Major System Failures Research Articles

Extraperitoneal robot assisted laparoscopic prostatectomy with Versius system: single centre experience.

Versius Surgical System (CMR Surgical, Cambridge, UK) is a novel tele-operated robotic surgical system designed to assist surgeons for minimally invasive surgery which is gaining momentum in the world of robotic surgery. We describe our single centre experience with Versius and report the advantages and challenges posed by this new robotic system in a series of 53 extraperitoneal robotic assisted laparoscopic prostatectomies (eRALP) for prostate cancer (PCa). Data of 53 eRALP performed with Versius in our centre were collected and analysed, Descriptive statistics were used to report our results. In 16 months we performed 53 eRALP: 18 (34%) with PLND, 33 (62%) nerve sparingcases. Mean setup time was 15 min, mean console time was 100 min and mean operative time was 130 min. We observed a substantial reduction of console time and set-up time after only 5 procedures. In the first 4 procedures, the dissection of the neurovascular bundle was performed laparoscopically, to switch back to robotic assisted approach afterwards. No major system failures were observed. No major intra-operative and post-operative complications occurred. Mean follow-up time was 9 months (range 3-15 months); no patients experienced biochemical recurrence or metastatic progression over this period, 8 (15%) patients had adjuvant radiotherapy based on unfavourable pathology report (positive surgical margins or positive limphnodes). This represents to our knowledge the largest extraperitoneal RALP case series with Versius, and it aims to provide solid clinical proof of the safety, effectiveness and versatility of this innovative system. In our experience, this platform represents a good option for every urologic surgeon who wants to start a robotic programme and it appears particularly suitable for urologists with a large laparoscopic expertise.

E3 ligases: a potential multi-drug target for different types of cancers and neurological disorders.

Ubiquitylation is a posttranslational modification of proteins that is necessary for a variety of cellular processes. E1 ubiquitin activating enzyme, E2 ubiquitin conjugating enzyme, and E3 ubiquitin ligase are all involved in transferring ubiquitin to the target substrate to regulate cellular function. The objective of this review is to provide an overview of different aspects of E3 ubiquitin ligases that can lead to major biological system failure in several deadly diseases. The first part of this review covers the important characteristics of E3 ubiquitin ligases and their classification based on structural domains. Further, the authors provide some online resources that help researchersexplore the data relevant to the enzyme. The following section delves into the involvement of E3 ubiquitin ligases in various diseases and biological processes, including different types of cancer and neurological disorders.

Voltage Stability Augmentation using Shunt FACTS

With the ever increasing demand of power, the major concern that has aroused is the problem of voltage instability. Due to voltage instability several major power system failures and blackouts occur. Voltage stability thus becomes a necessity. For this FACTS devices like SVC, STATCOM, etc. are used. Load Flow analysis and Continuation Power Flow Analysis is done to identify the weak buses and FACTS devices are installed in these weak buses to enhance the voltage stability. This paper presents a network formulation of IEEE 30 Bus test system using MATLAB and PSAT software and then comparing the effect of SVC and STATCOM for voltage stability enhancement.

Performance Analysis of Distributed Estimation for Data Fusion Using a Statistical Approach in Smart Grid Noisy Wireless Sensor Networks.

Internet of Things (IoT) can significantly enhance various aspects of today’s electric power grid infrastructures for making reliable, efficient, and safe next-generation Smart Grids (SGs). However, harsh and complex power grid infrastructures and environments reduce the accuracy of the information propagating through IoT platforms. In particularly, information is corrupted due to the measurement errors, quantization errors, and transmission errors. This leads to major system failures and instabilities in power grids. Redundant information measurements and retransmissions are traditionally used to eliminate the errors in noisy communication networks. However, these techniques consume excessive resources such as energy and channel capacity and increase network latency. Therefore, we propose a novel statistical information fusion method not only for structural chain and tree-based sensor networks, but also for unstructured bidirectional graph noisy wireless sensor networks in SG environments. We evaluate the accuracy, energy savings, fusion complexity, and latency of the proposed method by comparing the said parameters with several distributed estimation algorithms using extensive simulations proposing it for several SG applications. Results prove that the overall performance of the proposed method outperforms other fusion techniques for all considered networks. Under Smart Grid communication environments, the proposed method guarantees for best performance in all fusion accuracy, complexity and energy consumption. Analytical upper bounds for the variance of the final aggregated value at the sink node for structured networks are also derived by considering all major errors.

Contingency Analysis of Fault and Minimization of Power System Outage using Fuzzy Controller

In power systems, voltage stability perform the major role in design and its operation. Major system failures are occur due to voltage variability and breakdown. To meet and compensate the rising power demand of regular usage in modern trends, transmission networks are enormously loaded which create the voltage instability. Contingency analysis is a recognized energy managing tool. It calculate the violation in the transmission line. In this paper a computational controller fuzzy system is suggested to handle the transmission line outage and overload in other branch kind of problems in Power system. The efficiency of power transmission system with fuzzy controller is inveterate by computation of various parameters of transmission bus under different loading situations. For the contingency analysis the transmission power flow several methods have been developed. Fast Decoupled load flow program is the effective method which provides a fast and effective solution to the contingency analysis in the transmission system and also it is incorporate with matrix alteration formula which gives additional advantage for the system.

Effective fault prediction model developed using Least Square Support Vector Machine (LSSVM)

Software developers and project teams spend considerable amount of time in identifying and fixing faults reported by testers and users. Predicting defects and identifying regions in the source code containing faults before it is discovered or invoked by users can be valuable in terms of saving maintenance resources, user satisfaction and preventing major system failures post deployment. Fault prediction can also improve the effectiveness of software quality assurance activities by guiding the test team to focus efforts on fault prone components. The work presented in this paper involves building an effective fault prediction tool by identifying and investigating the predictive power of several well-known and widely used software metrics for fault prediction. We apply ten different feature selection techniques to choose the best set of metrics from a set of twenty source code metrics. We build the fault prediction model using Least Squares Support Vector Machine (LSSVM) learning method associated with linear, polynomial and radial basis function kernel functions. We perform experiments on 30 Open Source Java projects. Experimental results reveals that our prediction model is best suitable for projects with faulty classes less than the threshold value depending on fault identification efficiency (low- 52.139%, median- 46.206%, and high- 32.080%).

The Ganges Basin management and community empowerment

This paper explores the ecological effects of the top-down Ganges Basin water management systems in Chapra, Bangladesh, based on my ethnographic fieldworka data collected in 2011-12. An example of this top-down system is the Farakka Barrage in India that causes major ecological system failures and challenges to community livelihoods. The reduction in Ganges Basin water flow in Bangladesh based on the pre and post Farakka comparison is helpful in understanding these failures and their effects on community livelihoods. My argument is that basin communities are capable of becoming empowered by Ganges Basin water management and failures in the management create major challenges to the livelihood of these communities. In this context, I analyze the current Ganges Basin management practices, focusing specifically on the Joint River Commission and the 1996 Ganges Treaty between India and Bangladesh, and their effects on the basin communities in Chapra. My fieldwork data point out that the current shortcomings in basin management can be overcome with an improved management system. Water governance based on a multilateral approach is a way to restore the basin’s ecological systems and promote community empowerment. Based on this empowerment argument, this paper is divided into the following major sections: importance of the basin ecosystems for protecting community livelihoods, limitations of current basin management practices and community survival challenges, and proposed water governance for community empowerment.

Using Root Cause Analysis in Public Policy Pedagogy

Defining policy problems is crucial to the policy process. The definition process is difficult because it relies more on craft developed through experience and intuition than on objective methodology. The lack of a methodology presents considerable challenges to novice policy students because of their lack of knowledge and experience in defining complex problems and thus their undeveloped skill in craft. Root Cause Analysis (RCA), a structured methodology designed to analyze the causes and effects of problems, can be a powerful pedagogical method to increase student comprehension and success in defining policy problems. Although RCA was developed primarily as an ex post methodology in the engineering, computing, and health care fields to understand how major adverse events or system failures occurred, a modified RCA is well suited for identifying and analyzing complex and dynamic policy problems. This paper provides a framework on the use of RCA as a pedagogical method for improving policy student learning.

Power System Contingency Ranking using Fuzzy Logic Based Approach

Voltage stability is a major concern in planning and operations of power systems. It is well known that voltage instability and collapse have led to major system failures. Modern transmission networks are more heavily loaded than ever before to meet the growing demand. One of the major consequences resulted from such a stressed system is voltage collapse or instability. This paper presents fuzzy approach for ranking the contingencies using composite-index based on parallel operated fuzzy inference engine. The Line Flow index (L.F) and bus Voltage Magnitude (VM) of the load buses are expressed in fuzzy set notation. Further, they are evaluated using Fuzzy rules to obtain overall Criticality Index. Contingencies are ranked based on decreasing order of Criticality Index and then provide the comparison of ranking obtained with Fast Voltage Stability Index (FVSI) method.

Fuzzy Logic Based Power System Contingency Ranking

Voltage stability is a major concern in planning and operations of power systems. It is well known that voltage instability and collapse have led to major system failures. Modern transmission networks are more heavily loaded than ever before to meet the growing demand. One of the major consequences resulted from such a stressed system is voltage collapse or instability. This paper presents maximum loadability identification of a load bus in a power transmission network. In this study, Fast Voltage Stability Index (FVSI) is utilized as the indicator of the maximum loadability termed as Qmax. In this technique, reactive power loading will be increased gradually at particular load bus until the FVSI reaches close to unity. Therefore, a critical value of FVSI was set as the maximum loadability point. This value ensures the system from entering voltage-collapse region. The main purpose in the maximum loadability assessment is to plan for the maximum allowable load value to avoid voltage collapse; which is important in power system planning risk assessment. The most important task in security analysis is the problem of identifying the critical contingencies from a large list of credible contingencies and ranks them according to their severity. The condition of voltage stability in a power system can be characterized by the use of voltage stability indices. This paper presents fuzzy approach for ranking the contingencies using composite-index based on parallel operated fuzzy inference engine. The Line Flow index (L.F) and bus Voltage Magnitude (VM) of the load buses are expressed in fuzzy set notation. Further, they are evaluated using Fuzzy rules to obtain overall Criticality Index. Contingencies are ranked based on decreasing order of Criticality Index and then provides the comparison of ranking obtained with FVSI method.

Using 80001 to Manage Medical Devices on the IT Network

Healthcare technology today is considerably different than it was 20 to 40 years ago. Yet, much of what is done by healthcare technology managers in support of medical technology has not changed. The tools and procedures still used by most clinical engineering services have evolved little to address some of the unique challenges posed by new healthcare technologies that are at once more pervasive, more complex and more susceptible to failures that may have catastrophic consequences for patients and healthcare operations. Just how has the healthcare technology landscape changed?

Voltage Stability Study of IEEE 14 Bus System Using MATLAB simulation

The paper discusses voltage Stability as a major concern in planning and operations of power systems. It is well known that voltage instability and collapse have led to major system failures: with the development of power markets, moreand more electric utilities are facing voltage stability –imposed limits. The problem of voltage stability may be explained as inability of the power system itself. It is understood as a reactive power problem and is also a dynamic phenomenon. The objective of this work is to developed a fast and simple method which can be applied in the power system online, to estimate the voltage stability margin of the power system.

Economic costs of firm‐level information infrastructure failures

PurposeThis paper presents a method for estimating the macro‐economic cost of a firm‐level information system disruption within a supply chain.Design/methodology/approachThe authors combine field study estimates with a Leontief‐based input‐output model to estimate the macro‐economic costs of a targeted internet outage that disrupts the supply chain.FindingsThe authors find that supply chain vulnerability or resiliency to cyber disruptions is not necessarily dependent on the types of technology employed, but rather how the technology is used to enable supply chain processes and the type of attack experienced. The authors find that some supply chains like oil and gas could be significantly impacted by certain cyber disruptions. However, similar to other causes of supply chain disruptions such as labor disputes or natural disasters, the authors find that firms can be very resilient to cyber disruptions.Research limitations/implicationsThe validity of the approach is limited by the accuracy of parameters gathered through field studies and the resolution of government economic data.Practical implicationsManagers should examine how information technology is used to enable their supply chain processes and develop capabilities that provide resilience to failures. Lean supply chains that focus on minimizing inventory may be more vulnerable to major information system failures unless they take special steps to build resilience.Originality/valueThis paper provides a new approach to estimating economic vulnerability due to supply chain information failures.

Bulk liquid oxygen supply failure.

WE report an oxygen supply tank failure at our institution that occurred during the morning of a busy operating room schedule when medical center oxygen use was maximal.

Accountability and responsibility: clinical governance beyond the institution

The principal focus of clinical governance is intended to be at the level of the statutory organisation such as a Health Authority, Primary Care Trust or NHS Trust. This paper suggests that there are at least three levels (micro, macro and meta) at which clinical governance must operate if the original vision of flourishing excellence is to be fulfilled. These do not, regrettably, fit comfortably into the current organisational arrangements for the NHS in England and some cut across any traditional understanding of accountability relationships. With clinical governance at a relatively early stage of its development in many hospitals, and little better than vestigial in most Primary Care and Ambulance Trusts, it may be premature to take on such complex and challenging issues. However, the types of scenario described are typical of those that might create the next major system failure if they remain beyond the scope of clinical governance.

Independent validation of APACHE II severity of illness score for predicting mortality in patients with breast cancer admitted to the intensive care unit.

To determine the validity and predictive accuracy of the Acute Physiology and Chronic Health Evaluation (APACHE II) scoring system for severity of illness by comparing the actual hospital mortality with the predicted mortality for patients with breast cancer admitted to the intensive care unit (ICU). APACHE II scores were calculated based on retrospective evaluation of the medical records of 52 patients with breast cancer who received ICU care. The relationships between hospital mortality and APACHE II scores, number of sites of metastatic disease, duration of metastatic disease, number of chemotherapeutic regimens given for metastatic disease, presence of neutropenia or thrombocytopenia, age, reason for ICU admission, and length of ICU stay were assessed. Twenty-two patients (42%) died during the hospital stay during in which they were admitted to the ICU. Predicted mortality based on a logistic regression model using APACHE II scores was 21 patients (40%). APACHE II specificity was 87%; sensitivity was 54%. There were significant relationships between presence of metastatic disease, number of metastatic sites, reason for ICU admission, and length of ICU stay. Patients with more than two sites of metastatic disease and those with respiratory failure had particularly poor chances of survival. Regression analysis incorporating the number of sites of metastatic disease, reason for ICU admission (whether for a pulmonary or a cardiovascular problem), and APACHE II score suggested that APACHE II could predict hospital survival. This retrospective study showed that APACHE II scores were associated with hospital mortality in patients with breast cancer who were admitted to ICU. The number of metastatic sites and the type of major organ system failure were also associated with outcome. Regression analysis suggested that APACHE II scores were independently associated with survival outcome.

Recurrent hyperventilation tetany due to mild asthma

There is uncertainty about the boundaries, definition and diagnosis of disorders related to hyperventilation (1,2). The original definition of the hyperventilation syndrome implied an association between anxiety and hyperventilation (3), but more recent reports suggest that severe symptomatic hyperventilation can occur in the absence of reported anxiety and psychiatric morbidity (4-6). The interrelationship of anxiety, panic and hyperventilation is complex and controversial (7). Hyperventilation implies excessive respiratory drive and hypocapnia. Many organic disorders are associated with hypocapnia (2) which can occur in the early stages of most respiratory diseases, left ventricular failure, pulmonary embolus, chronic pain, most major system failures, and drug overdoses (e.g. aspirin). Hypocapnia also occurs with physiological states such as prolonged talking, pyrexia, pregnancy and in the second half of the menstrual cycle. Hyperventilation can cause the sudden onset of alarming symptoms due to both increased chest wall movement, and vasoconstriction and nervous hyperirritability induced by hypocapnic alkalosis. Hypocapnia is only of clinical relevance if it is associated with symptoms, and it has been suggested that hyperventilation only becomes self perpetuating and ultimately chronic if the patient misattributes these symptoms to serious disease, especially if the physician fails to recognise the true nature of the complaints (8). Such misattribution may prove to be the key to the etiology of the hyperventilation syndrome. Mild and moderate asthma can cause profound hypocapnia (9) and clinical experience suggests that asthma is often one of a number of factors contributing to the etiology of recurrent symptomatic hyperventilation (10). However, there is no evidence that an asthmatic, in the absence of other factors, can present with symptoms of hypocapnia sufficiently severe to overshadow the symptoms of airflow obstruction and

Acute renal support in the ITU

With mortality in excess of 90%, acute renal failure was largely untreatable until 1944 when Willem Kolff successfully dialysed a patient with sulphonamide induced acute renal failure. 1 Since that initial treatment a plethora of renal replacement devices and procedures have reduced the current mortality of uncomplicated acute renal failure to around 8%. 2 The mortality of acute renal failure in the ITU patient, however, remains high, increasing with the number of other failed organs; often assumed to be 100% with two other major organ system failures. 2

Dynamic contrast enhanced computed tomography: a precise technique for identifying and localising pancreatic necrosis.

To evaluate dynamic contrast enhanced computed tomography for detecting and localising pancreatic necrosis in acute pancreatitis. Prospective evaluation with blind reporting of scans. Single teaching hospital. 60 Consecutive patients with acute pancreatitis suspected to have pancreatic necrosis because of major organ system failure (13); slow recovery five to seven days after admission with raised scores on the acute physiological and chronic health evaluation (APACHE-II) system (27); or findings on previous ultrasonography or computed tomography (20). Pancreatic necrosis proved histologically--that is, greater than 30 g necrotic tissue debrided at laparotomy (for life threatening sepsis or peritonitis) or necropsy. Dynamic computed tomography correctly localised pancreatic necrosis in 11 patients (confirmed at laparotomy in nine and at necropsy in two). Of nine patients with low enhancement of peripancreatic tissues alone, eight recovered after conservative management; necropsy confirmed viable pancreas and necrosis of peripancreatic fat in one patient. Of 40 patients with normal contrast enhancement, none required laparotomy to debride pancreatic necrosis. Dynamic contrast enhanced computed tomography seems to be a safe and accurate method of identifying and localising pancreatic and peripancreatic necrosis, which cannot be predicted accurately by conventional imaging techniques.

Identifying ICU Patients Who Would Not Benefit from Total Parenteral Nutrition

This study attempted to improve patient selection for total parenteral nutrition (TPN) by identifying ICU patients whose prognoses were so hopeless that they would not or would no longer benefit from TPN. Computerized trend analysis of daily Apache II scores, corrected for the presence, number, and duration of major organ system failures was used to predict individual hospital outcome among 50 intensive care unit patients treated with TPN. Thirteen of the 18 deaths were correctly predicted without any false predictions. During the study, the results of predictions were not used to influence clinical decision making. If TPN was withheld in the five patients predicted to die before starting TPN, or withdrawn in the eight patients when they were predicted to die, $28,350 or 11.5% of the cost of TPN during the study period would have been saved. This hypothetical study shows that elimination of inappropriate treatment of patients with hopeless prognosis with the aim of avoiding the prolongation of the process of dying and unnecessary suffering is a compassionate patient-selection strategy that can result in major savings in healthcare resources.