Out Of Control Research Articles

An effective non‐restarting control chart based on the joint judgment

AbstractThe cumulative sum (CUSUM) and exponentially weighted moving average (EWMA) control charts have been widely used in industry and public health applications. Still, few researchers have paid attention to the practical problem in public health applications, in which the control chart statistic cannot be reset to zero after an out‐of‐control (OC) signal. Some studies have addressed this issue by adding an upper limit to the statistic or using adaptive hypothesis testing (AHT). However, the control chart with an upper limit added to the testing statistic leads to a loss of information, and the post‐outbreak false alarm rate is still higher than the restarting control chart. The AHT control charts could not quickly alarm for the pandemic outbreak alarm as expected. To improve these drawbacks of control chart monitoring, two phase‐II non‐restarting (NR) CUSUM–EWMA control charts with the AHT framework, named NR–CUSUM–EWMA and AHUTNR–CUSUM–EWMA control charts, are proposed to well alarm for the pandemic outbreak. The AHTUNR–CUSUM–EWMA control chart uses the joint judgment of the UNR–CUSUM–EWMA (uncorrected NR–CUMSUM–EWMA) and NR–CUSUM–EWMA control charts, and the run rule to enhance the efficiency of the pandemic outbreak alarm. Simulation results show that the proposed NR–CUSUM–EWMA and AHUTNR–CUSUM–EWMA control charts can well maintain the outbreak alarm rate and post‐outbreak false alarm rate without losing cumulative information. Finally, the applicability and effectiveness of the proposed method are illustrated by an application to measles surveillance in North Rhine‐Westphalia, Germany.

An artificial neural network approach for out‐of‐control stream identification in multiple stream processes

AbstractA multiple stream process (MSP) is a process at a point in time that generates several streams of output with quality variables and specifications that are identical in all streams. Statistical process control (SPC) schemes for MSPs are designed to issue an out‐of‐control (OC) signal when a possible change occurs from the in‐control (IC) state of the process. However, the SPM literature for MSPs lacks contributions regarding post‐hoc identification of the stream or group of streams responsible for an OC signal. In this article, we propose an artificial neural network (NN) specifically trained for this purpose and, through a Monte Carlo simulation, show its superiority in correctly identifying OC streams, since an OC signal has been correctly issued. The research is motivated by the need for a post hoc diagnosis of the heating, ventilation, and air conditioning (HVAC) systems installed on modern train coaches, generating multiple streams of quality variables of interest. A case study in this area based on the HVAC data (openly available online at https://github.com/unina‐sfere/NN4OCMSP) illustrates the practical applicability of the proposed approach, which is implemented in the Python package NN4OCMSP and published on the PyPI software repository.

Do integrated stroke units affect patient and family experience of care transitions?

Purpose Patients and families identify discharge from hospital as highly challenging. Less is known about experiences of transition between acute services and inpatient rehabilitation. We aimed to understand the experiences of patients and families as they transition to inpatient rehabilitation services, before and after the opening of a new integrated stroke and rehabilitation unit (ISU). Materials and methods Adults were recruited 7 days after transfer to inpatient rehabilitation, in two 6-month periods before and after the opening of the ISU. Their experiences of care continuity were evaluated with a survey. Univariate analyses compared survey data pre- and post-ISU. A subset of participants completed semi-structured interviews that underwent thematic analysis. Results 150 patients were recruited (median age 60 years, range 20-92 years, 72 female). There were no differences between pre- and post-ISU survey scores for patient or family experiences (all p > 0.3). Interview analysis identified 3 major themes: “Whānaungatanga - the foundation of patient experience”, “In the dark and out of control”, and “A nice view…but I want to be able to do more.” Conclusions Implementation of an integrated stroke and rehabilitation unit maintained levels of patient and family satisfaction. Interviews identified important themes for services planning to improve patient experience.

The Spiralling of Corporate Corruption and the Plummeting of Corporate Governance and Ethical Leadership in African Institutions

Generally, several factors around the corporate world influence different nations technologically, socially, economically, and politically. Specifically, this paper focuses on the African continent’s politics concerning corporate corruption, corporate governance, and ethical leadership. This study aims to critically reflect on and evaluate the significance of curbing and combating corruption, promoting governance and ethics in Africa, and furthering and practising those principles. It employed a theoretical, qualitative content analysis approach in which a critical evaluation of relevant in-depth literature review was used and conducted to achieve the study objective. The results of this study revealed that: Incompetent and unethical leaders succumb to corruption, causing Africa's corruption to spiral out of control. Competent and ethical leaders, on the other hand, resist corruption; African leaders and authorities should take steps to fight corruption through ethics and governance; African corporations have become increasingly corrupt; corporate governance and ethical leadership have declined in Africa; African politicians have uncurbed power to advance their private gains, and finally, African leaders need to change their mindsets and cultures to achieve economic growth. This study emphasizes and reiterates the importance of dealing effectively with corporate corruption and advancing governance and ethics to benefit the African population and the continent. It further provides a broad and deeper understanding of corruption, ethics, and governance. The conceptual, strategic model provided by this study may be selected and used by African leaders, authorities, boards of directors, shareholders, and Chief Executive Officers (CEOs), as a tool to address corruption in African organizations and institutions.

Phase I quality control framework for monitoring organ-at-risk dose

Objective. The aim of this work was to develop a Phase I control chart framework for the recently proposed multivariate risk-adjusted Hotelling’s T2 chart. Although this control chart alone can identify most patients receiving extreme organ-at-risk (OAR) dose, it is restricted by underlying distributional assumptions, making it sensitive to extreme observations in the sample, as is typically found in radiotherapy plan quality data such as dose-volume histogram (DVH) points. This can lead to slightly poor-quality plans that should have been identified as out-of-control (OC) to be signaled in-control (IC). Approach. We develop a robust iterative control chart framework to identify all OC patients with abnormally high OAR dose and improve them via re-optimization to achieve an IC sample prior to establishing the Phase I control chart, which can be used to monitor future treatment plans. Main Results. Eighty head-and-neck patients were used in this study. After the first iteration, P14, P67, and P68 were detected as OC for high brainstem dose, warranting re-optimization aimed to reduce brainstem dose without worsening other planning criteria. The DVH and control chart were updated after re-optimization. On the second iteration, P14, P67, and P68 were IC, but P40 was identified as OC. After re-optimizing P40’s plan and updating the DVH and control chart, P40 was IC, but P14* (P14’s re-optimized plan) and P62 were flagged as OC. P14* could not be re-optimized without worsening target coverage, so only P62 was re-optimized. Ultimately, a fully IC sample was achieved. Multiple iterations were needed to identify and improve all OC patients, and to establish a more robust control limit to monitor future treatment plans. Significance. The iterative procedure resulted in a fully IC sample of patients. With this sample, a more robust Phase I control chart that can monitor OAR doses of new plans was established.

Clinical and psychological associations and coping strategies for personality type D and depression in patients with coronary artery disease

The comorbidity of manifestations of psychological distress and cardiovascular diseases is complex. The degree of impact of psychological stress on the patient depends on the possibilities of the adaptive potential of the individual in the environment.Aim: To study the cognitive assessment of stress, coping strategies and clinical and psychological associations in personality type D and depression in patients with coronary artery disease (CAD).Material and Methods. The study included 112 CAD patients. The DS-14 questionnaire was used to determine personality type D.To determine the level of depression the hospital scale HADS (Hospital Anxiety and Depression Scale). To assess coping strategies, the questionnaires “Methods of Coping Behavior” and “Indicator of Stress Coping Strategies” were used. Difficult life situation (DLS) assessment was determined using the “Cognitive Assessment of DLS” methodology. The questionnaire “Types of Orientations in Difficult Situations” was used to study orientations in DLS.Results. Patients were divided into groups based on manifestations of psychological distress: with type D (n = 40), without type D (n = 72); with depression (n = 48) without depression (n = 82). In type D, there was a more frequent assessment of the situation as out of control (12.0 ± 4.6 points versus 11.0 ± 4.6 points, p = 0.049) and orientation towards losses in difficult situations (17.0 ± 4.1 points 15.5 ± 5.1, points, p = 0.016). In depression, less pronounced desire for difficulties (19.0 ± 5.0 points versus 23.0 ± 5.9 points, p = 0.006), orientation towards opportunities (15.5 ± 3.2 points versus 18.0 ± 3.5 points, p < 0.001). In type D, the strategies “Escape-avoidance” (p = 0.05) and “Self-control” (p = 0.04) were used more often. In depression, the strategies “Problem resolution” (p = 0.02), “Search for social support” (p < 0.001) and “Avoidance” (p = 0.02) were more often used, less often – “Confrontational coping” (p = 0.001).Conclusion. Differences in cognitive assessment and coping strategies were revealed in patients with coronary artery disease in personality type D and the development of depression symptoms. This study emphasizes the need for individualized behavioral interventions for patients with coronary artery disease with manifestations of psychological distress.

'Either something's wrong, or I'm a terrible parent': A systematic review of parent experiences of illness-related interpretations for unsettled babies.

To explore parents' experiences of unsettled babies and medical labels. Qualitative systematic review, thematic synthesis and development of a conceptual model. Systematic review and thematic synthesis of primary, qualitative research into parents' experiences of unsettled babies <12 months of age. 'Unsettled' was defined as perception of excessive crying with additional feature(s) such as vomiting, skin or stool problems. The Critical Appraisal Skills Programme (CASP) checklist was used to assess trustworthiness. Structured searches completed in CINAHL, Medline, Embase, PsychINFO and CochraneCT on 23 March 2022 and rerun on 14 April 2023. Ten eligible studies were included across eight countries contributing data from 103 mothers and 24 fathers. Two analytical themes and eight descriptive themes were developed. Firstly, parents expressed fearing judgement, feeling guilty and out of control as a result of babies' unsettled symptoms and seeking strategies to construct an 'Identity as a "Good Parent"'. This desire for positive parenting identity underpinned the second analytical theme 'Searching for an explanation' which included seeking external (medical) causes for babies' unsettled behaviours. Parents can become trapped in a cycle of 'searching for an explanation' for their baby's unsettled behaviours, experiencing considerable distress which is exacerbated by feelings of guilt and failure. Insight gained from this review could inform interventions to support parents, reducing inaccurate medicalization. Health visiting teams supporting parents with unsettled baby behaviour could focus on supporting a positive parenting identity by managing expectations, normalizing the continuum of infant behaviours, reducing feelings of guilt or uncertainty and helping parents regain a feeling of control. ENTREQ guidelines were adhered to in the reporting of this review. Parent input was crucial in the design phase; shaping the language used (e.g., 'unsettled babies') and in the analysis sense-checking findings.

Optimal constrained design of control charts using stochastic approximations

In statistical process monitoring, control charts typically depend on a set of tuning parameters besides its control limit(s). Proper selection of these tuning parameters is crucial to their performance. In a specific application, a control chart is often designed for detecting a target process distributional shift. In such cases, the tuning parameters should be chosen such that some characteristic of the out-of-control (OC) run length of the chart, such as its average, is minimized for detecting the target shift, while the control limit is set to maintain a desired in-control (IC) performance. However, explicit solutions for such a design are unavailable for most control charts, and thus numerical optimization methods are needed. In such cases, Monte Carlo-based methods are often a viable alternative for finding suitable design constants. The computational cost associated with such scenarios is often substantial, and thus computational efficiency is a key requirement. To address this problem, a two-step design based on stochastic approximations is presented in this paper, which is shown to be much more computationally efficient than some representative existing methods. A detailed discussion about the new algorithm’s implementation along with some examples are provided to demonstrate the broad applicability of the proposed methodology for the optimal design of univariate and multivariate control charts. Computer codes in the Julia programming language are also provided in the supplemental material.

THE RELATIONSHIP OF PARENTS USING THERAPEUTIC COMMUNICATION WITH TEMPER TANTRUM BEHAVIOR IN PRESCHOOL CHILDREN AT RT 021 RW 006 SUKAJAYA VILLAGE

Temper tantrum is an outburst of emotion that is out of control and out of control. The signs and symptoms of this temper tantrum vary, ranging from just whining, crying, screaming, rolling on the floor, kicking, hitting. The impact of this temper tantrum is quite dangerous. For example, a child who vents his frustration by rolling on a hard floor can cause injury to the child. According to data from the Indonesian Ministry of Health, the number of children aged 2-4 years in Indonesia who experience temper tantrums is quite large, which is around 19.39 million people. This study aims to determine the relationship between parents using therapeutic communication with temper tantrum behavior in preschool children in RT 021 RW 006 Sukajaya Village. This study used an analytical observational design with a cross sectional design. Sampling using non-probabilty sampling purposive sampling type with a total of 110 respondents. It was found that the results of the Chi Square test had a significant value of 0.045 &lt; a value (0.05). There is a relationship between parents using therapeutic communication with temper tantrum behavior in preschool age children in RT 021 RW 006 Sukajaya Village. There is a relationship between parents using therapeutic communication with temper tantrum behavior in preschool age children in RT 021 RW 006 Sukajaya.

A nonparametric adaptive EWMA control chart for monitoring mixed continuous and categorical data using self-starting strategy

In the context of big data-driven smart manufacturing, data is often characterized by high dimensionality, numerous variables, and complex associations. As a result, mixed continuous and categorical data are increasingly common. In the case of data that consist of a combination of continuous and categorical variables with unknown distributions, the application of traditional parametric control charts for monitoring purposes becomes challenging. Therefore, a novel nonparametric adaptive exponentially weighted moving average (EWMA) control chart using a self-starting strategy is proposed in this paper. First, the process of converting continuous data into categorical data is conducted using the data categorization method. The log-linear modeling is subsequently employed to investigate the relationships between various variables. Next, a nonparametric adaptive EWMA statistic is constructed to monitor mixed continuous and categorical data, and the self-starting strategy is employed to gradually expand the size of the in-control (IC) dataset and to update the parameters in real time. Then, a numerical simulation is conducted to compare the IC and out-of-control (OC) performance of the proposed chart with other control charts. According to the simulation result, it can be concluded that the proposed chart offers a more effective means of detecting shifts in the production process. Finally, a concrete illustration of an authentic dataset regarding red wine quality is provided to further clarify the effectiveness of the proposed control chart in monitoring mixed continuous and categorical data.

EVALUATION AND IMPLIMENTATION OF A COMMERCIAL QUALITY CONTROL PRODUCT TO MONITOR SERUM INDICES DETECTION IN DAILY ROUTINE USE

Abstract Introduction/Objective Clinical Chemistry analyzers measure serum indices of each sample. Serum indices affect patient result. Yet there is no current common practice of monitoring the Instruments ability to measure serum indices using a commercial QC product. In this study, we focused on such Q.C. product evaluation. Methods/Case Report We evaluated the implementation of daily routine use of serum indices QC. We used a commercially available Bio-Rad (Hercules, California, United States) LiquichekTM Serum Indices QC material on Abbott (Abbott Park, Illinois, United States) Architect c8000 Chemistry analyzers in National Guard Hospital, Jeddah, Saudi Arabia. We run the QC twice a day in three Instruments for Two months. Data transferred to Bio-Rad Unity Real Time, a QC data management software. Mean, standard deviation and coefficient of variation calculated for each Instrument. Results (if a Case Study enter NA) A total of 1,296 data points were collected. The QC performed well with a precision of % CV ≤ 1.97% Hemolysis, ≤ 2.67% Icterus and ≤ 6.80% Lipemia. The three instruments performed with a slightly different mean. No “out of control” situations observed. TAT was not affected. To mimic a possible day-to-day Lab scenario, the saline bottle used as HIL reagent was deliberately contaminated using a few drops of whole blood to study the effect of gross hemolysis reagent contamination on HIL readings. The commercial HIL quality control detected the problem. Its performance showed increase in Hemolysis, slight decrease in Icterus and a slight increase in Lipemia readings. Conclusion Bio-Rad Liquichek Serum Indices QC is easy to use with a long shelf life. It helps to monitor the instrument’s ability to detect the sample integrity. Results can be compared to peer group unlike the home brewed QC. Peer group comparison helps to monitor and troubleshoot any bias or shift from the peer group and brings benefit to the total QC process.

The Power of Chaos

The Power of Chaos

Alternative parameter learning schemes for monitoring process stability

In statistical process control, accurately estimating in-control (IC) parameters is crucial for effective monitoring. This typically requires a Phase I analysis to obtain estimates before monitoring commences. The traditional “fixed” estimate (FE) approach uses these estimates exclusively, while the “adaptive” estimate (AE) approach updates the estimates with each new observation. Such extreme criteria reflect the traditional bias-variance tradeoff in the framework of the sequential parameter learning schemes. This paper proposes an intermediate update rule that generalizes two ad hoc criteria for monitoring univariate Gaussian data, by giving a lower probability to parameter updates when an out-of-control (OC) situation is likely, therefore updating more frequently when there is no evidence of an OC scenario. The simulation study shows that this approach improves the detection power for small and early shifts, which are commonly regarded as a weakness of control charts based on fully online adaptive estimation. The paper also shows that the proposed method performs similarly to the fully adaptive procedure for larger or later shifts. The proposed method is illustrated by monitoring the sudden increase in ICU counts during the 2020 COVID outbreak in New York.

Heteroantigen-assembled nanovaccine enhances the polyfunctionality of TILs against tumor growth and metastasis

The dysfunction of tumor infiltrating lymphocytes (TILs) directly correlates with out of control of tumor growth and metastasis. New approaches and insightful clarity for rescuing TILs dysfunction are urgently needed. Here, we design two heterogenous antigens based on MHC-I epitope and MHC-II epitope from tumor, and assemble heterogenous antigens by electrostatic interactions and π-π stacking into heteroantigen-assembled nanovaccine (HANV). HANV not only significantly increases the abundance of CD8+ and CD4+ TILs, but also elicits stronger polyfunctionality of CD8+ and CD4+ TILs in vivo. Enhanced polyfunctionality of CD8+ and CD4+ TILs positively correlate to suppression of tumor growth and metastasis in melanoma-bearing mouse models. We also validate that nucleotide-binding oligomerization domain-containing protein 2 (NOD2) dominantly enhances anti-tumor capacity of TILs in a temporal immunoregulation manner. This work presents a new insight in developing HANV as a rational strategy to shape TILs polyfunctionality for tumor growth and metastasis.

A Coupled Tensor–DEM–FEM Model for the Whole Process of Internal Fine-Scale Damage to Surface Damage in Red-Bed Soft Rocks in the Coastal Area of South China

Calculation and characterization of the whole process of internal microscopic damage to surface damage in red-bed soft rock is a theoretical research difficulty and an urgent need for engineering safety protection. However, the current study cannot accurately and directly correlate internal and external damage. Therefore, in this paper, a coupled tensor–DEM–FEM model is proposed to deal with surface damage by indoor triaxial test digital image processing (DIC), internal damage by FJM acoustic emission study, and internal and external damage by moment tensor correlation. The study demonstrates that the whole process damage process of the red-bed soft rock peak front can be divided into six distinct phases, with early damage beginning with the elastic phase; the local strain divergence value begins to spiral out of control during the period of crack acceleration development; the overall acoustic emission intensity distribution is in the range of [−8.5, −6.3] in two dimensions and in the range of [−11, −9] in three dimensions; the R were between −40 and 40, which corresponded to the results of the indoor tests. A model has been developed that allows a direct reflection of the whole damage process. The method can be used to better understand the disaster mechanism and guide engineering practice.

Marcus Aurelius' Stoicism and its Solution to Overthinking

&lt;p&gt;This research was library research with overthinking as its material object and the Stoicism of Marcus Aurelius as a formal object. The main problem in this study is how Marcus Aurelius' Stoicism becomes a solution to overthinking. This research used critical analysis and heuristics methods. The data source in this research refers to the book or personal record of Marcus Aurelius, namely &lt;em&gt;Meditations&lt;/em&gt;, which is supported by other sources that are closely related to the problems of Stoicism and overthinking. There are some critical points as the solution to the overthinking of Marcus Aurelius' Stoicism, namely, first, living in harmony with nature, where things beyond human control are on the scale of nature. Second, regarding the treatment of others, the actions and words of others are beyond human control, and what should be controlled is their perception. Third, self-restraint is in of control of humans. Everything that comes from out of control will not affect and interfere if in of control can be managed with the argumentation that humans as a whole are human beings that have a ratio; then this is the core of Marcus Aurelius' Stoicism.&lt;/p&gt;

A sensitized variable selection control chart based on a classification algorithm for monitoring high‐dimensional processes

AbstractDuring the last decade, variable‐selection‐based (VS) control charts have gained much popularity for process monitoring and diagnosis. These charts have been proven efficient for the detection of sparse mean shifts in high‐dimensional processes. VS charts usually assume that in‐control (IC) data are the only information used to determine the control limits. In modern industrial processes, however, out‐of‐control (OC) data can be easily collected. Detecting a specific shift in a data‐rich environment without utilizing OC data information will limit the development of a process monitoring scheme. In this paper, a novel variable selection control chart that is combined with a classification algorithm is proposed, which is expected to benefit from both the classification and variable selection approaches. In contrast to alternative charts, the proposed sensitized variable selection chart can capture the potential shifted variables using both IC and OC information, which can improve the sensitivity of the chart in a specific direction. Extensive Monte Carlo simulations demonstrate that the proposed chart outperforms the alternatives in a data‐rich and high‐dimensional environment. A real‐life example of cellular localization is also included to support the findings of our study.

MSR79 Predicting Medication Adherence Using Blue Cross and Blue Shield of Louisiana's Historical Medical Claims

Medication non-adherence contributes to significant health care costs and detriments overall quality of life. Non-adherence may cause underlying conditions to spiral out of control until a disease is no longer manageable. Historically, only around 60% of prescribed medications are taken properly. Blue Cross and Blue Shield of Louisiana introduces the risk of medication non-adherence (RoMNA) models which leverage machine learning to predict whether someone is at risk of not taking their medication as prescribed. The models predict three classes of drugs: diabetes medications (non-insulin), anti-hypertensives and statins.

Knockoff procedure for false discovery rate control in high-dimensional data streams

Motivated by applications to root-cause identification of faults in high-dimensional data streams that may have very limited samples after faults are detected, we consider multiple testing in models for multivariate statistical process control (SPC). With quick fault detection, only small portion of data streams being out-of-control (OC) can be assumed. It is a long standing problem to identify those OC data streams while controlling the number of false discoveries. It is challenging due to the limited number of OC samples after the termination of the process when faults are detected. Although several false discovery rate (FDR) controlling methods have been proposed, people may prefer other methods for quick detection. With a recently developed method called Knockoff filtering, we propose a knockoff procedure that can combine with other fault detection methods in the sense that the knockoff procedure does not change the stopping time, but may identify another set of faults to control FDR. A theorem for the FDR control of the proposed procedure is provided. Simulation studies show that the proposed procedure can control FDR while maintaining high power. We also illustrate the performance in an application to semiconductor manufacturing processes that motivated this development.

A novel hyperbolic tangent sliding mode observation of vehicle lateral force fed back by longitudinal force error

AbstractThe tyre lateral force control is crucial to vehicle lateral stability. Vehicle side slip and out of control can be prevented effectively by observing accurately the lateral force. Thus, a novel quasi‐sliding mode observer (QSMO) is proposed. The algorithm adopts the longitudinal tyre force error as feedback considering vehicle parameter uncertainties and without a complex tyre model. First, the on‐line verification of the algorithm was carried out by dSPACE for using the experimental data of the real vehicle linear acceleration and deceleration conditions, and comparison of experimental output with different observation algorithms. Further, the simulation under emergency obstacle avoidance conditions and the double‐line shifting conditions were conducted to verify the accuracy of the algorithm respectively. Simulation results show that the percentage errors between the tyre lateral forces from the proposed QSMO and the actual data are less than 5.35%, and the prediction accuracy of the QSMO by 38.78% is higher than that of the conventional first‐order SMO (FSMO), which indicates that the QSMO is superior to the FSMO.