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The COVID-19 pandemic precipitated a surge in the non-performing assets held by financial institutions, elevating systemic risk in financial networks. Therefore, developing strategies to alleviate this risk, with a focus on non-performing assets, has become a research area of interest. Supported by policies related to the Chinese insurance market, this study proposes the establishment of a non-performing assets disposal fund backed by insurance capital. This fund will invest in the non-performing assets of financial institutions with the aim of mitigating systemic risk. Using a linear threshold model, we identify an asymptotically optimal scheme for disposing of non-performing assets. Additionally, we construct a payment model integrated with non-performing assets, from which we derive an optimal payment and clearing strategy. Our research also proposes a robust set of criteria to assist regulators in determining whether to use the non-performing assets disposal fund. To demonstrate the efficacy of the fund in reducing systemic risk, we conduct simulations and analyze data from the Chinese interbank financial network. Through this rigorous analysis, we confirm the role of the fund in enhancing the stability of the financial system. [ABSTRACT FROM AUTHOR]

This paper studies countries' economic dependence on China through trade. As China's importance in the world economy has grown significantly in recent years, developments in China will increasingly be reflected in its trading partners' economic performance. Therefore, measuring and identifying countries' economic exposure to China has become increasingly relevant. Responding to the need by risk management practitioners in financial institutions, the paper builds a tool to measure and compare countries' exposure to the Chinese economy through trade channels, using principal component analysis. The resultant China Trade Exposure Index ranks countries based on their economic dependence on trade with China. The utilisation possibilities of the index are broad, yet the most obvious application is in financial institutions' stress testing exercises. Indeed, the index can be used in a China-specific stress testing scenario to transmit a shock to other countries according to their China dependence. To validate the relevance of the index, the paper further shows that the China Trade Exposure Index is significant in explaining countries' cyclical economic growth co-movement with China, with a higher ranking implying a stronger real gross domestic product (GDP) growth correlation. Therefore, the China Trade Exposure Index helps global investors, risk professionals and policymakers in analysing potential China-related country risks. [ABSTRACT FROM AUTHOR]

Backend constitutes a critical component of digital infrastructure, responsible for processing business logic, managing data, and facilitating communication between software systems. APIs serve as the interface that enables software interaction and plays a pivotal role in backend operations. This study investigates the performance of three API architectures: RESTful, GraphQL, and gRPC. The experimental approach involves the implementation of Load Testing and Stress Testing to assess the performance of these architectures. The experiment utilizes a dedicated server and client hardware to simulate real-world conditions, with parameters such as CPU usage, memory usage, response time, load time, latency, success rate, and failure rate evaluated using a dataset comprising 1,000 rows of student-related records. Result show that RESTful achieves the highest total request but exhibit greater resource consumption and a higher failure rate. GraphQL demonstrated better CPU and memory efficiency with strong stability, though it has higher latency and slower response times. gRPC strikes a balance with a moderate latency and resource usage, albeit with slightly higher memory consumption under stress. By presenting a comprehensive analysis of each API architecture, this study contributes a comprehensive performance analysis under practical testing scenarios giving developers and system architect with data-driven guidance for selecting API architecture to their application needs. RESTful is well suited for high-throughput scenarios with less critical operations, GraphQL excels in resource efficiency and stability, and gRPC offers balanced performance across diverse workloads.

Abstract The COVID-19 pandemic precipitated a surge in the non-performing assets held by financial institutions, elevating systemic risk in financial networks. Therefore, developing strategies to alleviate this risk, with a focus on non-performing assets, has become a research area of interest. Supported by policies related to the Chinese insurance market, this study proposes the establishment of a non-performing assets disposal fund backed by insurance capital. This fund will invest in the non-performing assets of financial institutions with the aim of mitigating systemic risk. Using a linear threshold model, we identify an asymptotically optimal scheme for disposing of non-performing assets. Additionally, we construct a payment model integrated with non-performing assets, from which we derive an optimal payment and clearing strategy. Our research also proposes a robust set of criteria to assist regulators in determining whether to use the non-performing assets disposal fund. To demonstrate the efficacy of the fund in reducing systemic risk, we conduct simulations and analyze data from the Chinese interbank financial network. Through this rigorous analysis, we confirm the role of the fund in enhancing the stability of the financial system.

Together with other "bottom‐up" methods, climate stress testing is becoming a prominent approach for climate change impact assessment of water systems. Compared with traditional approaches, stress testing is: (i) more focused on exploring the vulnerabilities of the system at hand; (ii) potentially more inclusive, being amenable to stakeholder involvement and (iii) well suited to identify robust policy options that better account for the deep uncertainty associated with multiple plausible futures. Stress testing is rapidly evolving and giving rise to new techniques and concepts, but few articles provide an accessible overview that can serve as an introduction to the field. Here, we review the underlying principles and concepts of climate stress testing, providing a guide to the main decisions involved in practical application. Topics include selection of stressors, characterizing and exploring the exposure space and data generation including the use of stochastic data. In a complex world where water decisions are made in the context of wider socio‐ecological systems, stress testing and other bottom‐up methods can support decisions that are not only robust to future uncertainty but also regarded as legitimate by affected communities. This article is categorized under:Engineering Water > Sustainable Engineering of WaterScience of Water > Water and Environmental ChangeWater and Life > Stresses and Pressures on Ecosystems [ABSTRACT FROM AUTHOR]

Wind power generation is expected to greatly contribute to the future of humanity as a promising source of renewable energy. However, the high variability inherent in wind is a challenge that hinders stable power generation. To utilize wind power as a primary energy source, integration with a polymer electrolyte membrane water electrolysis (PEMWE) system is proposed. Yet, PEMWE is known to suffer from degradation when exposed to input power patterns with high variability. This poses challenges to its commercialization. This necessitates stress testing with various wind power fluctuations during the production process of the devices. This study investigates representative patterns of wind power fluctuation so that these patterns can be used for the stress testing process. We employ data-mining techniques, including the swing door algorithm and k-means clustering, to identify these patterns by analyzing wind power generation data at a 10-s interval. As a result, the five most representative wind power ramps are presented. This study provides practical guidelines for the development process of expensive devices for wind power generation, thereby promoting the active utilization of wind power generation. [ABSTRACT FROM AUTHOR]

Forced degradation subjects drug substances to stress conditions, producing degradation products that are crucial for evaluating stability under accelerated conditions. Imeglimin hydrochloride is a commonly prescribed medicine for managing type 2 diabetes mellitus. This study details the forced degradation experiments and LC-MS analysis of degraded products of Imeglimin Hydrochloride under various stress conditions, offering insights into its stability and providing information on fragmentation pathways and major degradation products. The optimized mobile phase for the LC-MS method was composed of 10 mM ammonium format buffer (pH 3): methanol with a ratio of 75:25 v/v, obtained on an Xtimate C-18 column (flow rate of 0.8 ml/min), with 234 nm as the specific detection wavelength for Imeglimin Hydrochloride. The drug was subjected to stress conditions including photolysis, hydrolysis, thermal, and oxidative stress conditions. After various stress conditions were applied, the complete stability pathways and effects of these stress conditions were examined. Imeglimin hydrochloride underwent degradation when exposed to oxidative conditions at room temperature and basic conditions at elevated temperatures. However, specific degradation products were not found under acidic, thermal, and photolytic stress conditions. By comparing predicted and observed fragmentation patterns and identifying base peaks, LC-MS analysis of Imeglimin Hydrochloride revealed two new degradation products, DP1 (m/z 160.2) and DP2 (m/z 118.0) under oxidative and basic stress conditions, respectively. The developed method was validated as per the guidelines of analytical method validation. [ABSTRACT FROM AUTHOR]

We propose an optimization-simulation method for determining combinations of influences that make it possible to remove an organizational and technical system from a potentially unfavorable state. We demonstrate the solution using the example of the inverse problem of stress testing mature companies in traditional industries of the real sector. A condition for a company to be in a potentially unfavorable state is a projected negative cash balance. To determine changes that improve the forecast, mathematical programming methods solve the problem of maximizing the benefits from such changes—the difference between the predicted cash balance and the costs of changes. The results obtained can be applied when solving issues of stabilization under risk conditions: pandemics, economic sanctions, natural disasters, etc. A model example is given. [ABSTRACT FROM AUTHOR]

Background: There is wide variation in stress test utilization before major vascular surgery and adherence to practice guidelines is unclear. We defined rates of stress test compliance at our institution and led a quality improvement initiative to improve compliance with American Heart Association (ACC/AHA) guidelines. Methods: We implemented a stress testing order set in the electronic medical record at one tertiary hospital. We reviewed all patients who underwent elective, major vascular surgery in the 6 months before (Jan 1, 2022 – Jul 1, 2022) and 6 months after (Aug 1, 2022 – Jan 31, 2023) implementation. We studied stress test guideline compliance, changes in medical or surgical management, and major adverse cardiac events (MACE). Results: Before order set implementation, 37/122 patients (30%) underwent stress testing within the past year (29 specifically ordered preoperatively) with 66% (19/29) guideline compliance. After order set implementation, 50/173 patients (29%) underwent stress testing within the past year (41 specifically ordered preoperatively) with 80% (33/41) guideline compliance. In the pre- and postimplementation cohorts, stress testing led to a cardiovascular medication change or preoperative coronary revascularization in 24% (7/29) and 27% (11/41) of patients, and a staged surgery or less invasive anesthetic strategy in 14% (4/29) and 4.9% (2/41) of patients, respectively. All unindicated stress tests were surgeon-ordered and none led to a change in management. There was no change in MACE after order set implementation. Conclusions: Electronic medical record-based guidance of perioperative stress testing led to a slight decrease in overall stress testing and an increase in guideline-compliant testing. Our study highlights a need for improved preoperative cardiovascular risk assessment prior to major vascular surgery, which may eliminate unnecessary testing and more effectively guide perioperative decision-making. [ABSTRACT FROM AUTHOR]

Aims This study aimed to determine in patients undergoing stress cardiovascular magnetic resonance (CMR) whether fully automated stress artificial intelligence (AI)-based left ventricular ejection fraction (LVEFAI) can provide incremental prognostic value to predict death above traditional prognosticators. Methods and results Between 2016 and 2018, we conducted a longitudinal study that included all consecutive patients referred for vasodilator stress CMR. LVEFAI was assessed using AI algorithm combines multiple deep learning networks for LV segmentation. The primary outcome was all-cause death assessed using the French National Registry of Death. Cox regression was used to evaluate the association of stress LVEFAI with death after adjustment for traditional risk factors and CMR findings. In 9712 patients (66 ± 15 years, 67% men), there was an excellent correlation between stress LVEFAI and LVEF measured by expert (LVEFexpert) (r = 0.94, P < 0.001). Stress LVEFAI was associated with death [median (interquartile range) follow-up 4.5 (3.7–5.2) years] before and after adjustment for risk factors [adjusted hazard ratio, 0.84 (95% confidence interval, 0.82–0.87) per 5% increment, P < 0.001]. Stress LVEFAI had similar significant association with death occurrence compared with LVEFexpert. After adjustment, stress LVEFAI value showed the greatest improvement in model discrimination and reclassification over and above traditional risk factors and stress CMR findings (C -statistic improvement: 0.11; net reclassification improvement = 0.250; integrative discrimination index = 0.049, all P < 0.001; likelihood-ratio test P < 0.001), with an incremental prognostic value over LVEFAI determined at rest. Conclusion AI-based fully automated LVEF measured at stress is independently associated with the occurrence of death in patients undergoing stress CMR, with an additional prognostic value above traditional risk factors, inducible ischaemia and late gadolinium enhancement. [ABSTRACT FROM AUTHOR]

The article proposes a new model for defining and implementing performance tests used in the process of designing and operating IT systems. By defining the objectives, types, topological patterns, and methods of implementation, a coherent description of the test preparation and execution is achieved, facilitating the interpretation of results and enabling straightforward replication of test scenarios. The model was used to develop and implement performance tests in a laboratory environment and in a production system. The proposed division of the testing process into layers correlated with the test preparation steps allows to separate quasi-independent areas, which can be handled by isolated teams of engineers. Such an approach allows to accelerate the process of implementation of performance tests and may affect the optimization of the cost of their implementation. [ABSTRACT FROM AUTHOR]

Stress testing (also known as forced degradation) of pharmaceutical drug substances and products is a critical part of the drug development process, providing insight into the degradation pathways of drug substances and drug products. This information is used to support the development of stability-indicating methods (SIMs) capable of detecting pharmaceutically relevant degradation products that might potentially be observed during manufacturing, long-term storage, distribution, and use. Assessing mass balance of stressed samples is a key aspect of developing SIMs and is a regulatory expectation. However, the approaches to measure, calculate, and interpret mass balance can vary among different pharmaceutical companies. Such disparities also pose difficulties for health authorities when reviewing mass balance assessments, which may result in the potential delay of drug application approvals. The authors have gathered input from 10 pharma companies to map out a practical review of science-based approaches and technical details to assess and interpret mass balance results. Key concepts of mass balance are introduced, various mass balance calculations are demonstrated, and recommendations on how to investigate poor mass balance results are presented using real-world case studies. Herein we provide a single source reference on the topic of mass balance in pharmaceutical forced degradation for small molecule drug substances and drug products in support of regulatory submissions with the goal of facilitating a shared understanding among pharmaceutical scientists and health authorities. [ABSTRACT FROM AUTHOR]

Stress degradation of mangiferin and gallic acid was induced to establish the stability indicating power of the validated high performance thin layer chromatography method. Mangiferin is a C-glycosyl xanthone derivative with many health-endorsing biological activities such as hypoglycaemic, antioxidant, and anti-inflammatory. Similarly, gallic acid a phenolic compound possesses antioxidant, antimicrobial, anti-inflammatory, anticancer, cardioprotective, gastroprotective, and neuroprotective effects. To elucidate the intrinsic stability, both molecules were subjected to a forced degradation process under conditions more severe than accelerated ones, generating degradation products for further study. Forced degradation studies were performed according to stability guidelines by International Council for Harmonisation of Technical Requirements of Pharmaceuticals for Human Use Q1(R2) and Q1B. Accordingly, mangiferin and gallic acid were exposed to oxidation, acid hydrolysis, alkaline hydrolysis, photolysis, as well as hydrolytic and thermal degradation experiments. Forced degradation results show that mangiferin was less susceptible to acidic and hydrolytic conditions and moderately susceptible to dry heat and photostability conditions. Mangiferin was highly susceptible to alkali and oxidative conditions. Gallic acid was less susceptible to photostability conditions and moderately susceptible to alkali, hydrolytic, and dry heat conditions. Gallic acid was highly susceptible to acid and oxidative conditions. [ABSTRACT FROM AUTHOR]

In the current regulatory environment, banks are required to quantify credit risk by means of default probabilities, loss rates conditional on default and expected exposures for a number of purposes: regulatory capital calculation, loan loss provisioning and stress testing. The nature of each credit risk parameter might be different for each application, e.g., forward looking default probabilities are needed for loan loss provisioning while regulatory capital is based on long-term averages. These different requirements for each purpose create a substantial burden especially for small and medium-sized banks. This paper describes a simple framework that allows the consistent calculation of credit risk parameters for all risk applications. It assumes that a bank is using a scorecard based on loan-level data where the data history might only span a couple of years. These data are combined with a macroeconomic model in a suitable way to derive risk parameters compliant with all regulatory requirements. [ABSTRACT FROM AUTHOR]

Conglomerates play an important role in the functioning of capital markets. Therefore, assessing their response to external shocks is a significant risk management challenge not only for conglomerate executives but also for investors and regulators alike. In this context, a conglomerate refers to a group of companies typically operating across different industries and interconnected through both equity and debt relationships. Essentially, a conglomerate functions as a financial network whose nodes are linked by two layers of reciprocal connections. This paper introduces an algorithm to evaluate a conglomerate's response to external shocks. Additionally, it proposes a protocol based on five key metrics that collectively summarize the conglomerate's overall resilience. These metrics offer two major advantages: they facilitate comparisons between the strengths of different conglomerates and help assess the effectiveness of various strategies, such as internal capital reallocations, aimed at enhancing a conglomerate's resilience. The algorithm's usefulness, including its ability to detect cascades or "second-wave" defaults, is demonstrated through two illustrative examples. [ABSTRACT FROM AUTHOR]

This paper reviews the historical evolution of the quantitative models, model usage and model risk management (MRM) in large US banks since the 1980s. It comments on the most significant model-related events through this period. Some of these events were associated with contexts of great stress to the financial system. The paper identifies the main features of modelling in finance and economics that distinguish it from its application in the natural sciences. Then it presents the different types of models used in the large banks' stress testing programmes, the specific characteristics and risks of each type of model and the best practices for the implementation of sound model risk management, and it suggests a proper way to interpret the results of stress testing and capital assessment in the presence of model risks. The paper discusses the future evolution of MRM towards the implementation of a fully fledged risk management framework along the lines of other risk management disciplines, including risk identification, measurement, monitoring, reporting, limiting and capitalisation. It acknowledges the enhancements and opportunities offered by advances in the use of artificial intelligence and machine learning as well as increases in computational power. The paper concludes by noting that the model risk management framework that has been enforced by the Federal Reserve's stress testing and capital planning programmes has substantially strengthened the capital position, profitability and resilience of the large banks in the US. [ABSTRACT FROM AUTHOR]

Background: The crucial aspect to consider during method development and validation, ensuring accurate, precise, and specific estimation of drug substances and drug products, is stability. Various factors, including environmental, instrumental, reagent, and human factors, can pose challenges in achieving suitable method development and validation. Objective: This work aimed to develop and validate a low flow rate, LCMS compatible, simple, and rapid reverse-phase high-performance liquid chromatographic method for estimating efavirenz and its degradation products at different stress conditions. Materials and Methods: The HPLC system employed a Phenomenex Luna 5μ C18 (2) 100A (250 x 4.6 mm) column and a mobile phase of methanol: 20 millimolar ammonium formate solution (90:10) adjusted to pH 4 with formic acid. All analytes were separated within 15 minutes and detected at 247 nm. Method validation was carried out according to ICH guidelines, including linearity, accuracy, precision, ruggedness, robustness, LOD, and LOQ. Results and Discussion: The method was linear in the 10-90 μg/ml range, with a regression coefficient 0.999. Intra- and inter-day precisions, ruggedness, and robustness were within acceptable limits (≤2% RSD) with LOD and LOQ of 0.35 and 1.16 μg/ml, respectively. Degradation study indicates well resolution of the drug and degradants. Conclusion: Purposeful degradation of efavirenz resulted in different degradation products under various stress conditions, and the method demonstrated satisfactory resolution from its degradants.

Noninvasive stress testing is commonly used for detection of coronary ischemia but possesses variable accuracy and may result in excessive health care costs. This study aimed to derive and validate an artificial intelligence-guided quantitative coronary computed tomography angiography (AI-QCT) model for the diagnosis of coronary ischemia that integrates atherosclerosis and vascular morphology measures (AI-QCT ISCHEMIA) and to evaluate its prognostic utility for major adverse cardiovascular events (MACE). A post hoc analysis of the CREDENCE (Computed Tomographic Evaluation of Atherosclerotic Determinants of Myocardial Ischemia) and PACIFIC-1 (Comparison of Coronary Computed Tomography Angiography, Single Photon Emission Computed Tomography [SPECT], Positron Emission Tomography [PET], and Hybrid Imaging for Diagnosis of Ischemic Heart Disease Determined by Fractional Flow Reserve) studies was performed. In both studies, symptomatic patients with suspected stable coronary artery disease had prospectively undergone coronary computed tomography angiography (CTA), myocardial perfusion imaging (MPI), SPECT, or PET, fractional flow reserve by CT (FFR CT), and invasive coronary angiography in conjunction with invasive FFR measurements. The AI-QCT ISCHEMIA model was developed in the derivation cohort of the CREDENCE study, and its diagnostic performance for coronary ischemia (FFR ≤0.80) was evaluated in the CREDENCE validation cohort and PACIFIC-1. Its prognostic value was investigated in PACIFIC-1. In CREDENCE validation (n = 305, age 64.4 ± 9.8 years, 210 [69%] male), the diagnostic performance by area under the receiver-operating characteristics curve (AUC) on per-patient level was 0.80 (95% CI: 0.75-0.85) for AI-QCT ISCHEMIA , 0.69 (95% CI: 0.63-0.74; P < 0.001) for FFR CT , and 0.65 (95% CI: 0.59-0.71; P < 0.001) for MPI. In PACIFIC-1 (n = 208, age 58.1 ± 8.7 years, 132 [63%] male), the AUCs were 0.85 (95% CI: 0.79-0.91) for AI-QCT ISCHEMIA , 0.78 (95% CI: 0.72-0.84; P = 0.037) for FFR CT , 0.89 (95% CI: 0.84-0.93; P = 0.262) for PET, and 0.72 (95% CI: 0.67-0.78; P < 0.001) for SPECT. Adjusted for clinical risk factors and coronary CTA-determined obstructive stenosis, a positive AI-QCT ISCHEMIA test was associated with aHR: 7.6 (95% CI: 1.2-47.0; P = 0.030) for MACE. This newly developed coronary CTA-based ischemia model using coronary atherosclerosis and vascular morphology characteristics accurately diagnoses coronary ischemia by invasive FFR and provides robust prognostic utility for MACE beyond presence of stenosis. [Display omitted] [ABSTRACT FROM AUTHOR]

In recent years, stress tests have emerged as one of the best ways to assess fitness and health of athletes. However, there is some controversy as to their ability to replicate the actual physiological needs generated during competition. The aim of the study was to compare the levels of various physiological variables measured during laboratory stress tests with those observed during competition. Heart rate, blood lactate, blood pressure, rate of perceived effort and stress level were analysed in ten amateur male basketball players, during three maximal laboratory tests (TREADMILL, CYCLE and Wingate test), and in five official competition games. The level of significance for the study was set at p=.05. Statistically significant differences between the physiological needs of competitive matches and those of stress tests were reported (p<.05). Furthermore, the time during which a higher HR was recorded during the competition compared to the HR obtained during the stress tests was calculated. This time was 12.36 ± 9.21% of the Live Time (LT) on TREADMILL, 35.04 ± 11.78% of the LT on CYCLE and 63.75 ± 11.57% of the LT on Wingate. The results suggest that laboratory stress tests do not reproduce the physiological requirements imposed on amateur basketball players during competition. [ABSTRACT FROM AUTHOR]

Purpose: Exercise imaging using current modalities can be challenging. This was patient focused study to establish the feasibility and reproducibility of exercise-cardiovascular magnetic resonance imaging (EX-CMR) acquired during continuous in-scanner exercise in asymptomatic patients with primary mitral regurgitation (MR). Methods: This was a prospective, feasibility study. Biventricular volumes/function, aortic flow volume, MR volume (MR-Rvol) and regurgitant fraction (MR-RF) were assessed at rest and during low- (Low-EX) and moderate-intensity exercise (Mod-EX) in asymptomatic patients with primary MR. Results: Twenty-five patients completed EX-CMR without complications. Whilst there were no significant changes in the left ventricular (LV) volumes, there was a significant increase in the LVEF (rest 63 ± 5% vs. Mod-EX 68 ± 6%;p = 0.01). There was a significant reduction in the right ventricular (RV) end-systolic volume (rest 68 ml(60–75) vs. Mod-EX 46 ml(39–59);p < 0.001) and a significant increase in the RV ejection fraction (rest 55 ± 5% vs. Mod-EX 65 ± 8%;p < 0.001). Whilst overall, there were no significant group changes in the MR-Rvol and MR-RF, individual responses were variable, with MR-Rvol increasing by ≥ 15 ml in 4(16%) patients and decreasing by ≥ 15 ml in 9(36%) of patients. The intra- and inter-observer reproducibility of LV volumes and aortic flow measurements were excellent, including at Mod-EX. Conclusion: EX-CMR is feasible and reproducible in patients with primary MR. During exercise, there is an increase in the LV and RV ejection fraction, reduction in the RV end-systolic volume and a variable response of MR-Rvol and MR-RF. Understanding the individual variability in MR-Rvol and MR-RF during physiological exercise may be clinically important. [ABSTRACT FROM AUTHOR]

This study presents a stress testing operation conducted using a wireline formation tester in a newly discovered gas hydrate prospect located offshore in Japan. The campaign, which spanned from December 2021 to January 2022, involved drilling a well using logging-while-drilling technology. Subsequently, wireline formation testing and stress testing were successfully conducted at three different depths within a gas hydrate-concentrated zone. The testing was accomplished in a single riserless descent, with the primary goal of obtaining crucial data such as mobility, formation pressure, and fracture gradient for one of the prospects. This operation marked the first stress testing job performed with dual packers in an open water and deepwater environment specifically for gas hydrate reservoirs. The study also provides a comprehensive interpretation of the data gathered during the operation. Moreover, it evaluates various properties such as formation mobility, formation pressure, initial breakdown pressure, closure pressure, fracture propagation pressure, and instantaneous shut-in pressure. [ABSTRACT FROM AUTHOR]

This review article focuses on the role of adenosine in coronary artery disease (CAD) diagnosis and treatment. Adenosine, an endogenous purine nucleoside, plays crucial roles in cardiovascular physiology and pathology. Its release and effects, mediated by specific receptors, influence vasomotor function, blood pressure regulation, heart rate, and platelet activity. Adenosine therapeutic effects include treatment of the no-reflow phenomenon and paroxysmal supraventricular tachycardia. The production of adenosine involves complex cellular pathways, with extracellular and intracellular synthesis mechanisms. Adenosine's rapid metabolism underscores its short half-life and physiological turnover. Furthermore, adenosine's involvement in side effects of antiplatelet therapy, particularly ticagrelor and cangrelor, highlights its clinical significance. Moreover, adenosine serves as a valuable tool in CAD diagnosis, aiding stress testing modalities and guiding intracoronary physiological assessments. Its use in assessing epicardial stenosis and microvascular dysfunction is pivotal for treatment decisions. Overall, understanding adenosine's mechanisms and clinical implications is essential for optimizing CAD management strategies, encompassing both therapeutic interventions and diagnostic approaches. [ABSTRACT FROM AUTHOR]

The research investigates the stability of 7-hydroxy coumarin i.e. umbelliferone, a compound with diverse applications, through forced degradation studies under various conditions. These investigations aim to comprehend its susceptibility to degradation and provide insights crucial for its safe handling and formulation. Umbelliferone displays differing degrees of vulnerability to distinct stressors: it exhibits higher susceptibility to alkali-induced and photolytic degradation, signaling the necessity for cautious management under these conditions. Conversely, it demonstrates moderate susceptibility to acid and water-induced degradation. The findings underscore the importance of handling umbelliferone carefully, particularly in environments, where it is more prone to degradation. Furthermore, the study suggests future explorations to elucidate the structures of degradation products, potentially enhancing our understanding of its stability profile. This comprehensive analysis not only elucidates umbelliferone's stability nuances but also accentuates the significance of forced degradation studies in evaluating the inherent stability of pharmaceutical compounds, offering crucial insights for formulation and storage practices. [ABSTRACT FROM AUTHOR]

The interest rate hikes intended to combat inflation have not only significantly increased mortgage payments, but also significantly depressed house prices. The probability of default for mortgages is typically estimated through the debt servicing ability of the obligor. The alternative estimation based on the default option, although well studied in literature, is typically not used by practitioners. This option is normally 'deep out of money' and moves in the money if the loan to value (LTV) increases significantly, even creating negative equity. This is typically a remote probability due to the down payment requirements, but not as much under the current environment, where the house price depreciation has significantly increased LTVs, especially for newer mortgages underwritten when house prices were at their peak. This paper discusses the potential risk management oversights in this environment, illustrating that the increasing default risk is not adequately captured in probability of default (PD) models based on debt servicing ability alone. This is also true for the loss given default (LGD) risk if the contemporaneous LTV effects are not captured. Numerical examples are provided to demonstrate the material increase in PD, LGD and the combined expected loss risk with increasing LTV. It also discusses an alternative default option PD model, its calibration and its usage for stress testing along with LGD modelling, which together capture the contemporaneous LTV effects. [ABSTRACT FROM AUTHOR]

BACKGROUND: Ischemia with nonobstructive coronary arteries (INOCA) is common clinically, particularly among women, but its prevalence among patients with at least moderate ischemia and the relationship between ischemia severity and non-obstructive atherosclerosis severity are unknown. OBJECTIVES: The authors investigated predictors of INOCA in enrolled, nonrandomized participants in ISCHEMIA (International Study of Comparative Health Effectiveness with Medical and Invasive Approaches), sex differences, and the relationship between ischemia and atherosclerosis in patients with INOCA. METHODS: Core laboratories independently reviewed screening noninvasive stress test results (nuclear imaging, echocardiography, magnetic resonance imaging or nonimaging exercise tolerance testing), and coronary computed tomography angiography (CCTA), blinded to results of the screening test. INOCA was defined as all stenoses

This paper is the second part of a series studying the design of the mathematical models for the execution time of user tasks carried out on virtual computing nodes. It analyzes the quality of the proposed models that describe the processing time of the information stored in the databases (DBs). A prototype of the anonymization system of passengers' personal data is used as a testbed for stress testing. Stochastic models are constructed describing two types of user tasks: the procedure for the anonymization of personal data and calculation of the sample's statistical characteristics. This paper contains a detailed description of planning and performing stress testing for both models. The obtained mathematical models developed from real data demonstrate a fairly high quality. [ABSTRACT FROM AUTHOR]

The optimal surveillance strategy after percutaneous coronary intervention (PCI) for high-risk patients with multivessel or left main coronary artery disease (CAD) remains uncertain. This study aims to determine the prognostic role of routine functional testing in patients with multivessel or left main CAD who underwent PCI. The POST-PCI (Pragmatic Trial Comparing Symptom-Oriented Versus Routine Stress Testing in High-Risk Patients Undergoing Percutaneous Coronary Intervention) trial randomized high-risk PCI patients to routine functional testing at 1 year or standard care alone during follow-up. This analysis focused on participants with multivessel or left main CAD. The primary outcome was a composite of death from any cause, myocardial infarction, or hospitalization for unstable angina at 2 years. Among 1,706 initially randomized patients, 1,192 patients with multivessel (n = 833) or left main (n = 359) were identified, with 589 in the functional testing group and 603 in the standard care group. Two-year incidences of primary outcome were similar between the functional testing group and the standard care group (6.2% vs 5.7%, respectively; HR: 1.09; 95% CI: 0.68-1.74; P = 0.73). This trend persisted in both groups of multivessel (6.2% vs 5.7%; HR: 1.09; 95% CI: 0.62-1.89; P = 0.78) and left main disease (6.2% vs 5.7%; HR: 1.09; 95% CI: 0.46-2.56; P = 0.85) (P for interaction = 0.90). Routine surveillance functional testing was associated with increased rates of invasive angiography and repeat revascularization beyond 1 year. In high-risk patients with multivessel or left main CAD who underwent PCI, there was no incremental clinical benefit from routine surveillance functional-testing compared with standard care alone during follow-up. (Pragmatic Trial Comparing Symptom-Oriented Versus Routine Stress Testing in High-Risk Patients Undergoing Percutaneous Coronary Intervention [POST-PCI]; NCT03217877) [Display omitted] [ABSTRACT FROM AUTHOR]

The objective of this study is to explore the mechanism of action at the contact interface between gears and particles in spindle barrel finishing, using the Discrete Element Method (DEM) for simulation. The motion of the particles in the vicinity of the gear and the contact particles on the tooth surface is first described. Then the effects of gear embedment depth, gear and roller speed on relative particle motion velocity and tooth contact force are investigated. Finally, the simulation results are verified by experiments. The results show that the action of spindle barrel finishing on the gear tooth face is cyclical in nature. Contact force on the upper and lower tooth surfaces of the gear is not uniform, and the contact force on the upper tooth surface is 1.5 to 1.8 times that on the lower tooth surface. Increasing the gear embedment depth mainly affects the contact force between the particles and the tooth surface. A 75% increase in embedment depth leads to a 76% rise in tooth surface contact force. Similarly, increasing the gear and drum speed mainly affects the relative movement speed between particles and the tooth surface. A 150% increase in gear and drum speed results in a 148% increase in the relative movement speed of particles in contact with the tooth surface. Increasing the embedment depth of the gear can reduce the processing variability of the gear tooth surface along the axial direction. After increasing the embedment depth from 80 mm to 140 mm, the roughness of the upper and lower tooth surfaces along the axial direction decreases from 17% and 36% to 62% and 55%, respectively. However, the processing variability along the tooth profile direction does not change significantly by changing the speed and embedment depth.

The article proposes a new model for defining and implementing performance tests used in the process of designing and operating IT systems. By defining the objectives, types, topological patterns, and methods of implementation, a coherent description of the test preparation and execution is achieved, facilitating the interpretation of results and enabling straightforward replication of test scenarios. The model was used to develop and implement performance tests in a laboratory environment and in a production system. The proposed division of the testing process into layers correlated with the test preparation steps allows to separate quasi-independent areas, which can be handled by isolated teams of engineers. Such an approach allows to accelerate the process of implementation of performance tests and may affect the optimization of the cost of their implementation.

Abstract Background Splenic switch-off (SSO) is a marker of adequate adenosine-induced vasodilatation on cardiac magnetic resonance perfusion imaging. We evaluate the feasibility of quantitative assessment of SSO in myocardial positron emission tomography (PET) perfusion imaging using [15O]H2O. Methods Thirty patients underwent [15O]H2O PET perfusion with adenosine stress. Time-activity curves, as averaged standardized uptake values (SUV avg ), were extracted from dynamic PET for spleen and liver. Maximum SUV avg , stress and rest spleen-to-liver ratio (SLR), and the splenic activity concentration ratio (SAR) were computed. Optimal cut-off values for SSO assessment were estimated from receiver operating characteristics (ROC) curve for maximum SUV avg and SLR. Also, differences between coronary artery disease, myocardial ischemia, beta-blockers, and diabetes were assessed. Data are presented as median [interquartile range]. Results In concordance with the SSO phenomenon, both the spleen maximum SUV avg and SLR were lower in adenosine stress when compared to rest perfusion (8.1 [6.5, 9.2] versus 16.4 [13.4, 19.0], p

Purpose: is to develop the model for stress testing of the impact of external constraints of Russian regions in the context of foreign economic constraints 2022–2023.Methods: the research is based on the theory of economic dynamics, regional economy and spatial development, the concept of the BANI world; the methodological basis of the study is a scenario approach to the formation of the stress testing model and the algorithm for determining the expected impact based on the machine learning method – the artificial neural network.Results: the study of scientific publications on the research topic, analysis of shock events, post-shock consequences (2006–2022) made it possible to substantiate feasibility of testing and differentiating the response of Russian regions to external constraints, applying the criteria of “shock-resistant” development, classifying economic space and identifying the territory with “shock-resistant” and “non-shockresistant”reactions. The model of regions stress testing has been developed, industrial and sectoral (67.6% importance) and spatial (32.4%) stabilization factors have been identified, areas of vulnerability to the restrictions of 2022-2023 and industrial regions with the potential for “non-shock-resistant” type of reaction have been identified.Conclusions and Relevance: the reaction of regions to external economic shocks (the duration of the decline period and the intensity of recovery growth) is determined by the totality of the production and spatial characteristics of the regions. The results of the study are important for the development of the theory of regional economy; they can be used byfederal and regional executive authorities of the Russian Federation.

This paper contains the first part of a study on the design of mathematical models for the execution time of user tasks on virtual calculating nodes. It is assumed that the execution time is a random value with the mean and variance depending on the node resources, task parameters, and the current characteristics of the node state. We discover the key features of the mean and variance functions and specify some of their particular cases. Both the mean and variance functions depend on the unknown parameters, and the design of the stochastic model for time complexity leads to parameter identification in the form of the generalized maximum likelihood estimates under heterogeneous statistical information. This paper also contains recommendations concerning the gathering and subsequent use of this information: the node testbed preparation, stress test planning, and processing of the data obtained. Specific illustrating examples of the proposed mathematical model will be presented in the subsequent parts of the study. [ABSTRACT FROM AUTHOR]

We develop the first climate risk Stress Test for the Peruvian financial system following a topdown approach. Focusing on the microeconomic channel, we evaluate how heavy rainfall and droughts, under a scenario of pure physical risk, will marginally affect the probability of default (PD) of borrowers by 2050. Using information from the Credit Registry, the National Oceanic and Atmospheric Administration (NOAA), and CMIP6 precipitation projections (37 modeling groups), we calibrate the marginal impacts differentiating by economic sector and geographical location. We find that, on average, by December 2050, the probability of default of the Peruvian financial system would increase by 4.9% with respect to December 2020. By geographic area, borrowers located on the northern coast (Piura, Lambayeque) and the southern highlands (Ayacucho, Cusco) would be negatively affected by heavy rainfall, while the rainforest (Madre de Dios, Ucayali) would be negatively affected by droughts. Moreover, the economic sectors affected by heavy rainfall or droughts would be agriculture, commerce, and transportation & communications. [ABSTRACT FROM AUTHOR]

Forced degradation (i.e., stress testing) of small molecule drug substances and products is a critical part of the drug development process, providing insight into the intrinsic stability of a drug that is foundational to the development and validation of stability-indicating analytical methods. There is a lack of clarity in the scientific literature and regulatory guidance as to what constitutes an "appropriate" endpoint to a set of stress experiments. That is, there is no clear agreement regarding how to determine if a sample has been sufficiently stressed. Notably, it is unclear what represents a suitable justification for declaring a drug substance (DS) or drug product (DP) "stable" to a specific forced degradation condition. To address these concerns and to ensure all pharmaceutically-relevant, potential degradation pathways have been suitably evaluated, we introduce a two-endpoint classification designation supported by experimental data. These two endpoints are 1) a % total degradation target outcome (e.g., for "reactive" drugs) or, 2) a specified amount of stress, even in the absence of any degradation (e.g., for "stable" drugs). These recommended endpoints are based on a review of the scientific literature, regulatory guidance, and a forced degradation data set from ten global pharmaceutical companies. The experimental data set, derived from the Campbell et al. (2022) benchmarking study, 1 provides justification for the recommendations. Herein we provide a single source reference for small molecule DS and DP forced degradation stress conditions and endpoint best practices to support regulatory submissions (e.g., marketing applications). Application of these forced degradation conditions and endpoints, as part of a well-designed, comprehensive and a sufficiently rigorous study plan that includes both the DS and DP, provides comprehensive coverage of pharmaceutically-relevant degradation and avoids unreasonably extreme stress conditions and drastic endpoint recommendations sometimes found in the literature. [ABSTRACT FROM AUTHOR]