Biologically Inspired Self-Healing Software System Architecture

Self-healing capabilities have begun to emerge as an interesting and potentially valuable property of software systems. Self-healing characteristic enables software systems to continuously and dynamically monitor, diagnose, and adapt itself after a failures has occur in their components. Adding such characteristic into existing software systems is immensely useful and valuable for allowing them to recover from failures. However, developing such self-healing software systems is a significant challenge. The nature introduces to us unforeseen concepts in terms of presenting biological systems that have the ability to handle its abnormal conditions. Based on this observation, this thesis presents self healing architecture for software system based on one of the biological processes that have the ability to heal by itself (the wound-healing process). The self-healing architecture provides software systems the ability to handle anomalous conditions that appear among its components. The presented architecture is divided into to layers, functional and healing layer. In the functional layer, the components of the system provide its services without any disruptions. The component is considered as faulty component if it fails to provide its services. The healing layer aims to heal the faulty component and return it to the running system without the awareness of the user. The presented self-healing software system is formally described to prove its functionality. Set-theoretic and Finite State Machine (FSM) is introduced. A prototype for the presented architecture has been implemented using Java language. Java objects are considered as the system components. The modules of the healing layer in the selfhealing architecture have been implemented into Java classes. An object from the module class will be created to perform its task for the healing process. The thesis concludes with recommendations for future works in this area and enhancement of the presented architecture

Biologically Inspired Self-Healing Software System Architecture

Self-healing capabilities have begun to emerge as an interesting and potentially valuable property of software systems. Self-healing characteristic enables software systems to continuously and dynamically monitor, diagnose, and adapt itself after a failures has occur in their components. Adding such characteristic into existing software systems is immensely useful and valuable for allowing them to recover from failures. However, developing such self-healing software systems is a significant challenge. The nature introduces to us unforeseen concepts in terms of presenting biological systems that have the ability to handle its abnormal conditions. Based on this observation, this thesis presents self healing architecture for software system based on one of the biological processes that have the ability to heal by itself (the wound-healing process). The self-healing architecture provides software systems the ability to handle anomalous conditions that appear among its components. The presented architecture is divided into to layers, functional and healing layer. In the functional layer, the components of the system provide its services without any disruptions. The component is considered as faulty component if it fails to provide its services. The healing layer aims to heal the faulty component and return it to the running system without the awareness of the user. The presented self-healing software system is formally described to prove its functionality. Set-theoretic and Finite State Machine (FSM) is introduced. A prototype for the presented architecture has been implemented using Java language. Java objects are considered as the system components. The modules of the healing layer in the selfhealing architecture have been implemented into Java classes. An object from the module class will be created to perform its task for the healing process. The thesis concludes with recommendations for future works in this area and enhancement of the presented architecture

Biologically Inspired Self-Healing Software System Architecture

Self-healing capabilities have begun to emerge as an interesting and potentially valuable property of software systems. Self-healing characteristic enables software systems to continuously and dynamically monitor, diagnose, and adapt itself after a failures has occur in their components. Adding such characteristic into existing software systems is immensely useful and valuable for allowing them to recover from failures. However, developing such self-healing software systems is a significant challenge. The nature introduces to us unforeseen concepts in terms of presenting biological systems that have the ability to handle its abnormal conditions. Based on this observation, this thesis presents self-healing architecture for software system based on one of the biological processes that have the ability to heal by itself (the wound-healing process). The self-healing architecture provides software systems the ability to handle anomalous conditions that appear among its components. The presented architecture is divided into to layers, functional and healing layer. In the functional layer, the components of the system provide its services without any disruptions. The component is considered as faulty component if it fails to provide its services. The healing layer aims to heal the faulty component and return it to the running system without the awareness of the user. The presented self-healing software system is formally described to prove its functionality. Set-theoretic and Finite State Machine (FSM) is introduced. A prototype for the presented architecture has been implemented using Java language. Java objects are considered as the system components. The modules of the healing layer in the selfhealing architecture have been implemented into Java classes. An object from the module class will be created to perform its task for the healing process. The thesis concludes with recommendations for future works in this area and enhancement of the presented architecture.

Evolving trends in the management of acute appendicitis during COVID-19 waves. The ACIE appy II study

Background: In 2020, ACIE Appy study showed that COVID-19 pandemic heavily affected the management of patients with acute appendicitis (AA) worldwide, with an increased rate of non-operative management (NOM) strategies and a trend toward open surgery due to concern of virus transmission by laparoscopy and controversial recommendations on this issue. The aim of this study was to survey again the same group of surgeons to assess if any difference in management attitudes of AA had occurred in the later stages of the outbreak. Methods: From August 15 to September 30, 2021, an online questionnaire was sent to all 709 participants of the ACIE Appy study. The questionnaire included questions on personal protective equipment (PPE), local policies and screening for SARS-CoV-2 infection, NOM, surgical approach and disease presentations in 2021. The results were compared with the results from the previous study. Results: A total of 476 answers were collected (response rate 67.1%). Screening policies were significatively improved with most patients screened regardless of symptoms (89.5% vs. 37.4%) with PCR and antigenic test as the preferred test (74.1% vs. 26.3%). More patients tested positive before surgery and commercial systems were the preferred ones to filter smoke plumes during laparoscopy. Laparoscopic appendicectomy was the first option in the treatment of AA, with a declined use of NOM. Conclusion: Management of AA has improved in the last waves of pandemic. Increased evidence regarding SARS-COV-2 infection along with a timely healthcare systems response has been translated into tailored attitudes and a better care for patients with AA worldwide

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

External validation and recalibration of an incidental meningioma prognostic model - IMPACT: protocol for an international multicentre retrospective cohort study

Introduction: Due to the increased use of CT and MRI, the prevalence of incidental findings on brain scans is increasing. Meningioma, the most common primary brain tumour, is a frequently encountered incidental finding, with an estimated prevalence of 3/1000. The management of incidental meningioma varies widely with active clinical-radiological monitoring being the most accepted method by clinicians. Duration of monitoring and time intervals for assessment, however, are not well defined. To this end, we have recently developed a statistical model of progression risk based on single-centre retrospective data. The model Incidental Meningioma: Prognostic Analysis Using Patient Comorbidity and MRI Tests (IMPACT) employs baseline clinical and imaging features to categorise the patient with an incidental meningioma into one of three risk groups: low, medium and high risk with a proposed active monitoring strategy based on the risk and temporal trajectory of progression, accounting for actuarial life expectancy. The primary aim of this study is to assess the external validity of this model. Methods and analysis: IMPACT is a retrospective multicentre study which will aim to include 1500 patients with an incidental intracranial meningioma, powered to detect a 10% progression risk. Adult patients ≥16 years diagnosed with an incidental meningioma between 1 January 2009 and 31 December 2010 will be included. Clinical and radiological data will be collected longitudinally until the patient reaches one of the study endpoints: intervention (surgery, stereotactic radiosurgery or fractionated radiotherapy), mortality or last date of follow-up. Data will be uploaded to an online Research Electronic Data Capture database with no unique identifiers. External validity of IMPACT will be tested using established statistical methods. Ethics and dissemination: Local institutional approval at each participating centre will be required. Results of the study will be reported through peer-reviewed articles and conferences and disseminated to participating centres, patients and the public using social media

Evolving trends in the management of acute appendicitis during COVID-19 waves. The ACIE appy II study (vol 46, pg 2021, 2022)

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Global variation in postoperative mortality and complications after cancer surgery: a multicentre, prospective cohort study in 82 countries

© 2021 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY-NC-ND 4.0 licenseBackground: 80% of individuals with cancer will require a surgical procedure, yet little comparative data exist on early outcomes in low-income and middle-income countries (LMICs). We compared postoperative outcomes in breast, colorectal, and gastric cancer surgery in hospitals worldwide, focusing on the effect of disease stage and complications on postoperative mortality. Methods: This was a multicentre, international prospective cohort study of consecutive adult patients undergoing surgery for primary breast, colorectal, or gastric cancer requiring a skin incision done under general or neuraxial anaesthesia. The primary outcome was death or major complication within 30 days of surgery. Multilevel logistic regression determined relationships within three-level nested models of patients within hospitals and countries. Hospital-level infrastructure effects were explored with three-way mediation analyses. This study was registered with ClinicalTrials.gov, NCT03471494. Findings: Between April 1, 2018, and Jan 31, 2019, we enrolled 15 958 patients from 428 hospitals in 82 countries (high income 9106 patients, 31 countries; upper-middle income 2721 patients, 23 countries; or lower-middle income 4131 patients, 28 countries). Patients in LMICs presented with more advanced disease compared with patients in high-income countries. 30-day mortality was higher for gastric cancer in low-income or lower-middle-income countries (adjusted odds ratio 3·72, 95% CI 1·70–8·16) and for colorectal cancer in low-income or lower-middle-income countries (4·59, 2·39–8·80) and upper-middle-income countries (2·06, 1·11–3·83). No difference in 30-day mortality was seen in breast cancer. The proportion of patients who died after a major complication was greatest in low-income or lower-middle-income countries (6·15, 3·26–11·59) and upper-middle-income countries (3·89, 2·08–7·29). Postoperative death after complications was partly explained by patient factors (60%) and partly by hospital or country (40%). The absence of consistently available postoperative care facilities was associated with seven to 10 more deaths per 100 major complications in LMICs. Cancer stage alone explained little of the early variation in mortality or postoperative complications. Interpretation: Higher levels of mortality after cancer surgery in LMICs was not fully explained by later presentation of disease. The capacity to rescue patients from surgical complications is a tangible opportunity for meaningful intervention. Early death after cancer surgery might be reduced by policies focusing on strengthening perioperative care systems to detect and intervene in common complications. Funding: National Institute for Health Research Global Health Research Unit

Effects of hospital facilities on patient outcomes after cancer surgery: an international, prospective, observational study

© 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 licenseBackground: Early death after cancer surgery is higher in low-income and middle-income countries (LMICs) compared with in high-income countries, yet the impact of facility characteristics on early postoperative outcomes is unknown. The aim of this study was to examine the association between hospital infrastructure, resource availability, and processes on early outcomes after cancer surgery worldwide. Methods: A multimethods analysis was performed as part of the GlobalSurg 3 study—a multicentre, international, prospective cohort study of patients who had surgery for breast, colorectal, or gastric cancer. The primary outcomes were 30-day mortality and 30-day major complication rates. Potentially beneficial hospital facilities were identified by variable selection to select those associated with 30-day mortality. Adjusted outcomes were determined using generalised estimating equations to account for patient characteristics and country-income group, with population stratification by hospital. Findings: Between April 1, 2018, and April 23, 2019, facility-level data were collected for 9685 patients across 238 hospitals in 66 countries (91 hospitals in 20 high-income countries; 57 hospitals in 19 upper-middle-income countries; and 90 hospitals in 27 low-income to lower-middle-income countries). The availability of five hospital facilities was inversely associated with mortality: ultrasound, CT scanner, critical care unit, opioid analgesia, and oncologist. After adjustment for case-mix and country income group, hospitals with three or fewer of these facilities (62 hospitals, 1294 patients) had higher mortality compared with those with four or five (adjusted odds ratio [OR] 3·85 [95% CI 2·58–5·75]; p<0·0001), with excess mortality predominantly explained by a limited capacity to rescue following the development of major complications (63·0% vs 82·7%; OR 0·35 [0·23–0·53]; p<0·0001). Across LMICs, improvements in hospital facilities would prevent one to three deaths for every 100 patients undergoing surgery for cancer. Interpretation: Hospitals with higher levels of infrastructure and resources have better outcomes after cancer surgery, independent of country income. Without urgent strengthening of hospital infrastructure and resources, the reductions in cancer-associated mortality associated with improved access will not be realised. Funding: National Institute for Health and Care Research