8,910 research outputs found
Faster Mutation Analysis via Equivalence Modulo States
Mutation analysis has many applications, such as asserting the quality of
test suites and localizing faults. One important bottleneck of mutation
analysis is scalability. The latest work explores the possibility of reducing
the redundant execution via split-stream execution. However, split-stream
execution is only able to remove redundant execution before the first mutated
statement.
In this paper we try to also reduce some of the redundant execution after the
execution of the first mutated statement. We observe that, although many
mutated statements are not equivalent, the execution result of those mutated
statements may still be equivalent to the result of the original statement. In
other words, the statements are equivalent modulo the current state.
In this paper we propose a fast mutation analysis approach, AccMut. AccMut
automatically detects the equivalence modulo states among a statement and its
mutations, then groups the statements into equivalence classes modulo states,
and uses only one process to represent each class. In this way, we can
significantly reduce the number of split processes. Our experiments show that
our approach can further accelerate mutation analysis on top of split-stream
execution with a speedup of 2.56x on average.Comment: Submitted to conferenc
M3-AUDIODEC: Multi-channel multi-speaker multi-spatial audio codec
We introduce M3-AUDIODEC, an innovative neural spatial audio codec designed
for efficient compression of multi-channel (binaural) speech in both single and
multi-speaker scenarios, while retaining the spatial location information of
each speaker. This model boasts versatility, allowing configuration and
training tailored to a predetermined set of multi-channel, multi-speaker, and
multi-spatial overlapping speech conditions. Key contributions are as follows:
1) Previous neural codecs are extended from single to multi-channel audios. 2)
The ability of our proposed model to compress and decode for overlapping
speech. 3) A groundbreaking architecture that compresses speech content and
spatial cues separately, ensuring the preservation of each speaker's spatial
context after decoding. 4) M3-AUDIODEC's proficiency in reducing the bandwidth
for compressing two-channel speech by 48% when compared to individual binaural
channel compression. Impressively, at a 12.6 kbps operation, it outperforms
Opus at 24 kbps and AUDIODEC at 24 kbps by 37% and 52%, respectively. In our
assessment, we employed speech enhancement and room acoustic metrics to
ascertain the accuracy of clean speech and spatial cue estimates from
M3-AUDIODEC. Audio demonstrations and source code are available online at
https://github.com/anton-jeran/MULTI-AUDIODEC .Comment: More results and source code are available at
https://anton-jeran.github.io/MAD
Clinical relevance of miR-423-5p levels in chronic obstructive pulmonary disease patients
Objective: This study aimed to examine changes in miRNAs expression profile of COPD patients.
Methods: Thirty-six COPD patients as well as thirty-three healthy volunteers were recruited. Total RNAs were collected from the plasma of each participant. The differentially expressed miRNAs in COPD were screened from the GEO database. RT-qPCR was carried out to detect miRNA expression.
Results: In total, 9 out of 55 miRNAs were expressed differentially in COPD patients. Confirmed by RT-qPCR validation, 6 miRNAs increased while 3 miRNAs decreased. Further analysis of miR-423-5p, which has not been reported in COPD, showed that AUC for the diagnosis of COPD was 0.9651, and miR-423-5p levels was inversely correlated with the duration of smoking.
Conclusion: The present study demonstrates that miR-423-5p is a potential marker for identifying COPD patients
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