TarTar: A Timed Automata Repair Tool

We present TarTar, an automatic repair analysis tool that, given a timed diagnostic trace (TDT) obtained during the model checking of a timed automaton model, suggests possible syntactic repairs of the analyzed model. The suggested repairs include modified values for clock bounds in location invariants and transition guards, adding or removing clock resets, etc. The proposed repairs are guaranteed to eliminate executability of the given TDT, while preserving the overall functional behavior of the system. We give insights into the design and architecture of TarTar, and show that it can successfully repair 69% of the seeded errors in system models taken from a diverse suite of case studies.Comment: 15 pages, 7 figure

Água-de-coco.

Considerações sobre as variedades e híbridos; Ponto ideal de colheita do fruto verde para consumos in natura e agroindustrial; Identificação do ponto ideal de colheita do fruto verde; Composição química; Uso alimentar da água-de-coco; Uso médico; Uso biotecnológico; Conservação da água-de-coco; Curiosidades sobre a água-de-coco.bitstream/item/91680/1/CPATC-DOC.-24-01.pd

Experimental Determination of the Dissociative Recombination Rate Coefficient for Rotationally Cold CH⁺ and Its Implications for Diffuse Cloud Chemistry

Observations of CH+ are used to trace the physical properties of diffuse clouds, but this requires an accurate understanding of the underlying CH+ chemistry. Until this work, the most uncertain reaction in that chemistry was dissociative recombination (DR) of CH+. Using an electron–ion merged-beams experiment at the Cryogenic Storage Ring, we have determined the DR rate coefficient of the CH+ electronic, vibrational, and rotational ground state applicable for different diffuse cloud conditions. Our results reduce the previously unrecognized order-of-magnitude uncertainty in the CH+ DR rate coefficient to ∼20% and are applicable at all temperatures relevant to diffuse clouds, ranging from quiescent gas to gas locally heated by processes such as shocks and turbulence. Based on a simple chemical network, we find that DR can be an important destruction mechanism at temperatures relevant to quiescent gas. As the temperature increases locally, DR can continue to be important up to temperatures of ∼600 K, if there is also a corresponding increase in the electron fraction of the gas. Our new CH+ DR rate-coefficient data will increase the reliability of future studies of diffuse cloud physical properties via CH+ abundance observations

Pop-up Langmuir probe diagnostic in the water cooled divertor of Wendelstein 7-X

The design, development, and successful implementation of pop-up Langmuir probes installed in the water-cooled divertor of W7-X are described. The probes are controlled by drive coils (actuators) installed behind the divertor plates. These drive coils make use of the magnetic field in W7-X to move the probe tips into and out of the plasma. The drive coils were installed in the vacuum vessel after extensively testing the durability of the coils and analyzing the criteria for safe operation. The probe design is carefully tailored for each of the 36 probe tips in order to be suitable for the different magnetic field configurations used in W7-X and ensure that the probes do not present leading edges to the magnetic flux tubes. An electronic bridge circuit is used for measurement to compensate for the effects of signal propagation time on the long cable lengths used. The diagnostic is integrated with the segment control of W7-X for automated operation and control of the diagnostic. The evaluation of the results from the plasma operation is presented after accounting for appropriate sheath expansion for negative bias voltage on the probes

COVID-19 in cancer patients: clinical characteristics and outcome—an analysis of the LEOSS registry

Introduction Since the early SARS-CoV-2 pandemic, cancer patients have been assumed to be at higher risk for severe COVID-19. Here, we present an analysis of cancer patients from the LEOSS (Lean European Open Survey on SARS-CoV-2 Infected Patients) registry to determine whether cancer patients are at higher risk. Patients and methods We retrospectively analyzed a cohort of 435 cancer patients and 2636 non-cancer patients with confirmed SARS-CoV-2 infection, enrolled between March 16 and August 31, 2020. Data on socio-demographics, comorbidities, cancer-related features and infection course were collected. Age-, sex- and comorbidity-adjusted analysis was performed. Primary endpoint was COVID-19-related mortality. Results In total, 435 cancer patients were included in our analysis. Commonest age category was 76–85 years (36.5%), and 40.5% were female. Solid tumors were seen in 59% and lymphoma and leukemia in 17.5% and 11% of patients. Of these, 54% had an active malignancy, and 22% had recently received anti-cancer treatments. At detection of SARS-CoV-2, the majority (62.5%) presented with mild symptoms. Progression to severe COVID-19 was seen in 55% and ICU admission in 27.5%. COVID-19-related mortality rate was 22.5%. Male sex, advanced age, and active malignancy were associated with higher death rates. Comparing cancer and non-cancer patients, age distribution and comorbidity differed significantly, as did mortality (14% vs 22.5%, p value < 0.001). After adjustments for other risk factors, mortality was comparable. Conclusion Comparing cancer and non-cancer patients, outcome of COVID-19 was comparable after adjusting for age, sex, and comorbidity. However, our results emphasize that cancer patients as a group are at higher risk due to advanced age and pre-existing conditions

Методичні рекомендації з дисципліни „Вступ до педагогічної майстерності” для студентів інституту заочно-дистанційної освіти освітньо-кваліфікаційний рівень „Магістр”

Мета вивчення дисципліни «Вступ до педагогічної майстерності»: сформувати у студентів уявлення професійну майстерність педагога з огляду на умови викладання у вищих та середніх навчальних закладах. Курс спрямовано на ознайомлення зі специфікою навчального і виховного процесу в сучасних закладах освіти, надання студентам систематизованих знань із теоретичних засад педагогічної майстерності та формування практичних умінь і навичок забезпечення ефективності педагогічної взаємодії

A robust genetic algorithm for learning temporal specifications from data

We consider the problem of mining signal temporal logical requirements from a dataset of regular (good) and anomalous (bad) trajectories of a dynamical system. We assume the training set to be labeled by human experts and that we have access only to a limited amount of data, typically noisy. We provide a systematic approach to synthesize both the syntactical structure and the parameters of the temporal logic formula using a two-steps procedure: first, we leverage a novel evolutionary algorithm for learning the structure of the formula; second, we perform the parameter synthesis operating on the statistical emulation of the average robustness for a candidate formula w.r.t. its parameters. We compare our results with our previous work [9] and with a recently proposed decision-tree [8] based method. We present experimental results on two case studies: an anomalous trajectory detection problem of a naval surveillance system and the characterization of an Ineffective Respiratory effort, showing the usefulness of our work

Hospitalized patients dying with SARS-CoV-2 infection—an analysis of patient characteristics and management in ICU and general ward of the LEOSS registry

BACKGROUND: COVID-19 is a severe disease with a high need for intensive care treatment and a high mortality rate in hospitalized patients. The objective of this study was to describe and compare the clinical characteristics and the management of patients dying with SARS-CoV-2 infection in the acute medical and intensive care setting. METHODS: Descriptive analysis of dying patients enrolled in the Lean European Open Survey on SARS-CoV-2 Infected Patients (LEOSS), a non-interventional cohort study, between March 18 and November 18, 2020. Symptoms, comorbidities and management of patients, including palliative care involvement, were compared between general ward and intensive care unit (ICU) by univariate analysis. RESULTS: 580/4310 (13%) SARS-CoV-2 infected patients died. Among 580 patients 67% were treated on ICU and 33% on a general ward. The spectrum of comorbidities and symptoms was broad with more comorbidities (≥ four comorbidities: 52% versus 25%) and a higher age distribution (>65 years: 98% versus 70%) in patients on the general ward. 69% of patients were in an at least complicated phase at diagnosis of the SARS-CoV-2 infection with a higher proportion of patients in a critical phase or dying the day of diagnosis treated on ICU (36% versus 11%). While most patients admitted to ICU came from home (71%), patients treated on the general ward came likewise from home and nursing home (44% respectively) and were more frequently on palliative care before admission (29% versus 7%). A palliative care team was involved in dying patients in 15%. Personal contacts were limited but more often documented in patients treated on ICU (68% versus 47%). CONCLUSION: Patients dying with SARS-CoV-2 infection suffer from high symptom burden and often deteriorate early with a demand for ICU treatment. Therefor a demand for palliative care expertise with early involvement seems to exist