Synergizing specification miners through model fissions and fusions

Abstract—Software systems are often developed and released without formal specifications. For those systems that are formally specified, developers have to continuously maintain and update the specifications or have them fall out of date. To deal with the absence of formal specifications, researchers have proposed tech-niques to infer the missing specifications of an implementation in a variety of forms, such as finite state automaton (FSA). Despite the progress in this area, the efficacy of the proposed specification miners needs to improve if these miners are to be adopted. We propose SpecForge, a new specification mining approach that synergizes many existing specification miners. SpecForge decomposes FSAs that are inferred by existing miners into simple constraints, through a process we refer to as model fission. It then filters the outlier constraints and fuses the constraints back together into a single FSA (i.e., model fusion). We have evaluated SpecForge on execution traces of 10 programs, which includes 5 programs from DaCapo benchmark, to infer behavioral models of 13 library classes. Our results show that SpecForge achieves an average precision, recall and F-measure of 90.57%, 54.58%, and 64.21 % respectively. SpecForge outperforms the best performing baseline by 13.75 % in terms of F-measure

Depolarization Property of Cirrus Clouds Over Hanoi

Cirrus cloud is one of the most commonly occurring cloud types globally. The clouds are found mainly to consist of floating ice crystals, which can reflect strongly incoming radiation. Lidar measurements provide an opportunity to study the microphysics and ice compositions of cirrus clouds. We have developed a polarization lidar system to measure the depolarization characteristics of the lower atmosphere over Hanoi. From our measurements of cirrus clouds over the period from 2010 to 2012, the depolarization ratio of cirrus clouds is found to be very high ranging from 20% up to 80{\%}, indicating large fraction of backscattering from ice crystals. We find a trend of increasing depolarization ratio with height and decreasing temperature. We also compare our lidar measurements with other results obtained by lidar technique in other regions of the world

Simultaneously induced mutations in eIF4E genes by CRISPR/Cas9 enhance PVY resistance in tobacco

Tobacco is an important commercial crop and a rich source of alkaloids for pharmaceutical and agricultural applications. However, its yield can be reduced by up to 70% due to virus infections, especially by a potyvirus Potato virus Y (PVY). The replication of PVY relies on host factors, and eukaryotic translation initiation factor 4Es (eIF4Es) have already been identified as recessive resistance genes against potyviruses in many plant species. To investigate the molecular basis of PVY resistance in the widely cultivated allotetraploid tobacco variety K326, we developed a dual guide RNA CRISPR/Cas9 system for combinatorial gene editing of two clades, eIF4E1 (eIF4E1-S and eIF4E1-T) and eIF4E2 (eIF4E2-S and eIF4E2-T) in the eIF4E gene family comprising six members in tobacco. We screened for CRISPR/Cas9-induced mutations by heteroduplex analysis and Sanger sequencing, and monitored PVY(O) accumulation in virus challenged regenerated plants by DAS-ELISA both in T0 and T1 generations. We found that all T0 lines carrying targeted mutations in the eIF4E1-S gene displayed enhanced resistance to PVY(O) confirming previous reports. More importantly, our combinatorial approach revealed that eIF4E1-S is necessary but not sufficient for complete PVY resistance. Only the quadruple mutants harboring loss-of-function mutations in eIF4E1-S, eIF4E1-T, eIF4E2-S and eIF4E2-T showed heritable high-level resistance to PVY(O) in tobacco. Our work highlights the importance of understanding host factor redundancy in virus replication and provides a roadmap to generate virus resistance by combinatorial CRISPR/Cas9-mediated editing in non-model crop plants with complex genomes

Awareness and preparedness of healthcare workers against the first wave of the COVID-19 pandemic: A cross-sectional survey across 57 countries.

BACKGROUND: Since the COVID-19 pandemic began, there have been concerns related to the preparedness of healthcare workers (HCWs). This study aimed to describe the level of awareness and preparedness of hospital HCWs at the time of the first wave. METHODS: This multinational, multicenter, cross-sectional survey was conducted among hospital HCWs from February to May 2020. We used a hierarchical logistic regression multivariate analysis to adjust the influence of variables based on awareness and preparedness. We then used association rule mining to identify relationships between HCW confidence in handling suspected COVID-19 patients and prior COVID-19 case-management training. RESULTS: We surveyed 24,653 HCWs from 371 hospitals across 57 countries and received 17,302 responses from 70.2% HCWs overall. The median COVID-19 preparedness score was 11.0 (interquartile range [IQR] = 6.0-14.0) and the median awareness score was 29.6 (IQR = 26.6-32.6). HCWs at COVID-19 designated facilities with previous outbreak experience, or HCWs who were trained for dealing with the SARS-CoV-2 outbreak, had significantly higher levels of preparedness and awareness (p<0.001). Association rule mining suggests that nurses and doctors who had a 'great-extent-of-confidence' in handling suspected COVID-19 patients had participated in COVID-19 training courses. Male participants (mean difference = 0.34; 95% CI = 0.22, 0.46; p<0.001) and nurses (mean difference = 0.67; 95% CI = 0.53, 0.81; p<0.001) had higher preparedness scores compared to women participants and doctors. INTERPRETATION: There was an unsurprising high level of awareness and preparedness among HCWs who participated in COVID-19 training courses. However, disparity existed along the lines of gender and type of HCW. It is unknown whether the difference in COVID-19 preparedness that we detected early in the pandemic may have translated into disproportionate SARS-CoV-2 burden of disease by gender or HCW type

Safety and efficacy of fluoxetine on functional outcome after acute stroke (AFFINITY): a randomised, double-blind, placebo-controlled trial

Background Trials of fluoxetine for recovery after stroke report conflicting results. The Assessment oF FluoxetINe In sTroke recoverY (AFFINITY) trial aimed to show if daily oral fluoxetine for 6 months after stroke improves functional outcome in an ethnically diverse population. Methods AFFINITY was a randomised, parallel-group, double-blind, placebo-controlled trial done in 43 hospital stroke units in Australia (n=29), New Zealand (four), and Vietnam (ten). Eligible patients were adults (aged ≥18 years) with a clinical diagnosis of acute stroke in the previous 2–15 days, brain imaging consistent with ischaemic or haemorrhagic stroke, and a persisting neurological deficit that produced a modified Rankin Scale (mRS) score of 1 or more. Patients were randomly assigned 1:1 via a web-based system using a minimisation algorithm to once daily, oral fluoxetine 20 mg capsules or matching placebo for 6 months. Patients, carers, investigators, and outcome assessors were masked to the treatment allocation. The primary outcome was functional status, measured by the mRS, at 6 months. The primary analysis was an ordinal logistic regression of the mRS at 6 months, adjusted for minimisation variables. Primary and safety analyses were done according to the patient's treatment allocation. The trial is registered with the Australian New Zealand Clinical Trials Registry, ACTRN12611000774921. Findings Between Jan 11, 2013, and June 30, 2019, 1280 patients were recruited in Australia (n=532), New Zealand (n=42), and Vietnam (n=706), of whom 642 were randomly assigned to fluoxetine and 638 were randomly assigned to placebo. Mean duration of trial treatment was 167 days (SD 48·1). At 6 months, mRS data were available in 624 (97%) patients in the fluoxetine group and 632 (99%) in the placebo group. The distribution of mRS categories was similar in the fluoxetine and placebo groups (adjusted common odds ratio 0·94, 95% CI 0·76–1·15; p=0·53). Compared with patients in the placebo group, patients in the fluoxetine group had more falls (20 [3%] vs seven [1%]; p=0·018), bone fractures (19 [3%] vs six [1%]; p=0·014), and epileptic seizures (ten [2%] vs two [<1%]; p=0·038) at 6 months. Interpretation Oral fluoxetine 20 mg daily for 6 months after acute stroke did not improve functional outcome and increased the risk of falls, bone fractures, and epileptic seizures. These results do not support the use of fluoxetine to improve functional outcome after stroke