Future Failure Research Articles

Bipolar Head Perforation With Rhabdomyosarcoma of the Thigh: A Case Report With Literature Review.

High complication rates during the perioperative management of sarcomas around the pelvis have been reported; however, few include the detailed clinical course or complications in the late postoperative period. Radiotherapy is a multidisciplinary strategy for treating sarcomas. However, irradiated bone and soft tissues show a permanent loss of repair and immunocompetence. We present a case of pleomorphic rhabdomyosarcoma of the thigh that resulted in acetabular collapse induced by radiation and intestinal perforation during long-term follow-up. Additionally, we discuss the risk factors for late complications and pelvic reconstruction methods. A 75-year-old man presented with a 1-month history of a recurring fever. Ten years prior, he was diagnosed with pleomorphic rhabdomyosarcoma of the right thigh and underwent a wide resection and bipolar hip arthroplasty, followed by chemotherapy and radiotherapy. Radiographs showed central dislocation of the bipolar head. Computed tomography revealed free air in the hip joint and thickening of the colon wall. Colonoscopy revealed displacement of the bipolar head into the colon wall. Colon resection and hip disarticulation were performed, as the bipolar head was contaminated with intestinal contents. Currently, he is able to walk stably with a walker, and there is no evidence of recurrence or metastasis of the tumor. Irradiation of the periacetabular bone may induce resorptive destruction, resulting in future structural failure. Hardware should not be used for periacetabular bone reconstruction; the risk of pelvic organ damage should be considered when the acetabular collapse becomes deteriorated. Therefore, other reliable and permanent reconstruction options are required.

Direct visualization and 3D reconstruction of conductive filaments in aSiO2 material-based memristive device.

Observation of conductive filaments has greatly aided the development of theoretical models of memristive devices. In this work, we visualized and reconstructed the conductive filaments in a Cu/Cu-doped SiO2/W device employing a focused ion beam (FIB) as a milling technique. The SEM images taken from the device after 150 DC sweep cycles showed that Joule heat played a vital role in determining the morphology of a conductive filament, where the vaporization of the conductive filament resulted in the creation of defects, including particles, voids, and cavities. The competition between the formation and vaporization of conductive filaments generally induces a remarkable current fluctuation. Since Cu-doped SiO2 was utilized as the electrolyte, the vapors exfoliated adjacent single layers. FIB milling proceeded in top-down and front-back modes; thus, a 3D model of conductive filaments and defects was constructed according to a series of FIB-SEM images. This methodology is promising for a future failure analysis of memristive devices.

Maintenance management strategies for medical equipment in healthcare institutions: a review

A large amount of medical equipment is now extensively utilized in healthcare institutions to assist clinical practitioners in the diagnosis and treatment of diseases. And the applications of such advanced and sophisticated medical equipment have greatly improved the quality of patient care, significantly alleviated the sufferings of patients, and facilitated their rehabilitation. Nevertheless, failures and malfunctions of medical equipment have compromised its reliability and effectiveness as well as jeopardizing the safety of patients and clinical staffs. And a majority of the failures can be attributed to the insufficient and inappropriate maintenance. Therefore, it is imperative to implement effective maintenance management to ensure that medical equipment is in its optimal function, and thereby mitigating the clinical risk resulted by adverse events. The presented review mainly discussed the maintenance strategies of medical equipment including corrective maintenance, preventive maintenance and predictive maintenance. In order to replace the fixed-interval of preventive maintenance, we systematically discussed methods to adjust the maintenance period. Additionally, two strategies to predicting future failures of medical equipment through processing and analyzing the maintenance data obtained from the historical maintenance logs and condition data collected by the embedded sensors are elaborated. Besides, the classification and life cycle of medical equipment are also summarized.

Glycated haemoglobin, HOMA2-B, C-peptide to glucose ratio and type 2 diabetes clusters as predictors for therapy failure in individuals with type 2 diabetes without insulin therapy: A registry analysis.

Some people with type 2 diabetes mellitus (T2D) and declining β-cell function do require insulin over time. Various laboratory parameters, indices of glucose metabolism or phenotypes of T2D (clusters) have been suggested, which might predict future therapy failure (TF), indicating the need for insulin therapy initiation. This analysis evaluated glycated haemoglobin (HbA1c), homeostatic model assessment (HOMA)2-B, C-peptide to glucose ratio (CGR) and diabetes clusters as predictive parameters for the occurrence of glycaemic TF in individuals diagnosed with T2D without previous insulin therapy. In total, 159 individuals with T2D [41% female, median age 50 (IQR: 53-69) years, diabetes duration 9 (5-15) years], without insulin therapy were prospectively evaluated for the occurrence of a composite primary endpoint, including HbA1c increasing or remaining >8.0% (64 mmol/mol) 3 months after baseline on non-insulin glucose-lowering agents, insulin initiation or hospital admissions because of acute hyperglycaemic events. Diabetes clusters were formed according to previously described characteristics. Only severe autoimmune diabetes clusters were excluded because of a small amount of glutamate decarboxylase antibody-positive participants. The other clusters were distributed as mild age-related diabetes 33%; severe insulin-deficient diabetes 31%; mild obesity-related diabetes 20%; and severe insulin-resistant diabetes 15%. During a median observation of 57 months, higher tertiles of HbA1c at baseline, HOMA2-B, as well as a lower CGR were significantly predictive for the occurrence of the primary endpoint. The probability of meeting the primary endpoint was the highest for mild obesity-related diabetes [hazard ratio 3.28 (95% confidence interval 1.75-6.2)], followed by severe insulin-deficient diabetes [hazard ratio 2.03 (95% confidence interval 1.1-3.7)], mild age-related diabetes and the lowest for severe insulin-resistant diabetes. The best performance to predict TF with an area under the curve (AUC) of 0.77 was HbA1c at baseline, followed by HOMA2-B (AUC 0.69) and CGR (AUC 0.64). HbA1c, indices of insulin secretion capacity (HOMA2-B and CGR) and T2D clusters might be applicable tools to guide practitioners in the decision of whether insulin is required in people already diagnosed with T2D. These findings need to be validated in prospective studies.

Free mebrofenin clearance.

To determine if three new simplified equations for measurement of free mebrofenin clearance give similar results to the equations defined by Ekman et. al ., and to evaluate the properties of all four methods. Regional mebrofenin clearance has been used to predict future remnant liver function and liver failure after regional liver therapy, such as partial hepatic resection. The means, standard deviations, and correlations of the free mebrofenin clearance measured by the Ekman method and the three simplified methods were compared in a consecutive series of 26 studies in 20 patients. The fractional change in the blood and free mebrofenin activities were compared, and integrals of normalized blood and free mebrofenin ("effective times") were compared. The average percent free mebrofenin clearance for the Ekman and the first, second and third simplified methods were 13.62 ± 2.88%/min, 12.98 ± 2.97%/min, 12.52 ± 2.81%/min and 15.03 ± 2.27%/min, respectively. The correlations of the new methods with Ekman were 0.97, 0.93 and 0.93. The fractional changes during the measurement interval for the blood and free mebrofenin activities were 0.381 ± 0.065 and 0.329 ± 0.062, difference 0.052, P < 0.5. The integrals of normalized blood and free mebrofenin activities were 2.566 ± 0.160 min and 2.661 ± 0.158 min, difference of 0.094 min and P < 0.05. The results of the three new methods were similar to the Ekman method. The first simplified method was identified as the lead method for clinical validation in a larger population.

Proteomic prediction of incident heart failure and its main subtypes.

To examine the ability of serum proteins in predicting future heart failure (HF) events, including HF with reduced or preserved ejection fraction (HFrEF or HFpEF), in relation to event time, and with or without considering established HF-associated clinical variables. In the prospective population-based Age, Gene/Environment Susceptibility Reykjavik Study (AGES-RS), 440 individuals developed HF after their first visit with a median follow-up of 5.45 years. Among them, 167 were diagnosed with HFrEF and 188 with HFpEF. A least absolute shrinkage and selection operator regression model with non-parametric bootstrap were used to select predictors from an analysis of 4782 serum proteins, and several pre-established clinical parameters linked to HF. A subset of 8-10 distinct or overlapping serum proteins predicted different future HF outcomes, and C-statistics were used to assess discrimination, revealing proteins combined with a C-index of 0.80 for all incident HF, 0.78 and 0.80 for incident HFpEF or HFrEF, respectively. In the AGES-RS, protein panels alone encompassed the risk contained in the clinical information and improved the performance characteristics of prediction models based on N-terminal pro-B-type natriuretic peptide and clinical risk factors. Finally, the protein predictors performed particularly well close to the time of an HF event, an outcome that was replicated in the Cardiovascular Health Study. A small number of circulating proteins accurately predicted future HF in the AGES-RS cohort of older adults, and they alone encompass the risk information found in a collection of clinical data. Incident HF events were predicted up to 8 years, with predictor performance significantly improving for events occurring less than 1 year ahead, a finding replicated in an external cohort study.

Central stress pathways in the development of cardiovascular disease.

Mental stress is of essential consideration when assessing cardiovascular pathophysiology in all patient populations. Substantial evidence indicates associations among stress, cardiovascular disease and aberrant brain-body communication. However, our understanding of the flow of stress information in humans, is limited, despite the crucial insights this area may offer into future therapeutic targets for clinical intervention. Key terms including mental stress, cardiovascular disease and central control, were searched in PubMed, ScienceDirect and Scopus databases. Articles indicative of heart rate and blood pressure regulation, or central control of cardiovascular disease through direct neural innervation of the cardiac, splanchnic and vascular regions were included. Focus on human neuroimaging research and the flow of stress information is described, before brain-body connectivity, via pre-motor brainstem intermediates is discussed. Lastly, we review current understandings of pathophysiological stress and cardiovascular disease aetiology. Structural and functional changes to corticolimbic circuitry encode stress information, integrated by the hypothalamus and amygdala. Pre-autonomic brain-body relays to brainstem and spinal cord nuclei establish dysautonomia and lead to alterations in baroreflex functioning, firing of the sympathetic fibres, cellular reuptake of norepinephrine and withdrawal of the parasympathetic reflex. The combined result is profoundly adrenergic and increases the likelihood of cardiac myopathy, arrhythmogenesis, coronary ischaemia, hypertension and the overall risk of future sudden stress-induced heart failure. There is undeniable support that mental stress contributes to the development of cardiovascular disease. The emerging accumulation of large-scale multimodal neuroimaging data analytics to assess this relationship promises exciting novel therapeutic targets for future cardiovascular disease detection and prevention.

Failure analysis on premature perforation of multiple effect evaporators in vacuum salt making system

Multiple effect evaporators (MEEs) are extensively utilized across diverse industries, such as pulp and paper, sugar, and desalination, for the purpose of concentration and purification. Nevertheless, MEEs often bring forth the issue of corrosion because of severe service conditions, thereby leading to equipment damage and decrease in efficiency. This study scrutinizes the premature perforation and corrosion of some multiple effect evaporators encountered soon after their commencement in a salt processing plant. The failed MEEs, designed to serve for 15 years, underwent severe corrosion and the emergence of multiple leakage points during a trial run of 40 days, with only 18 days of actual operation. To unearth the reasons for this failure, various macroscopic and microscopic analyses were carried out. The studies demonstrated that welding defects not found in time during the fabrication of evaporators reduced the corrosion resistance of the composite plate. Additionally, improper welding during the maintenance made the repair ineffective. Once the stainless-steel cladding layer was damaged, the carbon steel backing layer corroded and perforated rapidly under galvanic corrosion. Based on these findings, effective countermeasures were suggested to evade any future failures of the same kind. The outcomes of this analysis are likely to aid in enhancing the operational safety and reliability of multiple effect evaporators in vacuum salt-making systems.

Rainfall-induced transportation embankment failure: A review

Abstract Rainfall is one of the leading causes of transportation embankment failure. Similarly, the fill material properties and the loading conditions of the embankment serve as principals for assessing the mechanisms of potential failures that are derived from rainfall-related events. These events affect the hydro-mechanical behaviors of embankment fills and cast doubt on the construction and service life of most transportation-infrastructure. This article presents a review, of existing available records to critically examine rainfall-induced transportation embankment failures, causes, mechanisms, existing measures, and prevention techniques. Consequently, a review of the susceptibility assessment of infrastructures due to rainfall-induced failures, particularly in China, and embankment characteristics and their effects on the duration, magnitude, and safety of the infrastructures was carried out. The study was able to classify rainfall conditions as they influence embankment stability. We suggest the development of local and global rainfall-embankment fill material relationships that will give unique information on how rainfall-events change the behavior of fill material and to what extent they trigger failures. A summary of some of the active processes leading to transportation embankment failures is presented. Finally, we concluded by identifying future and prospective rainfall-induced transportation embankment failures that will enhance monitoring and mitigation of instability in embankments.

Resilience improvement of cyber-physical supply chain networks considering cascading failures with mixed failure modes

Failure mode analysis and recovery strategy improvement are critical to maintain the resilience of cyber-physical supply chain networks (CPSCNs). However, current literature mostly focuses on single failure mode and single-stage recovery strategy for CPSCNs, which may not be the case for real-world CPSCNs. In this paper, a new cascading failure model with four mixed failure modes and a joint improvement model for two-stage recovery regarding CPSCNs are proposed. A CPSCN model consisting of a weighted undirected cyber-supply network and a weighted directed physical-supply network is established to investigate the mixed cascading failures. Given the recovery requirements of practical contracts, the recovery time constraint on the enterprises in CPSCNs is considered in the joint improvement model of two-stage recovery. Based on the case studies of synthetic networks and a European supply chain network, the effects of some key factors, such as network topology and node coupling modes, on the resilience of CPSCNs are discussed. The performance of the proposed recovery strategy is compared with two traditional network recovery strategies, and the results show that the proposed strategy can help restore network performance more effectively. This work provides insights for CPSCNs recovery with resilience improvement against future cascading failures.

Radiomics of pericardial fat: a new frontier in heart failure discrimination and prediction

ObjectivesTo use pericardial adipose tissue (PAT) radiomics phenotyping to differentiate existing and predict future heart failure (HF) cases in the UK Biobank.MethodsPAT segmentations were derived from cardiovascular magnetic resonance (CMR) studies using an automated quality-controlled model to define the region-of-interest for radiomics analysis. Prevalent (present at time of imaging) and incident (first occurrence after imaging) HF were ascertained using health record linkage. We created balanced cohorts of non-HF individuals for comparison. PyRadiomics was utilised to extract 104 radiomics features, of which 28 were chosen after excluding highly correlated ones (0.8). These features, plus sex and age, served as predictors in binary classification models trained separately to detect (1) prevalent and (2) incident HF. We tested seven modeling methods using tenfold nested cross-validation and examined feature importance with explainability methods.ResultsWe studied 1204 participants in total, 297 participants with prevalent (60 ± 7 years, 21% female) and 305 with incident (61 ± 6 years, 32% female) HF, and an equal number of non-HF comparators. We achieved good discriminative performance for both prevalent (voting classifier; AUC: 0.76; F1 score: 0.70) and incident (light gradient boosting machine: AUC: 0.74; F1 score: 0.68) HF. Our radiomics models showed marginally better performance compared to PAT area alone.Increased PAT size (maximum 2D diameter in a given column or slice) and texture heterogeneity (sum entropy) were important features for prevalent and incident HF classification models.ConclusionsThe amount and character of PAT discriminate individuals with prevalent HF and predict incidence of future HF.Clinical relevance statementThis study presents an innovative application of pericardial adipose tissue (PAT) radiomics phenotyping as a predictive tool for heart failure (HF), a major public health concern. By leveraging advanced machine learning methods, the research uncovers that the quantity and characteristics of PAT can be used to identify existing cases of HF and predict future occurrences. The enhanced performance of these radiomics models over PAT area alone supports the potential for better personalised care through earlier detection and prevention of HF.Key Points•PAT radiomics applied to CMR was used for the first time to derive binary machine learning classifiers to develop models for discrimination of prevalence and prediction of incident heart failure.•Models using PAT area provided acceptable discrimination between cases of prevalent or incident heart failure and comparator groups.•An increased PAT volume (increased diameter using shape features) and greater texture heterogeneity captured by radiomics texture features (increased sum entropy) can be used as an additional classifier marker for heart failure.

AVAILABILITY AND RELIABILITY INDICES: A PRACTICAL APPROACH FOR AFAM THERMAL PLANT ASSESSMENT AND IMPROVEMENT

Mechanical integrity and risk analysis for power stations are often based on few failure data. The risk issue is to reduce and forecast future failure and corrective actions taken to mitigate down time. The power station has been acquiring equipment failure data for many years. Seldom is the data analyzed in a scientific manner, and rarely the acquired data used to solve their maintenance problem. The objective of this paper is to mine piles of existing data and how age to failure data can be in a thoughtful manner and used for reliability and availability purposes. Weibulll graph is used for the failure data.

Abstract 14595: Leveraging Deep Learning to Elucidate Subclinical Aortic Stenosis Risk

Background and Aims: Aortic stenosis (AS) is associated with a high global burden of morbidity. Current guidelines do not fully define normal aortic valve (AV) function or mild AS. We aimed to study normal variation in AV function and address current gaps in knowledge. Methods: We developed a deep learning model to study velocity-encoded magnetic resonance imaging (MRI) in 47,223 UK Biobank participants. We calculated aortic valve area (AVA), peak velocity (PV), and mean gradient (MG). Results: In healthy individuals, we found an annual decrement of 0.03 cm2 in AVA. Normal variation in AV function was predictive of future AV surgery (HR 2.4 per SD increase in PV, P2.6E-110), heart failure (HR 1.23 per SD, P=2.4E-07), and coronary disease (HR 1.23 per SD, P=2.0E-14). Risk was still elevated when excluding participants with moderate-to-severe AS. We determined thresholds for abnormal AV function as being &gt;95% for all age groups in 31,909 healthy people. This established the boundary between normal variation and mild AS as any of: PV &gt;1.65m/s, MG &gt;4.9mmHg, and AVA &lt;2.1cm2 (men) or &lt;1.7cms2 (women). A total of 3,288 participants (7.0%) met the definition of mild AS which was associated with high risk for AV surgery (HR 57.2, P=4.4E-29). Over a mean 3.1±2.0 years of follow-up, the incidence of AV surgery was 0.02% in those with normal AV function and nearly 20% among participants with MG ≥10mmHg. Greater levels of ApoB, triglycerides, Lp(a), and inflammatory markers were associated with higher AV gradients. Conclusion: In this study, we report the largest analysis of AV function and cardiovascular disease in the general population with MRI using deep learning. We propose thresholds to define the lower bounds of mild AS and demonstrate a step change in cardiovascular risk between normal AV function and mild AS. Atherogenic and inflammatory biomarkers were associated with increased AV gradients. These findings may inform earlier surveillance and efforts to prevent complications of AS.

Abstract 12928: Deep Learning-Derived Characterization of Lung Tissue Predicts Future Diagnosis of Heart Failure

Background: Cardiovascular and respiratory diseases are intrinsically coupled. Scalable methods for quantifying cardiac and pulmonary structures may improve our understanding of cardiopulmonary disease. Aims: We sought to quantify textural parameters of the lung fields in cardiovascular magnetic resonance imaging (cMRI) from the UK Biobank. We then sought to determine their genetic basis and their relationship with heart failure. Methods: We fine-tuned a convolutional neural network to segment left and right lung on cMRIs performed during expiratory breath hold. A random sample of 300 coronal slices from unique individuals was manually annotated for fine-tuning. The model was applied to 912,320 coronal cMRI images. Segmentation masks were stacked, and lung volume and texture metrics were quantified from the resulting 3D masks using the pyradiomics Python package. Results: After quality control, we computed lung traits in 45,179 participants. Mean lung volume was 2.19 ± 0.49 L in women and 2.87 ± 0.68 L in men. After adjustment for age and sex, lung volume was associated with forced vital capacity (FVC) (β = +0.30 L per SD, p &lt; 1.1 х 10 -308 ). After adjustment for age and sex, body size traits (e.g. standing height and heel bone mineral density) were associated with increased lung volume, whereas adiposity traits (e.g. body mass index and visceral adipose tissue) were associated with decreased lung volume. Greater heterogeneous and coarse lung textures were associated with an increased risk of heart failure (1-SD hazard ratios: 1.21 (95% CI [1.12, 1.31]) and 1.32 (95% CI [1.18, 1.47]), respectively). This association was still significant among non-smokers and after adjustment for left ventricular ejection fraction. Conclusions: Deep-learning derived measures of lung texture are linked to future heart failure. Our findings suggest that heart failure may manifest as changes in lung tissue that are detectable on MRI before changes in cardiac function.

Abstract 19109: AI-Enabled Automated Cardiac Chambers Volumetry in ECG-Gated Coronary Calcium Scans vs. Non-Gated Lung Cancer Screening Scans

Introduction: We have developed an AI-enabled automated volume measurement of cardiac chambers (AutoChamber) that works on ECG-gated non-contrast coronary artery calcium scans and correlates well with contrast enhanced coronary CT angiography scans. Automated LA and LV volumes have shown to predict atrial fibrillation (Afib) and congestive heart failure. Hypothesis: In this study, we hypothesize that AutoChamber volumetry results in ECG-gated CAC scans correlated well with those of non-gated full-chest lung cancer screening scans in the same individuals. Methods: We have studied 169 cases of paired ECG-gated cardiac CT scans and non-gated lung scans. Mean±SD for age was 62±10 with 52% female. All caseswere asymptomatic and were scanned for preventive health assessment. AutoChamber was run on all cases by an independent operator who was not involvedin data analysis. P value was calculated using a two-tailed test of significance with α=0.05. Results: AutoChamber in cardiac scans vs lung scans reported volume (Mean±SD) for left atrium (LA) as 67.2 and 70.1, left ventricle (LV) 102.8 and 105.5 right atrium (RA) 81.9 and 85.7 right ventricle (RV) 140.7 and 134.2 left ventricle wall (LVW) 113.0 and 109.7 respectively (P &lt; 0.0001). Correlations between cardiac and lung scans for each cardiac chamber: LA (R2= 0.85), LV (R 2= 0.93), RA (R2= 0.91), RV (R2= 0.92), and left ventricular wall (LVW) R2= 0.95. (P &lt;0.0001 for all). Conclusions: AutoChamber volumetry results are similar in ECG-gated cardiac scans vs non-gated full-chest lung scans. This AI-enabled automated tool is promising as it can provide added value to patients undergoing coronary calcium and lung cancer screening scans flagging enlarged cardiac chambers at risk of future Afib and heart failure.

Analysis of FRP-Strengthened Reinforced Concrete Beams Using Electromechanical Impedance Technique and Digital Image Correlation System.

Fiber-reinforced polymer (FRP) strengthening systems have been considered an effective technique to retrofit concrete structures, and their use nowadays is more and more extensive. Externally bonded reinforcement (EBR) and near-surface mounted (NSM) technologies are the two most widely recognized and applied FRP strengthening methods for enhancing structural performance worldwide. However, one of the main disadvantages of both approaches is a possible brittle failure mode provided by a sudden debonding of the FRP. Therefore, methodologies able to monitor the long-term efficiency of this kind of strengthening constitute a challenge to be overcome. In this work, two reinforced concrete (RC) specimens strengthened with FRP and subjected to increasing load tests were monitored. One specimen was strengthened using the EBR method, while for the other, the NSM technique was used. The multiple cracks emanating in both specimens in the static tests, as possible origins of a future debonding failure, were monitored using a piezoelectric (PZT)-transducer-based electromechanical impedance (EMI) technique and a digital image correlation (DIC) system. Clustering approaches based on impedance measurements of the healthy and damaged states of the specimens allowed us to suspect the occurrence of cracks and their growth. The strain profiles captured in the images of the DIC system allowed us to depict surface hair-line cracks and their propagation. The combined implementation of the two techniques to look for correlations during incremental bending tests was addressed in this study as a means of improving the prediction of early cracks and potentially anticipating the complete failure of the strengthened specimens.

Design, Load Analysis and Optimization of Epicyclic Gear Trains

Abstract: Mechanical power transmission systems rely heavily on Epicyclic gear trains, as their failure can compromise the entire system. Consequently, identifying and mitigating the causes of gear failure is crucial. Various gear failure modes, including bending pitting (contact stresses), failure (load failure), abrasive wear, and scoring, are discussed in literature by J.R. Davis(2005) [24], Khurmi &amp; Gupta (2006) [23], and P. Kannaiah (2006) [21][22]. These failures are often linked to the loads acting on the gears. This research focuses on optimizing gear design to reduce gear load failure. Table 1 summarizes various research efforts on Epicyclic gear trains conducted by different authors. This study delves into the optimization of epicyclic gear trains in India to minimize load failure. The analysis focuses on optimizing the gear train through load analysis of the pinions, gears, and annulus, including the sun and planet gears. The goal is to determine the optimal load conditions for the gear train to function effectively without succumbing to load failure. Epicyclic Gear Trains are widely used in industry due to their numerous advantages, including high torque capacity, improved efficiency, relatively smaller size, lower weight, and a highly compact package. However, there has been no comprehensive study of their load-bearing performance with respect to various parameters such as rotational speed, material, and power. This research paper aims to fill this gap by investigating the load performance of epicyclic gear trains under different parameters such as loading conditions and rotational speeds. This process helps in identifying the optimized design of epicyclic gear trains, ensuring optimal performance and minimizing gear loads and choosing correct rotational speed. The primary objective of this research investigation is to optimize epicyclic gear trains through load analysis to prevent future load failures.

Exploring the feasibility of introducing triple artemisinin-based combination therapy in the malaria treatment policy in Vietnam

BackgroundThis study investigates the processes regarding changing malaria treatment policies in Vietnam. Moreover, it explores the feasibility of introducing triple artemisinin-based combination therapy (TACT) in Vietnam to support the national malaria control and elimination plan.MethodsData were collected via 12 in-depth interviews with key stakeholders, combined with a review of policy documents.ResultsTACT is considered as a useful backup strategy in case future treatment failures with current artemisinin-based combination therapy (ACT) would occur. Moreover, TACT is also considered as a promising strategy to prevent the re-establishment of malaria. However, regulatory procedures and implementation timelines for TACT were expected to be lengthy. Therefore, strategies to engage national decision-makers, regulators, and suppliers should be initiated soon, stipulating the benefits of TACT deployment. In Vietnam, a procedure to apply for an import permit without registration that has previously been applied to the introduction of artesunate-pyronaridine was proposed to accelerate the introduction of TACT. Global-level support through the World Health Organization recommendations and prequalification were considered critical for supporting the introduction of TACT in Vietnam.ConclusionsAppropriate approach strategies and early stakeholder engagement will be needed to accelerate the introduction of TACT in Vietnam.

Local corrosion behavior of pipeline steel under deposition layer in produced water of Alkali/ Surfactants/ Polymers

The metal pipelines in ASP(Alkali/ Surfactants/ Polymers) flooding systems will suffer from severe under deposit corrosion. In this work, the corrosion behavior of AISI 1020 carbon steel under the deposition of SiO2 or CaCO3 was investigated in produced fluids of ASP (Alkali/ Surfactants/ Polymers) flooding. The results showed that the deposition layer inhibited the uniform corrosion of the metal and promoted the localized corrosion of the metal, and the promotion effect of the calcium carbonate deposition layer was stronger than that of the silica deposition layer. The metal corrosion product under the SiO2 deposition layer was Fe3O4 and FeOOH, and the metal corrosion product under the CaCO3 deposition layer was Fe3O4 and Fe2O3. The type and extent of localized corrosion have varied due to differences in deposited layers and corrosion products. The occurrence and development of localized corrosion of metals under deposition can be monitored by WBE. Based on the above conclusions, appropriate corrosion mitigation strategies are proposed to prevent future failures.

Biomechanical causes for failure of the Physiomesh/Securestrap system

This study investigates the mechanical behavior of the Physiomesh/Securestrap system, a hernia repair system used for IPOM procedures associated with high failure rates. The study involved conducting mechanical experiments and numerical simulations to investigate the mechanical behavior of the Physiomesh/Securestrap system under pressure load. Uniaxial tension tests were conducted to determine the elasticity modulus of the Physiomesh in various directions and the strength of the mesh-tissue-staple junction. Ex-vivo experiments on porcine abdominal wall models were performed to observe the system's behavior under simulated intra-abdominal pressure load. Numerical simulations using finite element analysis were employed to support the experimental findings. The results reveal nonlinearity, anisotropy, and non-homogeneity in the mechanical properties of the Physiomesh, with stress concentration observed in the polydioxanone (PDO) stripe. The mesh-tissue junction exhibited inadequate fixation strength, leading to staple pull-out or breakage. The ex-vivo models demonstrated failure under higher pressure loads. Numerical simulations supported these findings, revealing the reaction forces exceeding the experimentally determined strength of the mesh-tissue-staple junction. The implications of this study extend beyond the specific case of the Physiomesh/Securestrap system, providing insights into the mechanics of implant-tissue systems. By considering biomechanical factors, researchers and clinicians can make informed decisions to develop improved implants that mimic the mechanics of a healthy abdominal wall. This knowledge can contribute to better surgical outcomes and reduce complications in abdominal hernia repair and to avoid similar failures in future.