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

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

The DUNDRUM Quartet: validation of structured professional judgement instruments DUNDRUM-3 assessment of programme completion and DUNDRUM-4 assessment of recovery in forensic mental health services

<p>Abstract</p> <p>Background</p> <p>Moving a forensic mental health patient from one level of therapeutic security to a lower level or to the community is influenced by more than risk assessment and risk management. We set out to construct and validate structured professional judgement instruments for consistency and transparency in decision making</p> <p>Methods</p> <p>Two instruments were developed, the seven-item DUNDRUM-3 programme completion instrument and the six item DUNDRUM-4 recovery instrument. These were assessed for all 95 forensic patients at Ireland's only forensic mental health hospital.</p> <p>Results</p> <p>The two instruments had good internal consistency (Cronbach's alpha 0.911 and 0.887). Scores distinguished those allowed no leave or accompanied leave from those with unaccompanied leave (ANOVA F = 38.1 and 50.3 respectively, p < 0.001). Scores also distinguished those in acute/high security units from those in medium or in low secure/pre-discharge units. Each individual item distinguished these levels of need significantly. The DUNDRUM-3 and DUNDRUM-4 correlated moderately with measures of dynamic risk and with the CANFOR staff rated unmet need (Spearman r = 0.5, p < 0.001).</p> <p>Conclusions</p> <p>The DUNDRUM-3 programme completion items distinguished significantly between levels of therapeutic security while the DUNDRUM-4 recovery items consistently distinguished those given unaccompanied leave outside the hospital and those in the lowest levels of therapeutic security. This data forms the basis for a prospective study of outcomes now underway.</p