Avoidance and inhibition do not predict nonrespondent bias among patients with inflammatory bowel disease

It has been suggested that participant withdrawal from studies can bias estimates. However, this is only possible when withdrawers and nonwithdrawers differ in an important way. We tested the hypothesis that withdrawers are more likely than nonwithdrawers to be avoidant and negatively affected.

[Ethics, empiricism and uncertainty]

Accidents can lead to difficult boundary situations. Such situations often take place in the emergency units. The medical team thus often and inevitably faces professional uncertainty in their decision-making. It is essential to communicate these uncertainties within the medical team, instead of downplaying or overriding existential hurdles in decision-making. Acknowledging uncertainties might lead to alert and prudent decisions. Thus uncertainty can have ethical value in treatment or withdrawal of treatment. It does not need to be covered in evidence-based arguments, especially as some singular situations of individual tragedies cannot be grasped in terms of evidence-based medicine.

Avoidance of Long Mononucleotide Repeats in Codon Pair Usage

Protein is an essential component for life, and its synthesis is mediated by codons in any organisms on earth. While some codons encode the same amino acid, their usage is often highly biased. There are many factors that can cause the bias, but a potential effect of mononucleotide repeats, which are known to be highly mutable, on codon usage and codon pair preference is largely unknown. In this study we performed a genomic survey on the relationship between mononucleotide repeats and codon pair bias in 53 bacteria, 68 archaea, and 13 eukaryotes. By distinguishing the codon pair bias from the codon usage bias, four general patterns were revealed: strong avoidance of five or six mononucleotide repeats in codon pairs; lower observed/expected (o/e) ratio for codon pairs with C or G repeats (C/G pairs) than that with A or T repeats (A/T pairs); a negative correlation between genomic GC contents and the o/e ratios, particularly for C/G pairs; and avoidance of C/G pairs in highly conserved genes. These results support natural selection against long mononucleotide repeats, which could induce frameshift mutations in coding sequences. The fact that these patterns are found in all kingdoms of life suggests that this is a general phenomenon in living organisms. Thus, long mononucleotide repeats may play an important role in base composition and genetic stability of a gene and gene functions.

Assessment of total uncertainty in cocaine and benzoylecgonine wastewater load measurements

To check the effectiveness of campaigns preventing drug abuse or indicating local effects of efforts against drug trafficking, it is beneficial to know consumed amounts of substances in a high spatial and temporal resolution. The analysis of drugs of abuse in wastewater (WW) has the potential to provide this information. In this study, the reliability of WW drug consumption estimates is assessed and a novel method presented to calculate the total uncertainty in observed WW cocaine (COC) and benzoylecgonine (BE) loads. Specifically, uncertainties resulting from discharge measurements, chemical analysis and the applied sampling scheme were addressed and three approaches presented. These consist of (i) a generic model-based procedure to investigate the influence of the sampling scheme on the uncertainty of observed or expected drug loads, (ii) a comparative analysis of two analytical methods (high performance liquid chromatography-tandem mass spectrometry and gas chromatography-mass spectrometry), including an extended cross-validation by influent profiling over several days, and (iii) monitoring COC and BE concentrations in WW of the largest Swiss sewage treatment plants. In addition, the COC and BE loads observed in the sewage treatment plant of the city of Berne were used to back-calculate the COC consumption. The estimated mean daily consumed amount was 107 ± 21 g of pure COC, corresponding to 321 g of street-grade COC.

Corpus-Based Speech Enhancement With Uncertainty Modeling and Cepstral Smoothing

We present a new approach for corpus-based speech enhancement that significantly improves over a method published by Xiao and Nickel in 2010. Corpus-based enhancement systems do not merely filter an incoming noisy signal, but resynthesize its speech content via an inventory of pre-recorded clean signals. The goal of the procedure is to perceptually improve the sound of speech signals in background noise. The proposed new method modifies Xiao's method in four significant ways. Firstly, it employs a Gaussian mixture model (GMM) instead of a vector quantizer in the phoneme recognition front-end. Secondly, the state decoding of the recognition stage is supported with an uncertainty modeling technique. With the GMM and the uncertainty modeling it is possible to eliminate the need for noise dependent system training. Thirdly, the post-processing of the original method via sinusoidal modeling is replaced with a powerful cepstral smoothing operation. And lastly, due to the improvements of these modifications, it is possible to extend the operational bandwidth of the procedure from 4 kHz to 8 kHz. The performance of the proposed method was evaluated across different noise types and different signal-to-noise ratios. The new method was able to significantly outperform traditional methods, including the one by Xiao and Nickel, in terms of PESQ scores and other objective quality measures. Results of subjective CMOS tests over a smaller set of test samples support our claims.