Chemical and cytological studies on the formation of lipid inclusions in b.cereus and other bacteria

it is apparent that all modes of survival during starvation are largely dependent on the possession of energy reserves, and it is not therefore surprising that energy rich substances are quantitatively so predominant. It should be pointed out, however, that nitrogenous compounds may be stored as frequently as energy rich reserves, and their apparent scarcity may be simply a reflection of the relatively small amounts required by the cell; for a given amount of growth or metabolic transformation much more carbon and energy source is required, weight for weight, than nitrogen source, and the carbon and energy source is therefore always more obvious and more easily detectable. The purely technical difficulties of detecting a nitro- genous reserve may also play a part; the only known nitro- genous substances which might act as reserves are protein and nucleic acids, and present analytical techniques would make it difficult to detect small storage amounts of these compounds among the essential structural and functional proteins and nucleic acids of the cell.In this connection there is the added difficulty that there is probably no hard and fast dividing line between materials that function as "expendable" nutrient reserves, and components of the organism that are "essential" to its existence. Under the stress of prolonged starvation, it is conceivable that an organism might, to a limited extent, utilise some of its "essential" constituents in order to maintain its viability. A rather specialised example of this phenomenon was demonstrated by Spiegelman and Dunn (194e). These authors found that when yeasts were adapted to the fermentation of galactose in the absence of an exter- nal nitrogen source, there was some loss of glucozymase activity. This loss could be prevented by the addition to the medium of a nitrogen source, and it was deduced that some of the glucozymase protein was being broken down and utilised for the synthesis of the galactozymase. Since failure to adapt would have resulted in starvation, one can regard this phenomenon as a specialised instance of a response to adverse nutritional conditions, a response which entailed the partial breakdown of an "essential" or "functional" (as opposed to reserve) cell constituent. These findings suggest the possibility that other components of the cell, normally regarded as "essential ", might be utilised similarly

Alien Registration- Williamson, Donald M. (Brownville, Piscataquis County)

https://digitalmaine.com/alien_docs/10511/thumbnail.jp

Mechanisms and the Evidence Hierarchy

Evidence-based medicine (EBM) makes use of explicit procedures for grading evidence for causal claims. Normally, these procedures categorise evidence of correlation produced by statistical trials as better evidence for a causal claim than evidence of mechanisms produced by other methods. We argue, in contrast, that evidence of mechanisms needs to be viewed as complementary to, rather than inferior to, evidence of correlation. In this paper we first set out the case for treating evidence of mechanisms alongside evidence of correlation in explicit protocols for evaluating evidence. Next we provide case studies which exemplify the ways in which evidence of mechanisms complements evidence of correlation in practice. Finally, we put forward some general considerations as to how the two sorts of evidence can be more closely integrated by EBM

Attention-based Speech Enhancement Using Human Quality Perception Modelling

Perceptually-inspired objective functions such as the perceptual evaluation of speech quality (PESQ), signal-to-distortion ratio (SDR), and short-time objective intelligibility (STOI), have recently been used to optimize performance of deep-learning-based speech enhancement algorithms. These objective functions, however, do not always strongly correlate with a listener's assessment of perceptual quality, so optimizing with these measures often results in poorer performance in real-world scenarios. In this work, we propose an attention-based enhancement approach that uses learned speech embedding vectors from a mean-opinion score (MOS) prediction model and a speech enhancement module to jointly enhance noisy speech. The MOS prediction model estimates the perceptual MOS of speech quality, as assessed by human listeners, directly from the audio signal. The enhancement module also employs a quantized language model that enforces spectral constraints for better speech realism and performance. We train the model using real-world noisy speech data that has been captured in everyday environments and test it using unseen corpora. The results show that our proposed approach significantly outperforms other approaches that are optimized with objective measures, where the predicted quality scores strongly correlate with human judgments.Comment: 11 pages, 4 figures, 3 tables, submitted in journal TASLP 202

Privacy-preserving and Privacy-attacking Approaches for Speech and Audio -- A Survey

In contemporary society, voice-controlled devices, such as smartphones and home assistants, have become pervasive due to their advanced capabilities and functionality. The always-on nature of their microphones offers users the convenience of readily accessing these devices. However, recent research and events have revealed that such voice-controlled devices are prone to various forms of malicious attacks, hence making it a growing concern for both users and researchers to safeguard against such attacks. Despite the numerous studies that have investigated adversarial attacks and privacy preservation for images, a conclusive study of this nature has not been conducted for the audio domain. Therefore, this paper aims to examine existing approaches for privacy-preserving and privacy-attacking strategies for audio and speech. To achieve this goal, we classify the attack and defense scenarios into several categories and provide detailed analysis of each approach. We also interpret the dissimilarities between the various approaches, highlight their contributions, and examine their limitations. Our investigation reveals that voice-controlled devices based on neural networks are inherently susceptible to specific types of attacks. Although it is possible to enhance the robustness of such models to certain forms of attack, more sophisticated approaches are required to comprehensively safeguard user privacy