spatial distribution of potential rainfall landslides in this area is effectively predicted, and the reliability of the predicted results is also evaluated. The results show that: (1) The slope structure along the highway is mainly composed of loose gravel soil on the upper part and a strong weathering layer of bedrock on the lower part. The sliding surface is mostly a circular and plane type, and the main failure types are creep–tensile failure and flexural–tensile failure. (2) Based on the T-S coupling model, it is predicted that the potential landslide along the Bomi–Motuo Highway in the natural state is scattered. The distribution area of extremely unstable and unstable areas accounts for 4.92% of the total area. In the case of extreme rainfall once in a hundred years, the proportion of instability area (Fs &lt; 1) predicted by the T-S coupling model 1 h after rainfall is 7.74%, which is 1.57 times that of the natural instability area. The instability area (Fs &lt; 1) accounted for 43.40% of the total area after 12 h of rainfall. The potential landslides were mainly distributed in the Bangxin–Zhamu section and the East Gedang section. (3) The TRIGRS and T-S coupling model is both suitable for predicting the temporal–spatial distribution of rainfall-induced shallow landslides, but the TRIGRS model has the problem of over-prediction. The instability area predicted by the T-S coupling model accounted for 43.30%, and 74% of the historical landslide disaster points in the area were correctly predicted. (4) In terms of rainfall response, the T-S coupling model shows higher sensitivity. The %LRclass (Fs &lt; 1) index of the T-S coupling model is above 50% in different time periods, and its landslide-prediction effect (%LRclass = 78.80%) was significantly better than that of the one-dimensional TRIGRS model (%LRclass = 45.50%) under a 12 h rainfall scenario. The research results have important reference significance for risk identification and disaster reduction along the G559 Bomi–Motuo Highway.

XGBoost algorithm based estimation of near surface mounted FRP rod-to-concrete bond strength and failure mode

Using fiber-reinforced polymer (FRP) in reinforced concrete (RC) structures can mitigate the colossal repair costs due to reinforcing steel corrosion. Hence, FRP rod/bar is gaining wider applications in diverse RC structures as a partial or full replacement for steel rebar. The FRP rod-to-concrete interfacial bond is pivotal in transferring stresses from concrete to FRP rods. This study develops a novel prediction model to estimate the near surface mounted FRP rod-to-concrete bond strength as well as the failure type using five machine learning (ML) algorithms, namely, linear regression, decision tree, gradient boosting tree, random forest, and extreme gradient boosting (XGB). The performance of the developed models was compared with that of four bond strength design guidelines and one analytical model. A database comprising 416 experimental datasets was constructed and used for model training and validation. Based on statistical performance metrics, the precision of the XGB algorithm was superior to that of the other ML models, design guidelines, and analytical model. Feature importance analysis based on the SHapley Additive exPlanations theory and partial dependence plot was performed. The results show that the bond length had the most significant influence on the bond strength, followed by the tensile strength of the FRP composite, diameter of the FRP rod, compressive strength of concrete, and elastic modulus of the FRP composite. A graphical user interface was developed and offers a user friendly, free access, and simple tool for estimating the bond strength and failure type of FRP rods in concrete.

Development of a Real-time Force-based Algorithm for Infusion Failure Detection.

Continuous subcutaneous insulin infusion (CSII) is a common treatment option for people with diabetes (PWD), but insulin infusion failures pose a significant challenge, leading to hyperglycemia, diabetes burnout, and increased hospitalizations. Current CSII pumps' occlusion alarm systems are limited in detecting infusion failures; therefore, a more effective detection method is needed. We conducted five preclinical animal studies to collect data on infusion failures, utilizing both insulin and non-insulin boluses. Data were captured using in-line pressure and flow rate sensors, with additional force data from CSII pumps' onboard sensors in one study. A novel classifier model was developed using this dataset, aimed at detecting different types of infusion failures through direct utilization of force sensor data. Performance was compared against various occlusion alarm thresholds from commercially available CSII pumps. The testing dataset included 251 boluses. The Bagging classifier model showed the highest performance metrics among the models tested, exhibiting high accuracy (96%), sensitivity (94%), and specificity (98%), with lower false-positive and false-negative rate compared with traditional occlusion alarm pressure thresholds. Our study developed a novel non-threshold classifier that outperforms current occlusion alarm systems in CSII pumps in detecting infusion failures. This advancement has the potential to reduce the risk of hyperglycemia and hospitalizations due to undetected infusion failures, offering a more reliable and effective CSII therapy for PWD. Further studies involving human participants are recommended to validate these findings and assess the classifier's performance in a real-world setting.

Inappropriate Defibrillator Shock Due to Oversensing. What to Do?

In spite of advanced designs of implantable cardioverter defibrillators (ICD) lead fracture remains the most frequent complications. ICD interrogation is mandatory for the diagnosis of all type of lead failures. We report the case of an 18 years old boy, diagnosed with Jarvell and Lange Nielsen syndrome since he was 2 years. He received first Nadolol then he got ICD and a prophylactic left sympathectomy after he had a cardiac arrest. One year later, the ICD started delivering shocks, appropriate at first then inappropriate due to oversensing. Long QT syndrome is a rare congenital disorder characterized by repetitive episode of syncope and cardiac arrest due to polymorphic ventricular tachycardia. The treatment is mostly pharmaceutical with B-blockers. The indication for an ICD is in class I for patients who survived cardiac arrest, and for patients who experience recurrent syncopal events under B-blockers. On the other hand, in case of contraindicated or not tolerated medical therapy, ICD is recommended as a class IIa, according the ESC guidelines of 2022. An ICD must be interrogated frequently and have its measurements reviewed in order to detect lead dysfunction. The detection of high impedance suggests conductor fracture along with inappropriate defibrillator shocks delivered by the ICD. Oversensing with normal pacing impedance is the initial electrical abnormality with either conductor fracture.(4) The fractured lead will either be left inside the patient or removed, depending on specific factors related to the patient and the ICD. (5)