Future Failure Research Articles

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 >95% for all age groups in 31,909 healthy people. This established the boundary between normal variation and mild AS as any of: PV >1.65m/s, MG >4.9mmHg, and AVA <2.1cm2 (men) or <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 < 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 < 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 <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 & 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.

The Relationships Between Linguistic Literacy and Geometric Thinking in 2nd-Graders

ABSTRACT The correlation between linguistic literacy and geometric thinking was investigated in this study, which was conducted among 99 native Hebrew-speaking 2nd-graders. Current results suggest a positive correlation between the study measures. Higher linguistic literacy achievement was linked to higher geometric thinking achievement. Significant differences were found in most literacy measures between children with low and medium-high geometric thinking, in favor of the latter group. The findings suggest that students with a lower level of geometric thinking are also at literacy risk, and that the two processes share cognitive aspects. These relationships appear in 2nd grade, a relatively young age, which can be critical for children’s future development in both domains. Identifying children at risk for developing literacy and geometry difficulties can be essential in planning an integrated curriculum that refers to literacy in all its aspects, as a tool to prevent future failure both in geometry and language arts.

Post‐fledging survival of wedge‐tailed shearwaters is linked to pre‐fledge mass, which has decreased over 40 years

AbstractSeabird populations are declining across their global range due to a variety of threats, including shifting food webs from climate change. The impact of these threats is exacerbated in long‐lived species with low reproductive output and high investment in a few offspring, where juvenile survival is of substantial importance to populations. Changes to post‐fledging survival and recruitment of adults are difficult to detect, necessitating better information to forecast juvenile survival before fledglings take to sea. To achieve this goal, we test the hypothesis that there is an ideal mass range for fledglings, outside of which survival is limited, providing an early warning signal for future recruitment failures. Here we present a long‐term study of chick banding, weighing and resighting of wedge‐tailed shearwaters, Ardenna pacifica, a globally widespread but declining tropical/subtropical seabird in a sea‐surface warming hotspot across a span of 43 years. We provide data on 1615 fledgling birds banded most years between 1977 and 2020, with 111 resighted as adults. We found that fledglings weighing 380–470 g have the best chance to survive to adulthood and those weighing 330–540 g have a possible chance of survival. We detected a gradual decline in masses since data collection began, with chicks fledging, on average, 1.6 g lighter each year. This decline has been sharpest since 1996, with fledging masses decreasing at an average rate of 3.8 g annually. Should this 1.6 g decline continue, the average fledgling will cross out of the ‘survivable’ mass range by 2047/2048. We contextualise these findings with observed declines reported in some populations across the species South Pacific range, adding to the conversation about challenges to seabirds in regions experiencing rapid change.

FRI119 Cardiac Biomarkers In Fabry Disease Exhibit Distinct Associations With Cardiovascular Outcomes: A (Rare) Prism For Cardiovascular Endocrinology

Abstract Disclosure: E. Shemesh: None. R. Rusk: None. P. Feigin: None. P. Deegan: None. Background: Fabry disease (FD) (OMIM 301500) is a rare x-linked metabolic disorder. Cardiovascular involvement in this rare metabolic disorder is common, including hypertrophy, fibrosis, heart failure and arrythmias. Troponin concentrations are often continuously elevated in FD patients, which at times may lead to false assumptions and unnecessary invasive investigations. Furthermore, while nt-proBNP, another cardiac biomarker, is regarded by some as a valuable biomarker in FD, its concentrations might be falsely high due to renal involvement in the disease. We sought to explore the associations between these cardiac biomarkers with myocardial architecture and clinical outcomes in patients with FD. Hypothesis: Biomarkers in FD associate similarly with myocardial architecture and clinical outcomes. Results: 107 patients from a tertiary referral center in the United Kingdom were included in this study. Mean age at first visit was 44.5±17 years. Study population was composed of 40 males and 67 females. Twenty males and 43 females carried a classic mutation. At baseline, 27% had elevated troponin concentrations and 30% of patients had elevated nt-proBNP concentrations. Throughout follow-up, 17 cardiac-related hospitalizations were recorded, and 12 cardiac-related deaths occurred. While troponin and nt-proBNP concentrations at baseline were closely related (r= 0.5, p < 0.05), distinct associations with future occurrence of cardiac architecture pathologies were noted: elevated troponin concentrations associated with presence of late gadolinium enhancement and left ventricular hypertrophy in a statistically significant manner (late gadolinium enhancement: r=0.54, p<0.05; hypertrophy: r-0.45, p<0.05), but nt-proBNP did not. However, both biomarkers associated with adverse clinical outcomes, and nt-proBNP displayed stronger correlation with future heart failure events than troponin (r= 0.52, p<0.05 vs r=0.3, p<0.05). Neither troponin nor nt-proBNP baseline concentrations associated with the implantation of cardiac device (defibrillator or pacemaker). Conclusions: Cardiac biomarkers associate differently with myocardial architecture pathologies, but similarly with clinical outcomes in FD. Our results imply distinct roles for troponin and nt-proBNP in adverse cardiac events in FD. Presentation: Friday, June 16, 2023

The 51-60 cm H2O Artificial Urinary Sphincter Pressure Regulating Balloon: Indications and Outcomes

To describe the role and long-term outcomes of using the 51-60 cm H2O pressure regulating balloon (PRB) in male patients with an artificial urinary sphincter (AUS). From 2005 to 2021, 90 patients with a variety of urethral risk factors underwent AUS placement with use of the low pressure 51-60 cm H2O PRB to treat stress incontinence. Patient demographics, indication for use of the 51-60 cm H2O PRB, perioperative data, and postoperative outcomes were examined and Pearson's chi squared test and Wilcoxon rank sum test were used to identify associations with future revisions, erosion, and mechanical failure. 90 patients were included in the study. After median follow-up of 46.6 months (range: 6 - 146 months), 4 (4.44%) patients developed an erosion-related complication that required device removal, 4 developed an infection, and 3 underwent surgery for pump relocation. One patient had a reported mechanical failure of unknown source. 30 patients underwent revision surgery to reduce incontinence. Of the 4 patients with erosion, 1 was due to iatrogenic catheterization. The remaining 3 had numerous urethral risk factors. Univariate analysis was performed to identify predictors of cuff erosion, infection, and revision in patients with a 51-60 cm H2O PRB. No significant associations were found including prior pelvic radiation, age at AUS placement, presence of IPP, prior AUS erosion, or previous urethroplasty. The low pressure 51-60 cm H2O PRB can be used in high-risk male patients with urinary incontinence with low rates of complications including erosion, infection, and mechanical failure. While patients may choose to undergo future revisional surgery to improve continence, the 51-60 cm H2O PRB should be considered as the initial PRB in patients with urethral risk factors.

Ensemble Deep-Learning Model for Phase-Resolved Partial Discharge Diagnosis in Hydrogenerators

Condition monitoring of hydrogenerators is extremely essential for the optimisation of the power supply system’s maintenance, especially in a context where energy consumption will increase more and more. Industry investigations have consistently shown that the electrical insulation used in stator windings is one of the most potential components for breakdown. One of the major causes of this breakdown was shown to be partial discharges (PDs). PDs are designated as defects in electrical insulation, and their presence may cause future insulation failures in equipment. Online monitoring of PD activity is essential to anticipate degradation and avoid a sudden shutdown with a high economic impact. Thus, automating the recognition of PD sources by an intelligent system is a major issue in a Condition-Based Maintenance (CBM) process for hydrogenators. First, a method based on the U-Net model is used to isolate the main sources of a Phase-Resolved PD signal (PRPD). Afterwards, a set of deep learning models (DLM) is then applied to automatically recognize the PD sources. Finally, a decision-making method is then proposed to find the optimal output category considering the posterior and the prior probability estimated by various individual models. Experimental results on real signals from hydrogenerators show an accuracy of 87% on the detection of gap sources, and respectively 91%, 95%, 96% and 94% for the Internal, Corona, Slot and Delamination PD. The proposed decision-making method shows a significant advantage of the final decision over the performances of each individual DL model.

Automated endpointing in microelectronics failure analysis using laser induced breakdown spectroscopy

Failure analysis of microelectronics is essential to identify the root cause of a device's failure and prevent future failures. This process often requires removing material from the device sample to reach the region of interest, which can be done through various destructive methods, such as mechanical polishing, chemical etching, focused ion beam milling, and laser machining. Among these, laser machining offers a unique combination of speed, precision, and controllability to achieve a high-throughput, highly targeted material removal. In using lasers for processing of microelectronic samples, a much-desired capability is automated endpointing which is crucial for minimizing manual checks and improving the overall process throughput. In this paper, we propose to integrate laser-induced breakdown spectroscopy (LIBS), as a fast and high-precision material detection and process control means, into an ultrashort pulsed laser machining system, to enable vertical endpointing for sample preparation and failure analysis of microelectronics. The capabilities of the proposed system have been demonstrated through several sample processing examples.

The Perils of Overly Sensitive Viral Load Testing for Persons With Human Immunodeficiency Virus.

The concept of "undetectable = untransmittable (U = U)" has been revolutionary in both the prevention and treatment of persons with human immunodeficiency virus (HIV). Most studies proving the concept of U = U used an HIV RNA (viral load [VL]) cutoff of 200 copies/mL to define being undetectable. Since then, increasingly sensitive commercial VL assays, sometimes down to a lower limit of detection (LLD) of 20 copies/mL, lead to confusion about the definition of "undetectable" and when someone is truly considered untransmittable. VLs between the LLD and 200 copies/mL have been associated with future virologic failure; however, no data exist to suggest that intervening in those patients leads to any meaningful benefits. In the absence of a demonstrable benefit of reporting such low VLs, we view this practice as harmful. We suggest recommendations for adjusting VL reporting and improving provider counseling, and call for research designs to mitigate the harms of overly sensitive VL testing.

Estimation Fuzzy Reliability of the Distribution Data (Topp leone- Kumaraswamy)With Application

The process of mixing distributions is one of the vital and important processes that contribute to increasing the flexibility and efficiency of the basic distributions. In this research، a new idea was identified، which is the idea of building a new probability distribution function by the function generating the distributions (Topp - Leone) through the single distribution mode (Kumaraswamy). In the function generated and the derivation of the statistical properties of the resulting new mixed distribution (Kumaraswamy- Topp Leone)، which is characterized by efficiency and flexibility in data representation، as the more parameters of the distribution، the greater the accuracy، reliability and preference، and then estimate the parameters of the aforementioned distribution using the informational standard Bayes estimation methods in light of Different loss functions، and the method of optimization algorithm for the gray wolf (GWO)، the failure times were studied، which are often random and fuzzy mixture in it، and this is expressed in fuzzy numbers، and this leads us to estimate the fuzzy reliability function (Fuzzy Reliability) within certain ranges of belonging to the fuzzy group. Practically applying the (Kum - TL) distribution to the real data obtained from the Ministry of Electricity / South Baghdad Station - Al-Zafaraniya، which numbered (70) engines، representing the operating time of the engine until the failure in order to estimate the expected times of future failures. The results showed that the proposed distribution achieved a clear preference in representing real data. In addition، the results showed the superiority of the (BLS_10) method at all different cut-off levels.

Poor ovarian response in assisted reproductive technology cycles is associated with anti-ovarian antibody and pro-inflammatory immune responses

Anti-ovarian antibody (AOA) could be considered an independent marker for autoimmune ovarian disease and predicting future premature ovarian failure (POF). This study aims to investigate if AOA is associated with poor ovarian response (POR) and pro-inflammatory immune responses in women undergoing assisted reproductive technology (ART) cycles. Two hundred forty-eight women undergoing ART cycles were divided into four groups based on AOA test results and the presence of POR: POR(-)/AOA(-) group (N = 148), POR(+)/AOA(-) group (N = 34), POR (-)/AOA(+) group (N = 44), POR(+)/AOA(+) group (N = 22). The POR patients have a significantly higher prevalence of AOA than non-POR patients (P < 0.05). Peripheral blood CD56 + natural killer (NK) cell level (%), NK cytotoxicity, CD19 +CD5 + B-1 cell level (%), and IFN-γ/IL-10 producing T helper (Th) 1/Th2 cell ratios were significantly higher in POR(+)/AOA(+) group than those of other groups (P < 0.001, P < 0.005, P < 0.01, P < 0.05, respectively). TNF-α/IL-10 producing Th1/Th2 cell ratio of POR(+)/AOA(+) group was significantly higher than those of POR(+)/AOA(-) and POR(-)/AOA(-) groups (P < 0.05, respectively). Homocysteine and vitamin D levels of the POR(+)/AOA(+) group were significantly lower than those of other groups (P < 0.005, respectively). Plasminogen activator inhibiter-1 (PAI-1) level of POR(+)/AOA(+) group was significantly higher than that of POR(-)/AOA(-) group (P < 0.05). In the POR(+)/AOA(+) group, the prevalence of antiphospholipid antibodies was significantly higher than that of the POR(+)/AOA(-) group (P = 0.005). Women with autoimmune POR (POR(+)/AOA(+)) have dysregulated pro-inflammatory immune responses and metabolic factors. The diagnostic and therapeutic approaches for autoimmune POR should be differentiated from those for non-autoimmune POR.

Western Estimates of Russian Military Capabilities and the Invasion of Ukraine

ABSTRACT The poor performance of the Russian military during the invasion of Ukraine came as a surprise to many in the West. This prompted a debate about why Russian capabilities had been overestimated. Fingers were pointed at the work of Western military analysts who, in the eyes of some critics, had based their estimates almost entirely on numbers and technology, resulting in mistaken predictions of a quick and decisive Russian victory. It has since been suggested that changes to the practices of Western military analysis are required if similar future failures are to be avoided. This article takes stock of this debate, proposing that the reasons for Western overestimates of Russian military capabilities and the lessons to be learned from this are far more complex than suggested by the critics. Discussing the political nature of military assessments and defense debates, the problems inherent in military analysis, and the difficulties associated with predicting outcomes in war, it concludes that laying blame for overestimates of Russian military power on Western experts is a fallacy. Expectations of achieving accurate future military assessments by refining the analytical base need to be tempered.