Can Applications Recover from fsync Failures?

We analyze how file systems and modern data-intensive applications react to fsync failures. First, we characterize how three Linux file systems (ext4, XFS, Btrfs) behave in the presence of failures. We find commonalities across file systems (pages are always marked clean, certain block writes always lead to unavailability) as well as differences (page content and failure reporting is varied). Next, we study how five widely used applications (PostgreSQL, LMDB, LevelDB, SQLite, Redis) handle fsync failures. Our findings show that although applications use many failure-handling strategies, none are sufficient: fsync failures can cause catastrophic outcomes such as data loss and corruption. Our findings have strong implications for the design of file systems and applications that intend to provide strong durability guarantees.

Medical device error and failure reporting: Learning from the car industry

Background Improving the design of technology relies in part, on the reporting of performance failures in existing devices. Healthcare has low levels of formal reporting of performance and failure of medical equipment. This paper examines methods of reporting in the car industry and healthcare and aims to understand differences and identify opportunities for improvement within healthcare. Methods A literature search was carried out in Pubmed, Medline, Embase, Engineering Village, Scopus. NHS England and MHRA publications and guidelines were also reviewed. Focus was placed on the current system of reporting in both industries, known degree of patient harm, initiating factors, barriers, quality and methods of incident investigation and their validity. The findings were used to compare error reporting system in the two industries. Results Derivation of healthcare incident data from different sources means the full extent of patient harm is not known. For example, in 2012 there were 13,549 and 38,395 incidents reported by MHRA and NRLS (National Reporting and Learning System) respectively leading to uncertainties on the extent of the problem. The car industry emphasises the role of reporting source in ensuring data quality. Utilising some aspects of this approach might benefit healthcare reporting. These include a specific reporting system that stresses the importance of organisational learning in improving safety and recognises the limitations of root cause analysis. Conclusions Learning from reporting systems within the car industry may help the healthcare sector improve its own reporting, aiding healthcare performance.

Mental Fatigue Reduces Training Volume in Resistance Exercise: A Cross-Over and Randomized Study

The present study aimed to determine the effect of mental fatigue (MF) on total training volume (TTV; number of repetitions x number of sets x load) and on ratings of perceived exertion (RPE; Borg, 1982 ) in the half-back squat exercise (HBSE). Nine male subjects ( M age = 22.6 years, SD = 2.3; M height = 172.3 cm , SD = 6.8; M weight = 76.2 kg , SD = 9.8; M years of resistance training experience = 4.1, SD = 2.3 years) recruited from a university population were study participants in this participant-blind cross-over and randomized study. Participants underwent either the Stroop task – a highly demanding cognitive task (CT) – or a control condition (CON) in which they viewed a documentary exhibition for 30 minutes. Perception of MF and motivation were assessed after treatments using a visual analog scale of 100 mm. Participants then engaged in a countermovement jump (CMJ) test and three sets of HBSE until they reached momentary concentric failure, reporting RPE at the end of each exercise set. Following the CT, participants showed a significantly increased self-perception of MF in relation to the CON condition ( p = 0.01; d = 1.2), but this did not affect their motivation to engage in subsequent tests ( p = 0.99; d = 0.006). Neither the CMJ performances nor the RPE were statistically different between CT and CON conditions ( p = 0.33; d = 0.09 and p = 0.20 ; η2 = 0.20, respectively). TTV was significantly lower in the CT relative to the CON experimental condition (Δ = −15.8%; p = 0.04; η2 = 0.48). Prolonged involvement in a CT was associated with reduced volume on a resistance exercise, though this effect was not associated with changes in CMJ performance or motivation to exercise.

Disproportionality Analysis of Safety with Nafcillin and Oxacillin with the FDA Adverse Event Reporting System (FAERS)

ABSTRACT Antistaphylococcal penicillins such as nafcillin and oxacillin are among the first choices of treatment for severe invasive methicillin-susceptible Staphylococcus aureus (MSSA) infections, although there has been limited safety evaluations between individual agents. Using the FDA Adverse Event Reports System (FAERS), oxacillin was observed to have a lower proportion of reports of acute renal failure (reporting odds ratio [ROR], 5.3 [95% confidence interval {CI}, 3.1 to 9.3] versus 21.3 [95% CI, 15.8 to 28.6], respectively) and hypokalemia (ROR, 0.7 [95% CI, 0.1 to 4.8] versus 11.4 [95% CI, 7.1 to 18.3], respectively) than nafcillin.

Risk Management in Clinical Laboratory: from Theory to Practice

Clinical laboratory tests ensure approximately 70% of the medical decisions, so that the time until the release of the results and its accuracy are critical for the diagnosis and the efficiency of the treatment [1]. Risk management involves both the anticipation of what could happen erroneous and the assessment of errors’ frequency as well as the consequences or the severity of the effects caused by it, and finally to decide what can be done in order to reduce the risk to an acceptable clinical level. For this reason, organizations should not see the risk management as a compliance issue, but as an integral part of the decision-making process. EP23-A is a guideline of CLSI that introduces the risk management principles in the clinical laboratory and encourages the laboratories to develop plans of risk management which are addressed to the risks of each laboratory. EP18-A2 proposes 2 techniques for identifying and controlling the errors in the laboratory: FMEA (Failure Mode and Effects Analysis) and FRACAS (Failure Reporting, Analysis and Corrective Action System). The European Committee of Experts and Management of Safety and Quality in Health Care proposed to use the quality indicators to identify the critical stages of each process, thus being possible to assess continuously the medical processes with the aim of identifying the errors when they occur. This review summarizes the principles of the risk management in the clinical laboratory, thus it can achieve its aims to report valid, accurate and reliable test results