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Prognostic impact of bronchoalveolar lavage galactomannan and Aspergillus culture results on survival in COVID-19 ICU patients: a post-hoc analysis from the European Confederation of Medical Mycology (ECMM) COVID-19-associated pulmonary aspergillosis (CAPA) Study
No full textCritically ill patients with coronavirus disease 2019 (COVID-19) may develop COVID-19-associated pulmonary aspergillosis (CAPA), that impact their chances of survival. Whether positive bronchoalveolar lavage fluid (BALF) mycological tests can be used as a survival proxy remains unknown. We conducted a post-hoc analysis of a previous multicenter, multinational observational study with the aim of assessing the differential prognostic impact of BALF mycological tests, namely positive (≥ 1.0 optical density index) BALF galactomannan (GM) and positive BALF Aspergillus culture alone or in combination in critically ill patients with COVID-19. Of the 592 patients critically ill patients with COVID-19 enrolled in the main study, 218 were included in this post-hoc analysis as they had both test results available. CAPA was diagnosed in 56/218 patients (26%). Most cases were probable CAPA (51/56, 91%) and fewer were proven CAPA (5/56, 9%). In the final multivariable model adjusted for between-center heterogeneity, an independent association with 90-day mortality was observed for the combination of positive BALF GM and positive BALF Aspergillus culture in comparison with both tests negative (hazard ratio 2.53, 95% CI 1.28-5.02, p = 0.008). The other independent predictors of 90-day mortality were increasing age and active malignant disease. In conclusion, the combination of positive BALF GM and positive BALF Aspergillus culture was associated with increased 90-day mortality in critically ill patients with COVID-19. Additional study is needed to explore the possible prognostic value of other BALF markers.Key words: CAPA; GM; biomarker; galactomannan; Aspergillus; COVID-19; BALF.<br/
ADBSat: Methodology of a novel panel method tool for aerodynamic analysis of satellites
No full textADBSat is a novel software that determines the aerodynamic properties of any body in free-molecular flow. Its main advantage is the fast approximation of the aerodynamics of spacecraft in the lower end of the low-Earth orbit altitude range. It is a novel implementation of a panel method, where the body is represented as a set of fundamental elements and the sum of their individual aerodynamic properties makes up the properties of the whole. ADBSat’s approach treats the shape as a set of flat triangular plates. These are read from a CAD geometry file in the Wavefront format, which can be created with most common CAD programs. A choice of gas-surface interaction models is available to represent the physics of free-molecular flow under different conditions. Its modular design means that other models can be easily and quickly implemented. It also benefits from a new shading algorithm for fast determination of elemental flow exposure. An example case is presented to show the capability and functionality of the program
Investigating Characteristics of Idiopathic Inflammatory Myopathy Flares Using Daily Symptom Data Collected Via a Smartphone App
No full textObjectivesTo use daily data collected via a smartphone app for characterisation of patient-reported and “symptom-based” (using an a priori definition) flares in an adult idiopathic inflammatory myopathy (IIM) cohort.MethodsUK adults with an IIM answered patient-reported outcome measurements (PROMs) daily via a smartphone app during a 91 day study. Daily symptom PROMs addressed global activity, overall pain, myalgia, fatigue, and weakness (0-100 visual analogue scale). Patient-reported flares were recorded via a weekly app question. “Symptom-based” flares were defined via an a priori definition based on increase of daily symptom data from the previous four day mean.ResultsTwenty participants (65% female) participated. Patient-reported flares occurred on a median of five weeks (IQR 3, 7) per participant, out of a possible 13. The mean of each symptom score was significantly higher in flare weeks, compared to non-flare weeks (e.g. mean flare week myalgia score 34/100, vs 21/100 during non-flare week, t-test p-value <0.01).Fatigue accounted for the most symptom-based flares (incidence-rate 23/100 person-days [95% CI 19, 27]), and myalgia the fewest (incidence rate 13/100 person-days [95% CI 11, 16]). Symptom-based flares typically resolved after three days, although fatigue-predominant flares lasted two days. The majority (69%) of patient-reported flare weeks coincided with at least one symptom-based flare.ConclusionsIIM flares are frequent and associated with increased symptom scores. This study has demonstrated the ability to identify and characterise patient-reported and symptom-based flares (based on an a priori definition), using daily app-collected data
A System Identification Procedure Using Compressive Sensing
No full textThe conventional system identification, which is a branch of machine learning, takes advantages of the whole sampling data to identify the system. To identify a system with less sampling density, compressive sensing is applied on system identification, which randomly extracts the sampling data from the system response. Hence a novel identification procedure is proposed using compressive sensing techniques. Then a second order system is selected as the system to be identified using such identification procedure. The identification performances of estimated systems are investigated from the scenario randomly extracting 10% of total sampling data to the scenario using 90% of total sampling data. Each scenario consists of three noise cases with different levels of SNRs to test the robustness of the signal recovery algorithms of compressive sensing. The results show that the system identification using compressive sensing has are relatively high identification performance and is robust to noise when using 30% or more of total sampling data
Did the Siebel Systems Case Limit the SEC's Ability to Enforce Regulation Fair Disclosure?
No full textWe examine whether a shock to the enforceability of Regulation Fair Disclosure (Reg FD) limited its ability to restrict the flow of private information between managers and investors. While prior work provides evidence that Reg FD reduced managers’ selective disclosure of material information immediately following its promulgation, we posit that private information flows returned as a result of the SEC’s public enforcement failure in SEC v. Siebel Systems, Inc. Using multiple settings, we find consistent evidence suggesting that Siebel changed the cost-benefit tradeoff for Reg FD compliance and effectively reversed the initial effects of the regulation. We also find that Siebel disrupted the equilibrium of selective disclosure activity, resulting in an unleveling effect among investors with respect to private information advantages. Finally, we find that Siebel also had real effects by altering managers’ capital structure decisions. Our findings run counter to the prevailing “mosaic theory” and gradual learning explanations for private information advantages in the extended post-Reg FD period and highlight the importance of enforcement in achieving intended regulatory outcomes
Clinical outcome and underlying genetic cause of functional terminal complement pathway deficiencies in a multi-center UK cohort
No full textBackground: Terminal complement pathway deficiencies often present with severe and recurrent infections. There is a lack of good quality data on these rare conditions. This study investigated the clinical outcome and genetic variation in a large UK multi-center cohort with primary and secondary terminal complement deficiencies. Methods: Clinicians from seven UK centers provided anonymised demographic, clinical and laboratory data on patients with terminal complement deficiencies, which were collated and analysed. Results: Forty patients, median age 19 (range 3 62) years, were identified with terminal complement deficiencies. Ten (62%) of 16 patients with low serum C5 concentrations had underlying pathogenic CFH or CFI gene variants. Two-thirds were from consanguineous Asian families and 80% had an affected family member. The median age of first infection was nine years. Forty-three percent suffered meningococcal serotype B, and 43% serotype Y infections. Nine (22%) were treated in intensive care for meningococcal septicemia. Two patients had died, one from intercurrent COVID-19. Twenty-one (52%) were asymptomatic and diagnosed based on family history. All but one patient had received booster meningococcal vaccines and 70% were taking prophylactic antibiotics. Discussion: The genetic etiology and clinical course of patients with primary and secondary terminal complement deficiency is variable. Patients with low antigenic C5 concentrations require genetic testing, as the low level may reflect consumption secondary to regulatory defects in the pathway. Screening of siblings is important. Only half of patients develop septicemia, but all should have a clear management plan. Key words: terminal complement pathway; Factor H; Factor I; meningococcal infection; genetic
ESBMC-Solidity: An SMT-Based Model Checker for Solidity Smart Contracts
No full textSmart contracts written in Solidity are programs used in blockchain networks, such as Etherium, for performing transactions. However, as with any piece of software, they are prone to errors and may present vulnerabilities, which malicious attackers could then use. This paper proposes a solidity frontend for the efficient SMT-based context-bounded model checker (ESBMC), named ESBMC-Solidity, which provides a way of verifying such contracts with its framework. A benchmark suite with vulnerable smart contracts was also developed for evaluation and comparison with other verification tools. The experiments performed here showed that ESBMC-Solidity detected all vulnerabilities, was the fastest tool, and provided a counterexample for each benchmark. A demonstration is available at https://youtu.be/3UH8_1QAVN0
Wit4Java: A Violation-Witness Validator for Java Verifiers
No full textWe describe and evaluate a violation-witness validator for Java verifiers called Wit4Java. It takes a Java program with a safety property and the respective violation-witness output by a Java verifier to generate a new Java program whose execution deterministically violates the property. We extract the value of the program variables from the counterexample represented by the violation witness and feed this information back into the original program. In addition, we have two implementations for instantiating source programs by injecting counterexamples. Experimental results show that Wit4Java can correctly validate the violation-witnesses produced by JBMC and GDart in a few seconds
Effect of Clustering in Federated Learning on Non-IID Electricity Consumption Prediction
No full textWhen applied to short-term energy consumption forecasting, the federated learning framework allows for the creation of a predictive model without sharing raw data. There is a limit to the accuracy achieved by standard federated learning due to the heterogeneity of the individual clients’ data, especially in the case of electricity data, where prediction of peak demand is a challenge. A set of clustering techniques has been explored in the literature to improve prediction quality while maintaining user privacy. These studies have mainly been conducted using sets of clients with similar attributes that may not reflect realworld consumer diversity. This paper explores, implements and compares these clustering techniques for privacy-preserving load forecasting on a representative electricity consumption dataset. The experimental results demonstrate the effects of electricity consumption heterogeneity on federated forecasting and a nonrepresentative sample’s impact on load forecasting
Palliative radiotherapy in cancers of female genital tract: Outcomes and prognostic factors
No full textBackground and purposeMetastatic and incurable cancers of the gynaecological tract (FGTC) represent a major global health burden. Systemic treatment has modest efficacy and radiotherapy is often used for local symptoms. This study combines experience from two large UK centres in palliative radiotherapy for gynaecological cancers. Materials and methodsPooled data from two major centres was analysed. Advanced FGTC patients who received at least one fraction of palliative radiotherapy to the pelvis between 2013 to 2018 were included. Data collected included demographic and tumour details, radiotherapy dose fractionation and details of previous and subsequent treatment. Response was defined in terms of toxicity, symptomatic response and survival. Comorbidities were recorded using a modified ACE 27 score which is adjusted for the presence of uncontrolled FGTC in all the patients.ResultsA total of 184 patients were included for treatment response and toxicity; survival data was available for 165 patients. Subjective response in pre-radiotherapy symptoms was documented in 80.4%. Grade 3 or worse gastrointestinal, urinary and other(vomiting, fatigue, pain ) toxicity incidence was 2.2%, 3.8%, and 2.7% respectively. No statistically significant correlation between the prescribed EQD210 and symptom control or toxicity was seen. 1 year overall survival was 25.1% (median 5.9 months). Absent distant metastases, completion of the intended course of radiotherapy, response to radiotherapy, and receipt of further lines of treatment were independent prognostic factors. Conclusion.Palliative radiotherapy is effective for symptoms of advanced FGTC with low toxicity. The absence of a dose response argues for short low dose palliative radiotherapy schedules to be used.<br/