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Purpose – Stirred by scant regard for market phases in portfolio performance assessments, the current paper investigates the active versus passive investment strategies under the bull and bear market conditions in emerging markets focusing on South Africa as a case study. Design/methodology/approach – Methodologically, the measures of Jensen's alpha and Treynor index are applied to the monthly returns of 20 funds from January 2010 to June 2022. Findings – The results are enlightening; though they contradict developed market evidence, they are consistent with emerging market trends. The findings show that actively managed funds outperform the market benchmark and passive investing style under bear and normal market conditions. Passive investment strategy outperforms both market benchmark and actively investing style under bull market conditions. Practical implications – In the face of improved market efficiency, increased liquidity and recent technological impact, the findings of this study have practical application. The study outcomes should inform and update global investors, especially asset managers interested in emerging markets; however, the limitations of the study should also be considered. Originality/value – While limited studies consider market conditions when comparing and contrasting the performance of passive versus active investing, such consideration is lacking in emerging markets. The current study corrects this literature imbalance.

The competitive nature of the pharmaceutical industry necessitates that its multifaceted supply-chain be cost-efficient and profitable. This paper aims to ascertain the critical supply-chain financial indicators influencing pharmaceutical-supply-chain (PSC) performance, revealing its unique features and assessing these indicators' effect on profitability. This paper measures the PSC performance of 55 public-limited Indian pharmaceutical firms, including multinational enterprises, integrating supply-chain financial variables and SCOR KPIs through a ten-year timeline. The critical supply-chain-performance indicators (SCPIs) are identified from the measured set through factor analysis. A panel data random effect model is developed, linking these critical SCPIs and profitability to understand their significant influence on profitability. This paper has evidenced the existence of three critical SCPIs, revealing working capital efficiency, material flow efficiency and investment efficiency. It has also proved the significant influence of these SCPIs on firms' profitability and has brought out the importance of material flow efficiency in terms of inventory and distribution efficiency as a leading contributing factor for profitability. This paper contributes to finding key PSC performance features and their vital role in pharmaceutical firms' profitability. Supply-chain managers can enhance PSC's specific performance areas to be cost-efficient and can increase the firm's profitability. [ABSTRACT FROM AUTHOR]

Objective: The objective of this expert consensus process was to define performance measures that can be used to document remission or long-term progress following lifestyle medicine (LM) treatment. Methods: Expert panel members with experience in intensive, therapeutic lifestyle change (ITLC) developed a list of performance measures for key disease states, using an established process for developing consensus statements adapted for the topic. Proposed performance measures were assessed for consensus using a modified Delphi process. Results: After a series of meetings and an iterative Delphi process of voting and revision, a final set of 32 performance measures achieved consensus. These were grouped in 10 domains of diseases, conditions, or risk factors, including (1) Cardiac function, (2) Cardiac risk factors, (3) Cardiac medications and procedures, (4) Patient-centered cardiac health, (5) Hypertension, (6) Type 2 diabetes and prediabetes, (7) Metabolic syndrome, (8) Inflammatory conditions, (9) Inflammatory condition patient-centered measures, and (10) Chronic kidney disease. Conclusion: These measures compose a set of performance standards that can be used to evaluate the effectiveness of LM treatment for these conditions. [ABSTRACT FROM AUTHOR]

One of the critical issues in healthcare management is the operating room (OR) scheduling problem. Solutions to this problem consider surgery durations and allocate elective surgeries to OR sessions in order to create surgical lists of high quality. Determining the quality of a surgical list is a key undertaking within OR scheduling and is the focus of this research. Currently, probability- and/or expectation-based measures of surgical lists are used instead of statistical distributions of surgery lists to measure quality. The use of multiple measures, e.g., a combination of expectation and probability to assess a surgical list, complicates OR scheduling, so we introduce a new single measure – the OR scheduling metric – for evaluating surgical lists before their realisations, i.e., for use within OR scheduling. We apply the OR scheduling metric to an actual elective dataset and use simulation to demonstrate its use, including customised scheduling rules. We recommend the adoption of a benchmarked OR scheduling metric by the elective surgical services in hospitals with expected practical benefits in the long run, i.e., simpler OR scheduling and more desirable room utilisation, to be similar to that observed in our simulations. [ABSTRACT FROM AUTHOR]

Purpose: Machine learning models are used to develop and improve various disease prediction systems. Ensemble learning is a machine learning technique that combines many classifiers to increase performance by making more accurate predictions than a single classifier. Although several researchers have employed ensemble techniques for disease prediction, a comprehensive comparative study of these techniques still needs to be provided. Methods: Using 16 disease datasets from Kaggle and the UCI Machine Learning Repository, this study compares the performance of 15 variants of ensemble techniques for disease prediction. The comparison was performed using six performance measures: accuracy, precision, recall, F1 score, AUC (Area Under the receiver operating characteristics Curve) and AUPRC (Area Under the Precision-Recall Curve). Results: Stacking variant of Multi-level stacking showed superior disease prediction performance compared with other bagging and boosting variants, followed by another stacking variant (Classical stacking). Overall, stacking outperformed bagging and boosting for disease prediction. Logit Boost showed the worst performance. Conclusion: The findings of this study can help researchers select an appropriate ensemble approach for future studies focusing on accurate disease prediction. [ABSTRACT FROM AUTHOR]

Abstract The Pareto distribution is of paramount importance in actuarial science, wealth distribution, finance, etc. This paper introduces a control chart inspired by Shewhart's methodology, designed for monitoring shifts in the Pareto distribution through a repetitive sampling approach. The chart employs a modified statistic that combines shape and threshold parameters as its plotting statistic. Coefficients for the Shewhart-type Pareto chart are computed for two-phase limits. The performance of the suggested chart is assessed in terms of run length characteristics, assuming a shift in the process mean. Additionally, we conduct an efficiency comparison with existing control charts. The findings suggest that, on average, the proposed Pareto chart demonstrates greater efficiency in promptly detecting changes compared to alternative methods. To illustrate the practical application of our approach, we present an example using revenue data.

As medicine is moving toward performance and outcome-based payment and is transitioning away from productivity-based systems, value is now being appraised in healthcare through "performance measures." Over the past few decades, assessment of clinical performance in health care has been essential in ensuring safe and cost-effective patient care. The Centers for Medicare & Medicaid Services is further driving this change with measurable, outcomes-based national payer incentive payment systems. With the continually evolving requirements in health care reform focused on value-based care, there is a growing concern that clinicians, particularly dermatologists, may not understand the scientific rationale of health care quality measurement. As such, in order to help dermatologists understand the health care measurement science landscape to empower them to engage in the performance measure development and implementation process, the first article in this 2-part continuing medical education series reviews the value equation, historic and evolving policy issues, and the American Academy of Dermatology's approach to performance measurement development to provide the required foundational knowledge for performance measure developers. [ABSTRACT FROM AUTHOR]

The Pareto distribution is of paramount importance in actuarial science, wealth distribution, finance, etc. This paper introduces a control chart inspired by Shewhart's methodology, designed for monitoring shifts in the Pareto distribution through a repetitive sampling approach. The chart employs a modified statistic that combines shape and threshold parameters as its plotting statistic. Coefficients for the Shewhart-type Pareto chart are computed for two-phase limits. The performance of the suggested chart is assessed in terms of run length characteristics, assuming a shift in the process mean. Additionally, we conduct an efficiency comparison with existing control charts. The findings suggest that, on average, the proposed Pareto chart demonstrates greater efficiency in promptly detecting changes compared to alternative methods. To illustrate the practical application of our approach, we present an example using revenue data. [ABSTRACT FROM AUTHOR]

Background: There is great heterogeneity in the quality of care among hospitals in China, but studies on the performance measures and prognosis of patients with heart failure (HF) are still deficient. Hypothesis: Performance measures have been used as a guideline to clinicans, however, the association between them and outcomes among HF patients in China remains unclear. Methods: We analyzed 4497 patients with HF from the Heart Failure Registry of Patient Outcomes study. Performance measures were determined according to the guidelines, and the patients were divided into four groups based on a composite performance score. Multiple imputation and Cox proportional‐hazard regression models were used to assess the association between the performance measures and clinical outcomes. Results: Overall, only 12.5% of patients met the top 25% of the performance measures, whereas 33.5% of patients met the bottom 25% of the measures. A total of 992 (22.2%) patients died within 1 year, involving a larger proportion of patients who had met only the bottom 25% of the performance measures than had met the top 25% (27.0% vs. 16.3%, respectively). The patients who met the top 25% of the measures had a lower 1‐year mortality rate (adjusted hazard ratio: 0.78, 95% confidence interval: 0.61–0.98). Conclusions: The association between performance measures and mortality appeared to follow a dose–response pattern with a larger degree of compliance with performance measures being associated with a lower mortality rate in patients with HF. Accordingly, the quality of care for patients with HF in China needs to be further improved. [ABSTRACT FROM AUTHOR]

Data Envelopment Analysis (DEA) stands out as the most commonly employed approach for assessing the overall performance of a group of similar Decision-Making Units (DMUs) that utilize similar resources to produce comparable outputs. Nonetheless, the observed characteristics of symmetry or asymmetry in various types of data in real-world applications can often be imprecise, unclear, insufficient, or contradictory. Neglecting these conditions can potentially result in erroneous decision-making. Certain models take a more restrictive approach by assuming that inputs and outputs possess the same level of determinism. Regrettably, such constraints don't hold true for the majority of real-world scenarios. In actual situations, however, the observed input and output data may sometimes be neutrosophic numbers. So, the primary purpose of this study is to construct a Neutrosophic Input Oriented DEA (NIODEA) Model that incorporates both neutrosophic and deterministic output and/or input variables, handled in accordance with the scoring function. The model we have developed has broad applicability across diverse organizations, aiding decision-makers in making informed choices and optimizing resource allocation, a particularly valuable asset in today's intensely competitive business environment. To underscore the practical utility of the model, we provide an illustrative example that demonstrates its effectiveness and relevance for decision-makers.

People usually create a portfolio in order to diversify the risk coming from individual investments. To get a high yield with a good level of diversification, investors usually seek professional advice from portfolio managers. However, the true performance of an optimized portfolio usually depends on the correctness of the estimates of the distribution of future returns, which is often a matter of luck rather than skill. Thus, the optimization models may not be better than randomly selected portfolios. Our aim is to find how the so-called strategy portfolios, i.e., portfolios obtained by some decision optimized for a long-run horizon, perform compared to a benchmark, namely, a random investment, under specific market conditions. For this purpose, we evaluate several portfolio strategies over two periods of crisis: the subprime mortgage crisis and the Covid-19 pandemic, as well as run a moving window analysis over a longer horizon. In each case, the results are compared with the performance of random-weight portfolios. We find that if the strategy is minimization, the portfolios perform well; however, for the maximization of the objectives, the results are rather mixed. [ABSTRACT FROM AUTHOR]

In reverse osmosis applications, feed spacers are used in spiral wound membranes to separate the membrane surfaces and enhance mass transfer while incurring an acceptable pressure drop. In this study, an attempt has been made to understand the effect of spacer characteristics, such as arrangement and size, on mass transfer and pressure drop. Power-law equations were successfully developed to describe different spacer performance measures as a function of Reynolds number (Re), where both the multiplier of the Re term and the Re exponent vary for each spacer arrangement. Although at the macro level, it was not possible to adequately correlate the equation parameters with the spacers' geometrical parameters (such as porosity), examining the post-processed CFD results at the micro level led to explanations for the observed concentration profiles, trends in spacer performance and changes in the equation parameters. A key observation was the importance of lateral flow recirculation, which was termed side-washing. Overall, based on the Spacer Configuration Efficacy performance measure and by assessing the trade-off between Sherwood number and pressure drop, the Woven configuration shows the best performance among the spacer arrangements and range of flowrates studied. [Display omitted] • A comprehensive database of performance measures for SWM feed spacers was developed. • Correlations between flow, pressure drop, and mass transfer parameters are reported. • No correlation was found between Sh and geometrical parameters, such as porosity. • Longitudinal and lateral flow recirculation significantly affects mass transfer. • Micro-scale flow observations can explain spacer performance trends. [ABSTRACT FROM AUTHOR]

Data Envelopment Analysis (DEA) stands out as the most commonly employed approach for assessing the overall performance of a group of similar Decision-Making Units (DMUs) that utilize similar resources to produce comparable outputs. Nonetheless, the observed characteristics of symmetry or asymmetry in various types of data in real-world applications can often be imprecise, unclear, insufficient, or contradictory. Neglecting these conditions can potentially result in erroneous decision-making. Certain models take a more restrictive approach by assuming that inputs and outputs possess the same level of determinism. Regrettably, such constraints don't hold true for the majority of real-world scenarios. In actual situations, however, the observed input and output data may sometimes be neutrosophic numbers. So, the primary purpose of this study is to construct a Neutrosophic Input Oriented DEA (NIODEA) Model that incorporates both neutrosophic and deterministic output and/or input variables, handled in accordance with the scoring function. The model we have developed has broad applicability across diverse organizations, aiding decision-makers in making informed choices and optimizing resource allocation, a particularly valuable asset in today's intensely competitive business environment. To underscore the practical utility of the model, we provide an illustrative example that demonstrates its effectiveness and relevance for decision-makers. [ABSTRACT FROM AUTHOR]

The analysis of an M/M/1/N feedback working vacation queueing system with reneging is presented in this paper. Customers may become impatient and even disappointed when they see a long line. In the literature on queueing, customer dissatisfaction caused on by unsatisfactory service is referred as feedback. In the case of feedback, customers retry services after receiving unsatisfactory or incomplete. First, we create the equations for the steady-state probabilities using the Markov process method. The steady-state probabilities are then solved by the matrix method. We then provide some system performance measures. We create a cost model using performance analysis. Finally, we give some numerical examples to show how the various model parameters affect the system’s behaviour. [ABSTRACT FROM AUTHOR]

Abstract Aims This study aims to provide representative information on heart failure (HF) patients in China, especially older adults aged ≥75 years. We aim to clarify the age‐related discrepancies in performance measures and the modifying effect of age on the impact of HF patients' characteristics on clinical outcomes. Methods and results All HF patients admitted into five tertiary and four secondary hospitals of the Capital Medical University were divided into two groups according to age: 1419 (53.3%) were

This paper further modifies soil conservation service curve number (SCS-CN) based on the concept of adjusting the rainfall in accordance with rain duration and considering the initial abstraction (Ia) as a fraction of rainfall for runoff estimation. The former yields Model M3 and its explicit form with constant parameter λ = 0.2 is designated as Model M4. Model M5 couples both the concepts and thus all these models are the advanced versions. The applicability of all the five models is tested using a large number of rainfall-runoff events (25,502) derived from 53 U.S. Department of Agriculture-Agricultural Research Service watersheds. Models M3–M5 performed better than Models M1 and M2. Model performance is evaluated by employing six statistical measures, namely, root mean square error, mean absolute error, normalized root mean square error, Nash–Sutcliffe coefficient (%), percent bias, RSR, n(t), and several grading criteria. Results show Model M5 to have performed the best of all in both calibration and validation largely due to its incorporating the impact of rain duration and allowing Ia to vary with rainfall, which is close to reality and not accounted for in any other models considered in this study. HIGHLIGHTS An enhanced mathematical SCS-CN model for estimating direct surface runoff by storm duration and rainfall-based initial abstraction is suggested in this study.; Performance of the model is also evaluated by different indicators and compared with existing models.; The proposed model shows robust performance in surface runoff prediction.;

Aims: This study aims to provide representative information on heart failure (HF) patients in China, especially older adults aged ≥75 years. We aim to clarify the age‐related discrepancies in performance measures and the modifying effect of age on the impact of HF patients' characteristics on clinical outcomes. Methods and results: All HF patients admitted into five tertiary and four secondary hospitals of the Capital Medical University were divided into two groups according to age: 1419 (53.3%) were <75 years, and 1244 (46.7%) were ≥75 years. Older HF patients were more likely to be women, with higher left ventricular ejection fraction, with co‐morbidities including chronic obstructive pulmonary disease/asthma, anaemia, chronic kidney disease, stroke/transient ischemic attack (TIA), atrial fibrillation/atrial flutter, hypertension, and coronary artery disease, while obesity, diabetes mellitus, hypercholesterolaemia and valvular heart disease were more prevalent among younger HF patients. Left ventricular ejection fraction assessment was performed in a similar proportion of patients in the younger and older groups (81.7% vs. 80.5%, P = 0.426), while B‐type natriuretic peptide/N terminal pro brain natriuretic peptide was tested in a lower proportion in the younger group (84.8% vs. 89%, P = 0.001). At discharge, HF with reduced ejection fraction patients were less likely to receive beta‐blockers, angiotensin‐converting enzyme inhibitors/angiotensin II receptor blockers, or combined beta‐blockers and angiotensin‐converting enzyme inhibitors/angiotensin II receptor blockers therapy in the older group (49.74% vs. 63.2%, P = 0.002; 52.9% vs. 64.7%, P = 0.006; and 28.57% vs. 45.5%, P < 0.001, respectively) but were equally likely to receive mineralocorticoid receptor antagonists in the two age groups (80.8% vs. 84.1%, P = 0.322). Older patients with HF had higher risk of in‐hospital and 1 year mortality (2.7% vs. 1.3%, P = 0.011; 21.7% vs. 12.5%; P < 0.001, respectively). Higher body mass index was associated with better outcomes in both age groups. New York Heart Association functional class IV and estimated glomerular filtration rate < 60 mL/min/1.73 m2 were independent predictors of 1 year mortality. The associations between patients' characteristics and risk of mortality were not modified by age. Conclusions: HF patients aged ≥75 years had distinct clinical profiles, received worse in‐hospital therapies and experienced higher in‐hospital and 1 year mortality. [ABSTRACT FROM AUTHOR]

Recent research shows that matching between contemporaneous revenues and expenses has declined over the past 40 years. We argue that this decline in matching reduces the contracting usefulness of earnings and affects managerial effort allocation and performance measure choice. Based on a theoretical model, we predict that firms with poor matching benefit from contracting on sales revenue instead of earnings. Using hand-collected CEO performance measure data from S&P 500 firms, we document a significant increase in the use of sales revenue coupled with a significant decline in the use of bottom line income as a performance measure over time. We confirm the model prediction that firms are more likely to explicitly employ sales revenue as a performance measure when matching is poor. We further show that this negative association between matching and the use of sales revenue performance persists after controlling for the use of other earnings measures and equity compensation. This study contributes to the literature by examining the effect of revenue-expense matching on compensation design and documenting the increasing trend of revenue-based compensation in recent years. [ABSTRACT FROM AUTHOR]

In the last two decades, regardless of epidemiological, and clinical studies, the incidence of breast cancer (BC) is still increasing. However, so far, a lot of research has been done in this field to diagnose BC, and some of them have been discussed in the literature section. But still, happening major issues while dealing with fault feature matrix, generated from traditional feature extraction methods. As a result, the complexity of fault classification has raised, which will negatively impact fault identification's accuracy and effectiveness. Thus, in this research, a novel hybridized machine learning-fuzzy and dimension reduction (MLF-DR) model has been proposed to improve the decision capabilities and efficiency of an ML model. A feature-based class-togetherness fuzzification method has been used for every feature. The novelty of our research work is to find all possibilities between cancerous and non-cancerous cells by implementing a fuzzy inference system (FIS) in the data analysis phase, and DR techniques at preprocessing phase to select the best optimizing features. This research tries to reduce the incidence of BC and prevent needless deaths, thus will probably follow necessary action to perform i.e. (i) FIS to interpret input values; (ii) principal component analysis (PCA), and recursive feature elimination (RFE) to select best features, and (ii) logistic regression (LR) and random forest (RF) models to predict BC with these features. Furthermore, all the experiments have been done on Wisconsin Breast Cancer Dataset (WBCD), freely available on the Kaggle repository using Python programming on Jupyter Notebook version 6.4.3. The key findings of this research are that the LR-PCA (8 components) model can reliably and successfully obtain the defect diagnosis results with 99.1% accuracy, as compared to individual LR and RF models. [ABSTRACT FROM AUTHOR]

The problems of online pricing with offline data, among other similar online decision making with offline data problems, aim at designing and evaluating online pricing policies in presence of a certain amount of existing offline data. To evaluate pricing policies when offline data are available, the decision maker can either position herself at the time point when the offline data are already observed and viewed as deterministic, or at the time point when the offline data are not yet generated and viewed as stochastic. We write a framework to discuss how and why these two different positions are relevant to online policy evaluations, from a worst-case perspective and from a Bayesian perspective. We then use a simple online pricing setting with offline data to illustrate the constructions of optimal policies for these two approaches and discuss their differences, especially whether we can decompose the searching for the optimal policy into independent subproblems and optimize separately, and whether there exists a deterministic optimal policy. [ABSTRACT FROM AUTHOR]

As one of the principal lifeline systems, transportation networks are crucial for evacuation during extreme weather events like hurricanes, and critical network links must remain intact. The conventional evaluation measures prioritize to achieve the maximum system efficiencies, and therefore they estimate the functional criticality of a road network using measures such as travel time increase or throughput reduction caused by a link disruption. This study asks a fundamental question on equity achievement of such measures and develops a new framework to incorporate road users' vulnerabilities in identifying critical network links. This study introduces new evaluation measures that integrate the most vulnerable zones for evacuation prioritization based on social, environmental, and economic vulnerabilities. Results show that the critical links for the vulnerable population during an evacuation are not always identified by conventional link-based measures that emphasize overall system efficiencies. Among the links selected as critical using the throughput measure, only 25% serve socially vulnerable communities and 38% serve environmentally vulnerable populations. This highlights the importance of considering road users' vulnerability when prioritizing resources to strengthen the links since a link disruption may cause more significant consequences for vulnerable road users. Decision-making to identify critical links and minimize the impact of disruptions remains critical to distribute resources more effectively during an emergency and support the timely and safe evacuation of vulnerable populations that should be prioritized to achieve more equitable evacuation and disaster responses. An online interactive map is developed based on the results of this study to show the exact location of the critical links and other important metrics. In general, network links that carry higher traffic volume and ensure connectivity to isolated subnetworks represent critical links because disruptions on the links would impact more people, with a greater magnitude of travel time increase from rerouting or rescheduling. However, the individuals and communities that use the infrastructure determine the importance of the road links during extreme weather events. If a certain link serves at-risk communities (e.g., lower income or older population) for hurricane evacuation, the link should be considered critical regardless of its total traffic volume or impact on travel time if disrupted. These links must be resilient to save lives within the neighborhood, facilitate the evacuation of vulnerable groups, and strengthen the region's overall resiliency. The proposed research identifies the criticality of network links by identifying the community impacts of network disruption. In particular, this study focuses on developing a framework to determine the critical network links based on the vulnerability or importance of communities in a hurricane-prone area using three vulnerability measures and compares the results with the outputs of traditional measures. [ABSTRACT FROM AUTHOR]

Abstract Objective To determine whether there were improvements in rheumatology care for rheumatoid arthritis (RA) between 2002 and 2019 in Ontario, Canada, and to evaluate the impact of rheumatologist regional supply on access. Methods We conducted a population-based retrospective study of all individuals diagnosed with RA between January 1, 2002 and December 31, 2019. Performance measures evaluated were: (i) percentage of RA patients seen by a rheumatologist within one year of diagnosis; and (ii) percentage of individuals with RA aged 66 years and older (whose prescription drugs are publicly funded) dispensed a disease modifying anti-rheumatic drug (DMARD) within 30 days after initial rheumatologist visit. Logistic regression was used to assess whether performance improved over time and whether the improvements differed by rheumatology supply, dichotomized as

Measuring project management performance is complex and requires tools to capture the dynamic nature of the processes involved. Since the conception of system dynamics in the 1950s, the method has been used to solve complex projects. Project management possesses dynamic characteristics that involve planning, human resources, implementation, and control elements; thereby, using system dynamics to measure project management performance is a realistic approach. A research study was conducted using system dynamics to develop project management performance measures to capture the complexity of the process in local government agencies. The research approach considers measuring project engineering management performance as a holistic system influenced by leadership involvement, project management processes, and project engineering manager’s ability. The Zachman architectural framework was used to develop the project-management performance system’s ontology as the system dynamics model’s foundation. A case study was conducted for three cities with local government agencies to better understand the model components and factors that influence performance. Leadership involvement, project management processes, and project manager abilities were identified as critical factors that influence the project management performance level. To validate the results of the case study, the project management performance was further studied for the City of El Paso in terms of capability, capacity, and maturity level. The research study concluded that system dynamics is a feasible method and effective tool to measure management performance for engineering projects at local government agencies.

Purpose of Review: Aneurysmal subarachnoid hemorrhage carries high mortality and morbidity. Quality improvement (QI) efforts in the management of this disease process are growing as the field of neurocritical care matures. This review provides updates in QI in subarachnoid hemorrhage (SAH) and discusses gaps and future directions. Recent Findings: Literature published on the topic over the past 3 years were evaluated. An assessment of current QI practices pertaining to the acute care of SAH was conducted. These include processes surrounding acute pain management, inter-hospital coordination of care, complications during the initial hospital stay, role of palliative care, and quality metrics collection, reporting, and monitoring. Summary: SAH QI initiatives have shown promise by decreasing ICU and hospital lengths of stay, health care costs, and hospital complications. The review reveals substantial heterogeneity, variability, and limitations in SAH QI protocols, measures, and reporting. Uniformity in QI research, implementation, and monitoring will be crucial as disease-specific QI develops in neurological care. [ABSTRACT FROM AUTHOR]

There is a lack of diagnostic performance measures associated with pulmonary embolism (PE). We aimed to explore the concept of the time to diagnostic certainty, which we defined as the time interval that elapses between first presentation of a patient to a confirmed PE diagnosis with computed tomography pulmonary angiogram (CT PA). This approach could be used to highlight variability in health system diagnostic performance, and to select patient outliers for structured chart review in order to identify underlying contributors to diagnostic error or delay. We performed a retrospective observational study at academic medical centers and associated community-based hospitals in one health system, examining randomly selected adult patients admitted to study sites with a diagnosis of acute saddle PE. One hundred patients were randomly selected from 340 patients discharged with saddle PE. Twenty-four patients were excluded. Among the 76 included patients, time to diagnostic certainty ranged from 1.5 to 310 hours. We found that 73/76 patients were considered to have PE present on admission (CT PA ≤ 48 hours). The proportion of patients with PE present on admission with time to diagnostic certainty of > 6 hours was 26% (19/73). The median (IQR) time to treatment (thrombolytics/anticoagulants) was 3.5 (2.5-5.1) hours among the 73 patients. The proportion of patients with PE present on admission with treatment delays of > 6 hours was 16% (12/73). Three patients acquired PE during hospitalization (CT PA > 48 hours). In this study, we developed and successfully tested the concept of time to diagnostic certainty for saddle PE.

To control their enterprises in a complex environment, decision-makers need to measure their enterprise regularly to perpetuate. For that, they use a specific set of performance indicators grouped in a coherent system named performance measurement systems (PMS). Such systems are generally defined and implemented using different methods. As business performance measurement appeared from the 1900s, a large number of approaches developed by researchers and practitioners have appeared since those years until today. They were not designed for the same purpose and on the same basis and each of them has advantages and disadvantages to measure optimally the performance. So, decision-makers have difficulties to choose among these methods the most appropriate to their needs when they want to design and implement their customised PMS. The objective of this paper is to present the main concepts that approaches are based on, to present a state of the art as exhaustive as possible of the approaches and methods themselves and to make a comparison between them in order to allow decision-makers to choose among them the one or a combination of several ones which would efficiently suit to their needs to reach their global objective of PMS design and implementation. [ABSTRACT FROM AUTHOR]

Task composition in cloud manufacturing involves the selection of appropriate services from the cloud manufacturing platform and combining them to process the task with the purpose of achieving its expected performance. Calculation methods for achieving the performance expected by customers when the task has two or more composition patterns (e.g. sequential and switching pattern) are necessary because most tasks have multiple composition patterns in cloud manufacturing. Previous studies, however, have focused only on a single composition pattern. In this paper, we regard a task as a directed acyclic graph, and propose graph-based algorithms to obtain cost, execution time, quality and reliability of a task having multiple composition patterns. In addition, we model the task composition problem by introducing cost and execution time as performance attributes, and quality and reliability as basic attributes in the Kano model. Finally, an experiment to compare the performances of three metaheuristic algorithms (namely, variable neighbourhood search, genetic, and simulated annealing) is conducted to solve the problem. The experimental result shows that the variable neighbourhood search algorithm yields better and more stable solutions than the genetic algorithm and simulated annealing algorithms. [ABSTRACT FROM AUTHOR]

Diabetes Mellitus (DM) is a condition induced by unregulated diabetes that may lead to multi-organ failure in patients. Thanks to advances in machine learning and artificial intelligence, which enables the early detection and diagnosis of DM through an automated process which is more advantageous than a manual diagnosis. Currently, many articles are published on automatic DM detection, diagnosis, and self-management via machine learning and artificial intelligence techniques. This review delivers an analysis of the detection, diagnosis, and self-management techniques of DM from six different facets viz., datasets of DM, pre-processing methods, feature extraction methods, machine learning-based identification, classification, and diagnosis of DM, artificial intelligence-based intelligent DM assistant and performance measures. It also discusses the conclusions of the previous study and the importance of the results of the study. Also, three current research issues in the field of DM detection and diagnosis and self-management and personalization are listed. After a thorough screening procedure, 107 main publications from the Scopus and PubMed repositories are chosen for this study. This review provides a detailed overview of DM detection and self-management techniques which may prove valuable to the community of scientists employed in the area of automatic DM detection and self-management.

Background: Acute stroke care service in Armenia was established in 2019 after the implementation of the National Stroke Program (NSP). This study aimed to provide an up-to-date account of the current image and clinical characteristics of acute stroke service implementation at a tertiary hospital in Armenia by analyzing the quality of care and identifying the areas that need improvement. Methods: We analyzed patient data from a single hospital in 1 year after the establishment of acute stroke care service (February 2021–January 2022). We selected patients who were within 0–24 h from symptom onset at admission and included patients who benefited from reperfusion therapies (intravenous thrombolysis (IVT) and/or endovascular thrombectomy (EVT)). A favorable outcome was defined as a drop in the National Institutes of Health Stroke Scale (NIHSS) by more than four points at discharge and a modified Rankin score (mRS) of 0–2 at 90 days. Results: Of the total 385 patients, 155 underwent reperfusion therapies, 91% of patients (141/155) arrived by ambulance, 79.2% (122/155) had neurological improvement at discharge, and 60.6% (94/155) had anmRS of 0–2 at 3months. Less than 5% of patients had early direct access to the rehabilitation center. Conclusion: Our study demonstrated that the implementation of NSP with organized protocol-driven inpatient care led to significant advancement in acute stroke service performance. We believe that our report will serve as a model for achieving advanced and structured stroke care in a resource-limited context and contribute to the future development of the healthcare system in our country. [ABSTRACT FROM AUTHOR]

Performance thresholds are an important tool for determining successful conservation outcomes. They provide an objective means of defining good ecological condition and have been endorsed as an essential part of best practice in protected area (PA) management within the International Union for the Conservation of Nature Green List of Protected and Conserved Areas Standard. With a growing number of PAs attaining Green List status globally, thresholds developed by PAs on the Green List present an excellent resource with which to identify the attributes of well‐defined performance thresholds. We examined 349 thresholds associated with PAs on the Green List to determine whether they were specific and measurable (i.e., factors recognized as essential for setting well‐defined targets). We assessed whether thresholds were defined quantitatively and whether definitions included ambiguous terms (e.g., stable numbers). We identified six different ways thresholds were expressed and found that many thresholds were expressed as management objectives, rather than ecological condition thresholds, although this trend improved over time. Approximately one‐half of the performance thresholds lacked the necessary specificity to delineate successful outcomes. Our results enabled us to develop a checklist of information required to set robust performance thresholds. Recommendations include that thresholds should be quantitatively defined, including quantitative estimates of the limits of acceptable change (LAC) around the target condition. To ensure transparency, a rationale and associated evidence should be provided to support the threshold and the LAC. When accompanied by a rationale and quantitative estimate of the current condition of the value, unambiguously defined thresholds with a quantitative LAC provide an objective means of demonstrating that successful conservation outcomes have been achieved. These recommendations will help conservation managers apply the Green List Standard and improve the measurement of conservation outcomes more broadly. [ABSTRACT FROM AUTHOR]

The dynamic stability of long combination vehicles (LCVs) is an important part of vehicle safety. An LCV, its driver and the road constitute a unique closed-loop dynamic system. Assessing the dynamic stability is difficult due to the complex interactions of driver-tractor-trailers-road. Rearward amplification (RA) is an effective performance measure of the dynamic stability; various methods are applied for evaluating the RA. However, the measures from different methods may differ significantly. What are the root causes for the disparity of evaluation results? This paper tackles the problem by investigating the typical methods for evaluating the measure of two LCVs, i.e. an A-train double and a B-train double. To this end, simulations of the LCVs are conducted using TruckSim software. The study discloses the main causes for the disparity of the measures from different methods, and recommends the effective approaches to the assessment of the RA. [ABSTRACT FROM AUTHOR]

Measuring project management performance is complex and requires tools to capture the dynamic nature of the processes involved. Since the conception of system dynamics in the 1950s, the method has been used to solve complex projects. Project management possesses dynamic characteristics that involve planning, human resources, implementation, and control elements; thereby, using system dynamics to measure project management performance is a realistic approach. A research study was conducted using system dynamics to develop project management performance measures to capture the complexity of the process in local government agencies. The research approach considers measuring project engineering management performance as a holistic system influenced by leadership involvement, project management processes, and project engineering manager's ability. The Zachman architectural framework was used to develop the project-management performance system's ontology as the system dynamics model's foundation. A case study was conducted for three cities with local government agencies to better understand the model components and factors that influence performance. Leadership involvement, project management processes, and project manager abilities were identified as critical factors that influence the project management performance level. To validate the results of the case study, the project management performance was further studied for the City of El Paso in terms of capability, capacity, and maturity level. The research study concluded that system dynamics is a feasible method and effective tool to measure management performance for engineering projects at local government agencies. [ABSTRACT FROM AUTHOR]

In the recent era, graph neural networks are widely used on vision-to-language tasks and achieved promising results. In particular, graph convolution network (GCN) is capable of capturing spatial and semantic relationships needed for visual question answering (VQA). But, applying GCN on VQA datasets with different subtasks can lead to varying results. Also, the training and testing size, evaluation metrics and hyperparameter used are other factors that affect VQA results. These, factors can be subjected into similar evaluation schemes in order to obtain fair evaluations of GCN based result for VQA. This study proposed a GCN framework for VQA based on fine tune word representation to solve handle reasoning type questions. The framework performance is evaluated using various performance measures. The results obtained from GQA and VQA 2.0 datasets slightly outperform most existing methods. [ABSTRACT FROM AUTHOR]

The shareholder's interest oriented from business operation relies on opportunism regulation of the manager under asymmetry. Effective motivation incentives should be exploited to facilitate the manager's effort devotion enthusiasms. This paper establishes a theoretic model in which the shareholder offers equity-based incentive to a fairness-preferred manager to coordinate their interest conflicts and maximize her expected revenue. The manager exerts unverifiable levels of efforts toward both decision and coordination tasks making the most of his private information about fairness preference. Two interrelated performance measures on different hierarchical levels are considered for contracting purposes. In each situation, we derive the equilibrium effort choices and incentive coefficients of both participants, and investigate how these decisions are affected by fairness preference. Research findings suggest that the incorporation of firm equity dominates pure profit incentive in eliciting high effort levels toward two distinctive managerial tasks. Besides, the equity-based incentive weakens the perceived unfairness and facilitates the participants' expected revenue. Comparative statics and numerical analysis are conducted to demonstrate our results and the effectiveness of the proposed equity-based incentive. Finally, we summarize the contributions of this paper and put forward directions for further study. [ABSTRACT FROM AUTHOR]

Total Quality Management (TQM) is a tool to involve employees in the continuous improvement. SMEs are a well-known as the vital sector to Malaysia's Gross Domestic Product (GDP). However, SMEs still face issues of their performances. Most of SMEs have issue in TQM implementation due to the lack of awareness and accepting of TQM. The objective of this paper is to examine the TQM implementation amongst SMEs, in order to enhance their performance by using Balanced Scorecard (BSC). 130 respondents from Malaysia SMEs in manufacturing sector have been sent in this survey. Finally, 64 respondents have responded, representing 49.2 of response rate. The result shows that TQM practices have positive and significant relationship towards the BSC with r=0.64 at P